diff --git a/bioimageio/core.html b/bioimageio/core.html index 3e1565cf..5ac45a9b 100644 --- a/bioimageio/core.html +++ b/bioimageio/core.html @@ -3,7 +3,7 @@ - + bioimageio.core API documentation @@ -354,31 +354,36 @@

0.5.10

def - test_resource( source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]], *, format_version: Union[Literal['discover', 'latest'], str] = 'discover', weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, decimal: int = 4, expected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary: + test_resource( source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]], *, format_version: Union[Literal['discover', 'latest'], str] = 'discover', weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, absolute_tolerance: float = 0.00015, relative_tolerance: float = 0.0001, decimal: Optional[int] = None, expected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:
- 
51def test_description(
-52    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
-53    *,
-54    format_version: Union[Literal["discover", "latest"], str] = "discover",
-55    weight_format: Optional[WeightsFormat] = None,
-56    devices: Optional[List[str]] = None,
-57    decimal: int = 4,
-58    expected_type: Optional[str] = None,
-59) -> ValidationSummary:
-60    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
-61    rd = load_description_and_test(
-62        source,
-63        format_version=format_version,
-64        weight_format=weight_format,
-65        devices=devices,
-66        decimal=decimal,
-67        expected_type=expected_type,
-68    )
-69    return rd.validation_summary
+            
56def test_description(
+57    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
+58    *,
+59    format_version: Union[Literal["discover", "latest"], str] = "discover",
+60    weight_format: Optional[WeightsFormat] = None,
+61    devices: Optional[List[str]] = None,
+62    absolute_tolerance: float = 1.5e-4,
+63    relative_tolerance: float = 1e-4,
+64    decimal: Optional[int] = None,
+65    expected_type: Optional[str] = None,
+66) -> ValidationSummary:
+67    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
+68    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+69    rd = load_description_and_test(
+70        source,
+71        format_version=format_version,
+72        weight_format=weight_format,
+73        devices=devices,
+74        absolute_tolerance=absolute_tolerance,
+75        relative_tolerance=relative_tolerance,
+76        decimal=decimal,
+77        expected_type=expected_type,
+78    )
+79    return rd.validation_summary
 

 
 
diff --git a/bioimageio/core/_magic_tensor_ops.html b/bioimageio/core/_magic_tensor_ops.html
index 8d7a6bfd..ac3c2ae4 100644
--- a/bioimageio/core/_magic_tensor_ops.html
+++ b/bioimageio/core/_magic_tensor_ops.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core._magic_tensor_ops API documentation
             
 
diff --git a/bioimageio/core/_op_base.html b/bioimageio/core/_op_base.html
index 1161805c..6abbce5f 100644
--- a/bioimageio/core/_op_base.html
+++ b/bioimageio/core/_op_base.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core._op_base API documentation
             
 
diff --git a/bioimageio/core/_prediction_pipeline.html b/bioimageio/core/_prediction_pipeline.html
index b9ecf851..55a896fd 100644
--- a/bioimageio/core/_prediction_pipeline.html
+++ b/bioimageio/core/_prediction_pipeline.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core._prediction_pipeline API documentation
             
 
diff --git a/bioimageio/core/_resource_tests.html b/bioimageio/core/_resource_tests.html
index 8a4766eb..d53c55df 100644
--- a/bioimageio/core/_resource_tests.html
+++ b/bioimageio/core/_resource_tests.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core._resource_tests API documentation
             
 
@@ -100,399 +100,458 @@ 

  35    source: Union[v0_5.ModelDescr, PermissiveFileSource],
  36    weight_format: Optional[WeightsFormat] = None,
  37    devices: Optional[List[str]] = None,
- 38    decimal: int = 4,
- 39) -> ValidationSummary:
- 40    """Test model inference"""
- 41    return test_description(
- 42        source,
- 43        weight_format=weight_format,
- 44        devices=devices,
- 45        decimal=decimal,
- 46        expected_type="model",
- 47    )
- 48
- 49
- 50def test_description(
- 51    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
- 52    *,
- 53    format_version: Union[Literal["discover", "latest"], str] = "discover",
- 54    weight_format: Optional[WeightsFormat] = None,
- 55    devices: Optional[List[str]] = None,
- 56    decimal: int = 4,
- 57    expected_type: Optional[str] = None,
- 58) -> ValidationSummary:
- 59    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
- 60    rd = load_description_and_test(
- 61        source,
- 62        format_version=format_version,
- 63        weight_format=weight_format,
- 64        devices=devices,
- 65        decimal=decimal,
- 66        expected_type=expected_type,
- 67    )
- 68    return rd.validation_summary
- 69
- 70
- 71def load_description_and_test(
- 72    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
- 73    *,
- 74    format_version: Union[Literal["discover", "latest"], str] = "discover",
- 75    weight_format: Optional[WeightsFormat] = None,
- 76    devices: Optional[List[str]] = None,
- 77    decimal: int = 4,
- 78    expected_type: Optional[str] = None,
- 79) -> Union[ResourceDescr, InvalidDescr]:
- 80    """Test RDF dynamically, e.g. model inference of test inputs"""
- 81    if (
- 82        isinstance(source, ResourceDescrBase)
- 83        and format_version != "discover"
- 84        and source.format_version != format_version
- 85    ):
- 86        warnings.warn(
- 87            f"deserializing source to ensure we validate and test using format {format_version}"
- 88        )
- 89        source = dump_description(source)
- 90
- 91    if isinstance(source, ResourceDescrBase):
- 92        rd = source
- 93    elif isinstance(source, dict):
- 94        rd = build_description(source, format_version=format_version)
- 95    else:
- 96        rd = load_description(source, format_version=format_version)
- 97
- 98    rd.validation_summary.env.append(
- 99        InstalledPackage(name="bioimageio.core", version=VERSION)
-100    )
-101
-102    if expected_type is not None:
-103        _test_expected_resource_type(rd, expected_type)
-104
-105    if isinstance(rd, (v0_4.ModelDescr, v0_5.ModelDescr)):
-106        if weight_format is None:
-107            weight_formats: List[WeightsFormat] = [
-108                w for w, we in rd.weights if we is not None
-109            ]  # pyright: ignore[reportAssignmentType]
-110        else:
-111            weight_formats = [weight_format]
-112        for w in weight_formats:
-113            _test_model_inference(rd, w, devices, decimal)
-114            if not isinstance(rd, v0_4.ModelDescr):
-115                _test_model_inference_parametrized(rd, w, devices)
-116
-117    # TODO: add execution of jupyter notebooks
-118    # TODO: add more tests
-119
-120    return rd
-121
-122
-123def _test_model_inference(
-124    model: Union[v0_4.ModelDescr, v0_5.ModelDescr],
-125    weight_format: WeightsFormat,
-126    devices: Optional[List[str]],
-127    decimal: int,
-128) -> None:
-129    test_name = "Reproduce test outputs from test inputs"
-130    logger.info("starting '{}'", test_name)
-131    error: Optional[str] = None
-132    tb: List[str] = []
-133    try:
-134        inputs = get_test_inputs(model)
-135        expected = get_test_outputs(model)
+ 38    absolute_tolerance: float = 1.5e-4,
+ 39    relative_tolerance: float = 1e-4,
+ 40    decimal: Optional[int] = None,
+ 41) -> ValidationSummary:
+ 42    """Test model inference"""
+ 43    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+ 44    return test_description(
+ 45        source,
+ 46        weight_format=weight_format,
+ 47        devices=devices,
+ 48        absolute_tolerance=absolute_tolerance,
+ 49        relative_tolerance=relative_tolerance,
+ 50        decimal=decimal,
+ 51        expected_type="model",
+ 52    )
+ 53
+ 54
+ 55def test_description(
+ 56    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
+ 57    *,
+ 58    format_version: Union[Literal["discover", "latest"], str] = "discover",
+ 59    weight_format: Optional[WeightsFormat] = None,
+ 60    devices: Optional[List[str]] = None,
+ 61    absolute_tolerance: float = 1.5e-4,
+ 62    relative_tolerance: float = 1e-4,
+ 63    decimal: Optional[int] = None,
+ 64    expected_type: Optional[str] = None,
+ 65) -> ValidationSummary:
+ 66    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
+ 67    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+ 68    rd = load_description_and_test(
+ 69        source,
+ 70        format_version=format_version,
+ 71        weight_format=weight_format,
+ 72        devices=devices,
+ 73        absolute_tolerance=absolute_tolerance,
+ 74        relative_tolerance=relative_tolerance,
+ 75        decimal=decimal,
+ 76        expected_type=expected_type,
+ 77    )
+ 78    return rd.validation_summary
+ 79
+ 80
+ 81def load_description_and_test(
+ 82    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
+ 83    *,
+ 84    format_version: Union[Literal["discover", "latest"], str] = "discover",
+ 85    weight_format: Optional[WeightsFormat] = None,
+ 86    devices: Optional[List[str]] = None,
+ 87    absolute_tolerance: float = 1.5e-4,
+ 88    relative_tolerance: float = 1e-4,
+ 89    decimal: Optional[int] = None,
+ 90    expected_type: Optional[str] = None,
+ 91) -> Union[ResourceDescr, InvalidDescr]:
+ 92    """Test RDF dynamically, e.g. model inference of test inputs"""
+ 93    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+ 94    if (
+ 95        isinstance(source, ResourceDescrBase)
+ 96        and format_version != "discover"
+ 97        and source.format_version != format_version
+ 98    ):
+ 99        warnings.warn(
+100            f"deserializing source to ensure we validate and test using format {format_version}"
+101        )
+102        source = dump_description(source)
+103
+104    if isinstance(source, ResourceDescrBase):
+105        rd = source
+106    elif isinstance(source, dict):
+107        rd = build_description(source, format_version=format_version)
+108    else:
+109        rd = load_description(source, format_version=format_version)
+110
+111    rd.validation_summary.env.append(
+112        InstalledPackage(name="bioimageio.core", version=VERSION)
+113    )
+114
+115    if expected_type is not None:
+116        _test_expected_resource_type(rd, expected_type)
+117
+118    if isinstance(rd, (v0_4.ModelDescr, v0_5.ModelDescr)):
+119        if weight_format is None:
+120            weight_formats: List[WeightsFormat] = [
+121                w for w, we in rd.weights if we is not None
+122            ]  # pyright: ignore[reportAssignmentType]
+123        else:
+124            weight_formats = [weight_format]
+125        for w in weight_formats:
+126            _test_model_inference(
+127                rd, w, devices, absolute_tolerance, relative_tolerance, decimal
+128            )
+129            if not isinstance(rd, v0_4.ModelDescr):
+130                _test_model_inference_parametrized(rd, w, devices)
+131
+132    # TODO: add execution of jupyter notebooks
+133    # TODO: add more tests
+134
+135    return rd
 136
-137        with create_prediction_pipeline(
-138            bioimageio_model=model, devices=devices, weight_format=weight_format
-139        ) as prediction_pipeline:
-140            results = prediction_pipeline.predict_sample_without_blocking(inputs)
-141
-142        if len(results.members) != len(expected.members):
-143            error = f"Expected {len(expected.members)} outputs, but got {len(results.members)}"
-144
-145        else:
-146            for m, exp in expected.members.items():
-147                res = results.members.get(m)
-148                if res is None:
-149                    error = "Output tensors for test case may not be None"
-150                    break
-151                try:
-152                    np.testing.assert_array_almost_equal(
-153                        res.data, exp.data, decimal=decimal
-154                    )
-155                except AssertionError as e:
-156                    error = f"Output and expected output disagree:\n {e}"
-157                    break
-158    except Exception as e:
-159        error = str(e)
-160        tb = traceback.format_tb(e.__traceback__)
-161
-162    model.validation_summary.add_detail(
-163        ValidationDetail(
-164            name=test_name,
-165            status="passed" if error is None else "failed",
-166            errors=(
-167                []
-168                if error is None
-169                else [
-170                    ErrorEntry(
-171                        loc=("weights", weight_format),
-172                        msg=error,
-173                        type="bioimageio.core",
-174                        traceback=tb,
-175                    )
-176                ]
-177            ),
-178        )
-179    )
-180
-181
-182def _test_model_inference_parametrized(
-183    model: v0_5.ModelDescr,
-184    weight_format: WeightsFormat,
-185    devices: Optional[List[str]],
-186) -> None:
-187    if not any(
-188        isinstance(a.size, v0_5.ParameterizedSize)
-189        for ipt in model.inputs
-190        for a in ipt.axes
-191    ):
-192        # no parameterized sizes => set n=0
-193        ns: Set[v0_5.ParameterizedSize.N] = {0}
-194    else:
-195        ns = {0, 1, 2}
-196
-197    given_batch_sizes = {
-198        a.size
-199        for ipt in model.inputs
-200        for a in ipt.axes
-201        if isinstance(a, v0_5.BatchAxis)
-202    }
-203    if given_batch_sizes:
-204        batch_sizes = {gbs for gbs in given_batch_sizes if gbs is not None}
-205        if not batch_sizes:
-206            # only arbitrary batch sizes
-207            batch_sizes = {1, 2}
-208    else:
-209        # no batch axis
-210        batch_sizes = {1}
-211
-212    test_cases: Set[Tuple[v0_5.ParameterizedSize.N, BatchSize]] = {
-213        (n, b) for n, b in product(sorted(ns), sorted(batch_sizes))
-214    }
-215    logger.info(
-216        "Testing inference with {} different input tensor sizes", len(test_cases)
-217    )
-218
-219    def generate_test_cases():
-220        tested: Set[Hashable] = set()
-221
-222        def get_ns(n: int):
-223            return {
-224                (t.id, a.id): n
-225                for t in model.inputs
-226                for a in t.axes
-227                if isinstance(a.size, v0_5.ParameterizedSize)
-228            }
-229
-230        for n, batch_size in sorted(test_cases):
-231            input_target_sizes, expected_output_sizes = model.get_axis_sizes(
-232                get_ns(n), batch_size=batch_size
-233            )
-234            hashable_target_size = tuple(
-235                (k, input_target_sizes[k]) for k in sorted(input_target_sizes)
-236            )
-237            if hashable_target_size in tested:
-238                continue
-239            else:
-240                tested.add(hashable_target_size)
-241
-242            resized_test_inputs = Sample(
-243                members={
-244                    t.id: test_inputs.members[t.id].resize_to(
-245                        {
-246                            aid: s
-247                            for (tid, aid), s in input_target_sizes.items()
-248                            if tid == t.id
-249                        },
-250                    )
-251                    for t in model.inputs
-252                },
-253                stat=test_inputs.stat,
-254                id=test_inputs.id,
-255            )
-256            expected_output_shapes = {
-257                t.id: {
-258                    aid: s
-259                    for (tid, aid), s in expected_output_sizes.items()
-260                    if tid == t.id
-261                }
-262                for t in model.outputs
-263            }
-264            yield n, batch_size, resized_test_inputs, expected_output_shapes
-265
-266    try:
-267        test_inputs = get_test_inputs(model)
+137
+138def _test_model_inference(
+139    model: Union[v0_4.ModelDescr, v0_5.ModelDescr],
+140    weight_format: WeightsFormat,
+141    devices: Optional[List[str]],
+142    absolute_tolerance: float,
+143    relative_tolerance: float,
+144    decimal: Optional[int],
+145) -> None:
+146    test_name = "Reproduce test outputs from test inputs"
+147    logger.info("starting '{}'", test_name)
+148    error: Optional[str] = None
+149    tb: List[str] = []
+150
+151    precision_args = _handle_legacy_precision_args(
+152        absolute_tolerance=absolute_tolerance,
+153        relative_tolerance=relative_tolerance,
+154        decimal=decimal,
+155    )
+156
+157    try:
+158        inputs = get_test_inputs(model)
+159        expected = get_test_outputs(model)
+160
+161        with create_prediction_pipeline(
+162            bioimageio_model=model, devices=devices, weight_format=weight_format
+163        ) as prediction_pipeline:
+164            results = prediction_pipeline.predict_sample_without_blocking(inputs)
+165
+166        if len(results.members) != len(expected.members):
+167            error = f"Expected {len(expected.members)} outputs, but got {len(results.members)}"
+168
+169        else:
+170            for m, exp in expected.members.items():
+171                res = results.members.get(m)
+172                if res is None:
+173                    error = "Output tensors for test case may not be None"
+174                    break
+175                try:
+176                    np.testing.assert_allclose(
+177                        res.data,
+178                        exp.data,
+179                        rtol=precision_args["relative_tolerance"],
+180                        atol=precision_args["absolute_tolerance"],
+181                    )
+182                except AssertionError as e:
+183                    error = f"Output and expected output disagree:\n {e}"
+184                    break
+185    except Exception as e:
+186        error = str(e)
+187        tb = traceback.format_tb(e.__traceback__)
+188
+189    model.validation_summary.add_detail(
+190        ValidationDetail(
+191            name=test_name,
+192            status="passed" if error is None else "failed",
+193            errors=(
+194                []
+195                if error is None
+196                else [
+197                    ErrorEntry(
+198                        loc=("weights", weight_format),
+199                        msg=error,
+200                        type="bioimageio.core",
+201                        traceback=tb,
+202                    )
+203                ]
+204            ),
+205        )
+206    )
+207
+208
+209def _test_model_inference_parametrized(
+210    model: v0_5.ModelDescr,
+211    weight_format: WeightsFormat,
+212    devices: Optional[List[str]],
+213) -> None:
+214    if not any(
+215        isinstance(a.size, v0_5.ParameterizedSize)
+216        for ipt in model.inputs
+217        for a in ipt.axes
+218    ):
+219        # no parameterized sizes => set n=0
+220        ns: Set[v0_5.ParameterizedSize.N] = {0}
+221    else:
+222        ns = {0, 1, 2}
+223
+224    given_batch_sizes = {
+225        a.size
+226        for ipt in model.inputs
+227        for a in ipt.axes
+228        if isinstance(a, v0_5.BatchAxis)
+229    }
+230    if given_batch_sizes:
+231        batch_sizes = {gbs for gbs in given_batch_sizes if gbs is not None}
+232        if not batch_sizes:
+233            # only arbitrary batch sizes
+234            batch_sizes = {1, 2}
+235    else:
+236        # no batch axis
+237        batch_sizes = {1}
+238
+239    test_cases: Set[Tuple[v0_5.ParameterizedSize.N, BatchSize]] = {
+240        (n, b) for n, b in product(sorted(ns), sorted(batch_sizes))
+241    }
+242    logger.info(
+243        "Testing inference with {} different input tensor sizes", len(test_cases)
+244    )
+245
+246    def generate_test_cases():
+247        tested: Set[Hashable] = set()
+248
+249        def get_ns(n: int):
+250            return {
+251                (t.id, a.id): n
+252                for t in model.inputs
+253                for a in t.axes
+254                if isinstance(a.size, v0_5.ParameterizedSize)
+255            }
+256
+257        for n, batch_size in sorted(test_cases):
+258            input_target_sizes, expected_output_sizes = model.get_axis_sizes(
+259                get_ns(n), batch_size=batch_size
+260            )
+261            hashable_target_size = tuple(
+262                (k, input_target_sizes[k]) for k in sorted(input_target_sizes)
+263            )
+264            if hashable_target_size in tested:
+265                continue
+266            else:
+267                tested.add(hashable_target_size)
 268
-269        with create_prediction_pipeline(
-270            bioimageio_model=model, devices=devices, weight_format=weight_format
-271        ) as prediction_pipeline:
-272            for n, batch_size, inputs, exptected_output_shape in generate_test_cases():
-273                error: Optional[str] = None
-274                result = prediction_pipeline.predict_sample_without_blocking(inputs)
-275                if len(result.members) != len(exptected_output_shape):
-276                    error = (
-277                        f"Expected {len(exptected_output_shape)} outputs,"
-278                        + f" but got {len(result.members)}"
-279                    )
-280
-281                else:
-282                    for m, exp in exptected_output_shape.items():
-283                        res = result.members.get(m)
-284                        if res is None:
-285                            error = "Output tensors may not be None for test case"
-286                            break
-287
-288                        diff: Dict[AxisId, int] = {}
-289                        for a, s in res.sizes.items():
-290                            if isinstance((e_aid := exp[AxisId(a)]), int):
-291                                if s != e_aid:
-292                                    diff[AxisId(a)] = s
-293                            elif (
-294                                s < e_aid.min or e_aid.max is not None and s > e_aid.max
-295                            ):
-296                                diff[AxisId(a)] = s
-297                        if diff:
-298                            error = (
-299                                f"(n={n}) Expected output shape {exp},"
-300                                + f" but got {res.sizes} (diff: {diff})"
-301                            )
-302                            break
-303
-304                model.validation_summary.add_detail(
-305                    ValidationDetail(
-306                        name=f"Run {weight_format} inference for inputs with"
-307                        + f" batch_size: {batch_size} and size parameter n: {n}",
-308                        status="passed" if error is None else "failed",
-309                        errors=(
-310                            []
-311                            if error is None
-312                            else [
-313                                ErrorEntry(
-314                                    loc=("weights", weight_format),
-315                                    msg=error,
-316                                    type="bioimageio.core",
-317                                )
-318                            ]
-319                        ),
-320                    )
-321                )
-322    except Exception as e:
-323        error = str(e)
-324        tb = traceback.format_tb(e.__traceback__)
-325        model.validation_summary.add_detail(
-326            ValidationDetail(
-327                name=f"Run {weight_format} inference for parametrized inputs",
-328                status="failed",
-329                errors=[
-330                    ErrorEntry(
-331                        loc=("weights", weight_format),
-332                        msg=error,
-333                        type="bioimageio.core",
-334                        traceback=tb,
-335                    )
-336                ],
-337            )
-338        )
-339
-340
-341def _test_expected_resource_type(
-342    rd: Union[InvalidDescr, ResourceDescr], expected_type: str
-343):
-344    has_expected_type = rd.type == expected_type
-345    rd.validation_summary.details.append(
-346        ValidationDetail(
-347            name="Has expected resource type",
-348            status="passed" if has_expected_type else "failed",
-349            errors=(
-350                []
-351                if has_expected_type
-352                else [
-353                    ErrorEntry(
-354                        loc=("type",),
-355                        type="type",
-356                        msg=f"expected type {expected_type}, found {rd.type}",
-357                    )
-358                ]
-359            ),
-360        )
-361    )
-362
-363
-364# def debug_model(
-365#     model_rdf: Union[RawResourceDescr, ResourceDescr, URI, Path, str],
-366#     *,
-367#     weight_format: Optional[WeightsFormat] = None,
-368#     devices: Optional[List[str]] = None,
-369# ):
-370#     """Run the model test and return dict with inputs, results, expected results and intermediates.
-371
-372#     Returns dict with tensors "inputs", "inputs_processed", "outputs_raw", "outputs", "expected" and "diff".
-373#     """
-374#     inputs_raw: Optional = None
-375#     inputs_processed: Optional = None
-376#     outputs_raw: Optional = None
-377#     outputs: Optional = None
-378#     expected: Optional = None
-379#     diff: Optional = None
-380
-381#     model = load_description(
-382#         model_rdf, weights_priority_order=None if weight_format is None else [weight_format]
-383#     )
-384#     if not isinstance(model, Model):
-385#         raise ValueError(f"Not a bioimageio.model: {model_rdf}")
-386
-387#     prediction_pipeline = create_prediction_pipeline(
-388#         bioimageio_model=model, devices=devices, weight_format=weight_format
-389#     )
-390#     inputs = [
-391#         xr.DataArray(load_array(str(in_path)), dims=input_spec.axes)
-392#         for in_path, input_spec in zip(model.test_inputs, model.inputs)
-393#     ]
-394#     input_dict = {input_spec.name: input for input_spec, input in zip(model.inputs, inputs)}
-395
-396#     # keep track of the non-processed inputs
-397#     inputs_raw = [deepcopy(input) for input in inputs]
-398
-399#     computed_measures = {}
-400
-401#     prediction_pipeline.apply_preprocessing(input_dict, computed_measures)
-402#     inputs_processed = list(input_dict.values())
-403#     outputs_raw = prediction_pipeline.predict(*inputs_processed)
-404#     output_dict = {output_spec.name: deepcopy(output) for output_spec, output in zip(model.outputs, outputs_raw)}
-405#     prediction_pipeline.apply_postprocessing(output_dict, computed_measures)
-406#     outputs = list(output_dict.values())
-407
-408#     if isinstance(outputs, (np.ndarray, xr.DataArray)):
-409#         outputs = [outputs]
-410
-411#     expected = [
-412#         xr.DataArray(load_array(str(out_path)), dims=output_spec.axes)
-413#         for out_path, output_spec in zip(model.test_outputs, model.outputs)
-414#     ]
-415#     if len(outputs) != len(expected):
-416#         error = f"Number of outputs and number of expected outputs disagree: {len(outputs)} != {len(expected)}"
-417#         print(error)
-418#     else:
-419#         diff = []
-420#         for res, exp in zip(outputs, expected):
-421#             diff.append(res - exp)
+269            resized_test_inputs = Sample(
+270                members={
+271                    t.id: test_inputs.members[t.id].resize_to(
+272                        {
+273                            aid: s
+274                            for (tid, aid), s in input_target_sizes.items()
+275                            if tid == t.id
+276                        },
+277                    )
+278                    for t in model.inputs
+279                },
+280                stat=test_inputs.stat,
+281                id=test_inputs.id,
+282            )
+283            expected_output_shapes = {
+284                t.id: {
+285                    aid: s
+286                    for (tid, aid), s in expected_output_sizes.items()
+287                    if tid == t.id
+288                }
+289                for t in model.outputs
+290            }
+291            yield n, batch_size, resized_test_inputs, expected_output_shapes
+292
+293    try:
+294        test_inputs = get_test_inputs(model)
+295
+296        with create_prediction_pipeline(
+297            bioimageio_model=model, devices=devices, weight_format=weight_format
+298        ) as prediction_pipeline:
+299            for n, batch_size, inputs, exptected_output_shape in generate_test_cases():
+300                error: Optional[str] = None
+301                result = prediction_pipeline.predict_sample_without_blocking(inputs)
+302                if len(result.members) != len(exptected_output_shape):
+303                    error = (
+304                        f"Expected {len(exptected_output_shape)} outputs,"
+305                        + f" but got {len(result.members)}"
+306                    )
+307
+308                else:
+309                    for m, exp in exptected_output_shape.items():
+310                        res = result.members.get(m)
+311                        if res is None:
+312                            error = "Output tensors may not be None for test case"
+313                            break
+314
+315                        diff: Dict[AxisId, int] = {}
+316                        for a, s in res.sizes.items():
+317                            if isinstance((e_aid := exp[AxisId(a)]), int):
+318                                if s != e_aid:
+319                                    diff[AxisId(a)] = s
+320                            elif (
+321                                s < e_aid.min or e_aid.max is not None and s > e_aid.max
+322                            ):
+323                                diff[AxisId(a)] = s
+324                        if diff:
+325                            error = (
+326                                f"(n={n}) Expected output shape {exp},"
+327                                + f" but got {res.sizes} (diff: {diff})"
+328                            )
+329                            break
+330
+331                model.validation_summary.add_detail(
+332                    ValidationDetail(
+333                        name=f"Run {weight_format} inference for inputs with"
+334                        + f" batch_size: {batch_size} and size parameter n: {n}",
+335                        status="passed" if error is None else "failed",
+336                        errors=(
+337                            []
+338                            if error is None
+339                            else [
+340                                ErrorEntry(
+341                                    loc=("weights", weight_format),
+342                                    msg=error,
+343                                    type="bioimageio.core",
+344                                )
+345                            ]
+346                        ),
+347                    )
+348                )
+349    except Exception as e:
+350        error = str(e)
+351        tb = traceback.format_tb(e.__traceback__)
+352        model.validation_summary.add_detail(
+353            ValidationDetail(
+354                name=f"Run {weight_format} inference for parametrized inputs",
+355                status="failed",
+356                errors=[
+357                    ErrorEntry(
+358                        loc=("weights", weight_format),
+359                        msg=error,
+360                        type="bioimageio.core",
+361                        traceback=tb,
+362                    )
+363                ],
+364            )
+365        )
+366
+367
+368def _test_expected_resource_type(
+369    rd: Union[InvalidDescr, ResourceDescr], expected_type: str
+370):
+371    has_expected_type = rd.type == expected_type
+372    rd.validation_summary.details.append(
+373        ValidationDetail(
+374            name="Has expected resource type",
+375            status="passed" if has_expected_type else "failed",
+376            errors=(
+377                []
+378                if has_expected_type
+379                else [
+380                    ErrorEntry(
+381                        loc=("type",),
+382                        type="type",
+383                        msg=f"expected type {expected_type}, found {rd.type}",
+384                    )
+385                ]
+386            ),
+387        )
+388    )
+389
+390
+391def _handle_legacy_precision_args(
+392    absolute_tolerance: float, relative_tolerance: float, decimal: Optional[int]
+393) -> Dict[str, float]:
+394    """
+395    Transform the precision arguments to conform with the current implementation.
+396
+397    If the deprecated `decimal` argument is used it overrides the new behaviour with
+398    the old behaviour.
+399    """
+400    # Already conforms with current implementation
+401    if decimal is None:
+402        return {
+403            "absolute_tolerance": absolute_tolerance,
+404            "relative_tolerance": relative_tolerance,
+405        }
+406
+407    warnings.warn(
+408        "The argument `decimal` has been depricated in favour of "
+409        + "`relative_tolerance` and `absolute_tolerance`, with different validation "
+410        + "logic, using `numpy.testing.assert_allclose, see "
+411        + "'https://numpy.org/doc/stable/reference/generated/"
+412        + "numpy.testing.assert_allclose.html'. Passing a value for `decimal` will "
+413        + "cause validation to revert to the old behaviour."
+414    )
+415    # decimal overrides new behaviour,
+416    #   have to convert the params to emulate old behaviour
+417    return {
+418        "absolute_tolerance": 1.5 * 10 ** (-decimal),
+419        "relative_tolerance": 0,
+420    }
+421
 422
-423#     return {
-424#         "inputs": inputs_raw,
-425#         "inputs_processed": inputs_processed,
-426#         "outputs_raw": outputs_raw,
-427#         "outputs": outputs,
-428#         "expected": expected,
-429#         "diff": diff,
-430#     }
+423# def debug_model(
+424#     model_rdf: Union[RawResourceDescr, ResourceDescr, URI, Path, str],
+425#     *,
+426#     weight_format: Optional[WeightsFormat] = None,
+427#     devices: Optional[List[str]] = None,
+428# ):
+429#     """Run the model test and return dict with inputs, results, expected results and intermediates.
+430
+431#     Returns dict with tensors "inputs", "inputs_processed", "outputs_raw", "outputs", "expected" and "diff".
+432#     """
+433#     inputs_raw: Optional = None
+434#     inputs_processed: Optional = None
+435#     outputs_raw: Optional = None
+436#     outputs: Optional = None
+437#     expected: Optional = None
+438#     diff: Optional = None
+439
+440#     model = load_description(
+441#         model_rdf, weights_priority_order=None if weight_format is None else [weight_format]
+442#     )
+443#     if not isinstance(model, Model):
+444#         raise ValueError(f"Not a bioimageio.model: {model_rdf}")
+445
+446#     prediction_pipeline = create_prediction_pipeline(
+447#         bioimageio_model=model, devices=devices, weight_format=weight_format
+448#     )
+449#     inputs = [
+450#         xr.DataArray(load_array(str(in_path)), dims=input_spec.axes)
+451#         for in_path, input_spec in zip(model.test_inputs, model.inputs)
+452#     ]
+453#     input_dict = {input_spec.name: input for input_spec, input in zip(model.inputs, inputs)}
+454
+455#     # keep track of the non-processed inputs
+456#     inputs_raw = [deepcopy(input) for input in inputs]
+457
+458#     computed_measures = {}
+459
+460#     prediction_pipeline.apply_preprocessing(input_dict, computed_measures)
+461#     inputs_processed = list(input_dict.values())
+462#     outputs_raw = prediction_pipeline.predict(*inputs_processed)
+463#     output_dict = {output_spec.name: deepcopy(output) for output_spec, output in zip(model.outputs, outputs_raw)}
+464#     prediction_pipeline.apply_postprocessing(output_dict, computed_measures)
+465#     outputs = list(output_dict.values())
+466
+467#     if isinstance(outputs, (np.ndarray, xr.DataArray)):
+468#         outputs = [outputs]
+469
+470#     expected = [
+471#         xr.DataArray(load_array(str(out_path)), dims=output_spec.axes)
+472#         for out_path, output_spec in zip(model.test_outputs, model.outputs)
+473#     ]
+474#     if len(outputs) != len(expected):
+475#         error = f"Number of outputs and number of expected outputs disagree: {len(outputs)} != {len(expected)}"
+476#         print(error)
+477#     else:
+478#         diff = []
+479#         for res, exp in zip(outputs, expected):
+480#             diff.append(res - exp)
+481
+482#     return {
+483#         "inputs": inputs_raw,
+484#         "inputs_processed": inputs_processed,
+485#         "outputs_raw": outputs_raw,
+486#         "outputs": outputs,
+487#         "expected": expected,
+488#         "diff": diff,
+489#     }
@@ -502,7 +561,7 @@

def - test_model( source: Union[bioimageio.spec.model.v0_5.ModelDescr, Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, decimal: int = 4) -> bioimageio.spec.summary.ValidationSummary: + test_model( source: Union[bioimageio.spec.model.v0_5.ModelDescr, Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]], weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, absolute_tolerance: float = 0.00015, relative_tolerance: float = 0.0001, decimal: Optional[int] = None) -> bioimageio.spec.summary.ValidationSummary: @@ -512,16 +571,21 @@

36 source: Union[v0_5.ModelDescr, PermissiveFileSource], 37 weight_format: Optional[WeightsFormat] = None, 38 devices: Optional[List[str]] = None, -39 decimal: int = 4, -40) -> ValidationSummary: -41 """Test model inference""" -42 return test_description( -43 source, -44 weight_format=weight_format, -45 devices=devices, -46 decimal=decimal, -47 expected_type="model", -48 ) +39 absolute_tolerance: float = 1.5e-4, +40 relative_tolerance: float = 1e-4, +41 decimal: Optional[int] = None, +42) -> ValidationSummary: +43 """Test model inference""" +44 # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference` +45 return test_description( +46 source, +47 weight_format=weight_format, +48 devices=devices, +49 absolute_tolerance=absolute_tolerance, +50 relative_tolerance=relative_tolerance, +51 decimal=decimal, +52 expected_type="model", +53 )

@@ -535,31 +599,36 @@

def - test_description( source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]], *, format_version: Union[Literal['discover', 'latest'], str] = 'discover', weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, decimal: int = 4, expected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary: + test_description( source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]], *, format_version: Union[Literal['discover', 'latest'], str] = 'discover', weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None, devices: Optional[List[str]] = None, absolute_tolerance: float = 0.00015, relative_tolerance: float = 0.0001, decimal: Optional[int] = None, expected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:
- 
51def test_description(
-52    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
-53    *,
-54    format_version: Union[Literal["discover", "latest"], str] = "discover",
-55    weight_format: Optional[WeightsFormat] = None,
-56    devices: Optional[List[str]] = None,
-57    decimal: int = 4,
-58    expected_type: Optional[str] = None,
-59) -> ValidationSummary:
-60    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
-61    rd = load_description_and_test(
-62        source,
-63        format_version=format_version,
-64        weight_format=weight_format,
-65        devices=devices,
-66        decimal=decimal,
-67        expected_type=expected_type,
-68    )
-69    return rd.validation_summary
+            
56def test_description(
+57    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
+58    *,
+59    format_version: Union[Literal["discover", "latest"], str] = "discover",
+60    weight_format: Optional[WeightsFormat] = None,
+61    devices: Optional[List[str]] = None,
+62    absolute_tolerance: float = 1.5e-4,
+63    relative_tolerance: float = 1e-4,
+64    decimal: Optional[int] = None,
+65    expected_type: Optional[str] = None,
+66) -> ValidationSummary:
+67    """Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models"""
+68    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+69    rd = load_description_and_test(
+70        source,
+71        format_version=format_version,
+72        weight_format=weight_format,
+73        devices=devices,
+74        absolute_tolerance=absolute_tolerance,
+75        relative_tolerance=relative_tolerance,
+76        decimal=decimal,
+77        expected_type=expected_type,
+78    )
+79    return rd.validation_summary
 

 
 
@@ -573,62 +642,67 @@ 

 

             
         def
-        load_description_and_test(	source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],	*,	format_version: Union[Literal['discover', 'latest'], str] = 'discover',	weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,	devices: Optional[List[str]] = None,	decimal: int = 4,	expected_type: Optional[str] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:
+        load_description_and_test(	source: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],	*,	format_version: Union[Literal['discover', 'latest'], str] = 'discover',	weight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,	devices: Optional[List[str]] = None,	absolute_tolerance: float = 0.00015,	relative_tolerance: float = 0.0001,	decimal: Optional[int] = None,	expected_type: Optional[str] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:
 
                 
 
     

     
-            
 72def load_description_and_test(
- 73    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
- 74    *,
- 75    format_version: Union[Literal["discover", "latest"], str] = "discover",
- 76    weight_format: Optional[WeightsFormat] = None,
- 77    devices: Optional[List[str]] = None,
- 78    decimal: int = 4,
- 79    expected_type: Optional[str] = None,
- 80) -> Union[ResourceDescr, InvalidDescr]:
- 81    """Test RDF dynamically, e.g. model inference of test inputs"""
- 82    if (
- 83        isinstance(source, ResourceDescrBase)
- 84        and format_version != "discover"
- 85        and source.format_version != format_version
- 86    ):
- 87        warnings.warn(
- 88            f"deserializing source to ensure we validate and test using format {format_version}"
- 89        )
- 90        source = dump_description(source)
- 91
- 92    if isinstance(source, ResourceDescrBase):
- 93        rd = source
- 94    elif isinstance(source, dict):
- 95        rd = build_description(source, format_version=format_version)
- 96    else:
- 97        rd = load_description(source, format_version=format_version)
- 98
- 99    rd.validation_summary.env.append(
-100        InstalledPackage(name="bioimageio.core", version=VERSION)
-101    )
-102
-103    if expected_type is not None:
-104        _test_expected_resource_type(rd, expected_type)
-105
-106    if isinstance(rd, (v0_4.ModelDescr, v0_5.ModelDescr)):
-107        if weight_format is None:
-108            weight_formats: List[WeightsFormat] = [
-109                w for w, we in rd.weights if we is not None
-110            ]  # pyright: ignore[reportAssignmentType]
-111        else:
-112            weight_formats = [weight_format]
-113        for w in weight_formats:
-114            _test_model_inference(rd, w, devices, decimal)
-115            if not isinstance(rd, v0_4.ModelDescr):
-116                _test_model_inference_parametrized(rd, w, devices)
-117
-118    # TODO: add execution of jupyter notebooks
-119    # TODO: add more tests
-120
-121    return rd
+            
 82def load_description_and_test(
+ 83    source: Union[ResourceDescr, PermissiveFileSource, BioimageioYamlContent],
+ 84    *,
+ 85    format_version: Union[Literal["discover", "latest"], str] = "discover",
+ 86    weight_format: Optional[WeightsFormat] = None,
+ 87    devices: Optional[List[str]] = None,
+ 88    absolute_tolerance: float = 1.5e-4,
+ 89    relative_tolerance: float = 1e-4,
+ 90    decimal: Optional[int] = None,
+ 91    expected_type: Optional[str] = None,
+ 92) -> Union[ResourceDescr, InvalidDescr]:
+ 93    """Test RDF dynamically, e.g. model inference of test inputs"""
+ 94    # NOTE: `decimal` is a legacy argument and is handled in `_test_model_inference`
+ 95    if (
+ 96        isinstance(source, ResourceDescrBase)
+ 97        and format_version != "discover"
+ 98        and source.format_version != format_version
+ 99    ):
+100        warnings.warn(
+101            f"deserializing source to ensure we validate and test using format {format_version}"
+102        )
+103        source = dump_description(source)
+104
+105    if isinstance(source, ResourceDescrBase):
+106        rd = source
+107    elif isinstance(source, dict):
+108        rd = build_description(source, format_version=format_version)
+109    else:
+110        rd = load_description(source, format_version=format_version)
+111
+112    rd.validation_summary.env.append(
+113        InstalledPackage(name="bioimageio.core", version=VERSION)
+114    )
+115
+116    if expected_type is not None:
+117        _test_expected_resource_type(rd, expected_type)
+118
+119    if isinstance(rd, (v0_4.ModelDescr, v0_5.ModelDescr)):
+120        if weight_format is None:
+121            weight_formats: List[WeightsFormat] = [
+122                w for w, we in rd.weights if we is not None
+123            ]  # pyright: ignore[reportAssignmentType]
+124        else:
+125            weight_formats = [weight_format]
+126        for w in weight_formats:
+127            _test_model_inference(
+128                rd, w, devices, absolute_tolerance, relative_tolerance, decimal
+129            )
+130            if not isinstance(rd, v0_4.ModelDescr):
+131                _test_model_inference_parametrized(rd, w, devices)
+132
+133    # TODO: add execution of jupyter notebooks
+134    # TODO: add more tests
+135
+136    return rd
 

 
 
diff --git a/bioimageio/core/_settings.html b/bioimageio/core/_settings.html
index e87918be..4a3dc7f7 100644
--- a/bioimageio/core/_settings.html
+++ b/bioimageio/core/_settings.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core._settings API documentation
             
 
diff --git a/bioimageio/core/axis.html b/bioimageio/core/axis.html
index 79821196..4ebc2022 100644
--- a/bioimageio/core/axis.html
+++ b/bioimageio/core/axis.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.axis API documentation
             
 
diff --git a/bioimageio/core/block.html b/bioimageio/core/block.html
index adba1008..eb2889de 100644
--- a/bioimageio/core/block.html
+++ b/bioimageio/core/block.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.block API documentation
             
 
diff --git a/bioimageio/core/block_meta.html b/bioimageio/core/block_meta.html
index b2cfe661..ffcfdc09 100644
--- a/bioimageio/core/block_meta.html
+++ b/bioimageio/core/block_meta.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.block_meta API documentation
             
 
diff --git a/bioimageio/core/commands.html b/bioimageio/core/commands.html
index 5bff6013..77987513 100644
--- a/bioimageio/core/commands.html
+++ b/bioimageio/core/commands.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.commands API documentation
             
 
diff --git a/bioimageio/core/common.html b/bioimageio/core/common.html
index 27ec9cb3..7ddc96d6 100644
--- a/bioimageio/core/common.html
+++ b/bioimageio/core/common.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.common API documentation
             
 
diff --git a/bioimageio/core/dataset.html b/bioimageio/core/dataset.html
index 8145923c..2be0e64e 100644
--- a/bioimageio/core/dataset.html
+++ b/bioimageio/core/dataset.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.dataset API documentation
             
 
diff --git a/bioimageio/core/digest_spec.html b/bioimageio/core/digest_spec.html
index 20e9aeaf..c66e4505 100644
--- a/bioimageio/core/digest_spec.html
+++ b/bioimageio/core/digest_spec.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.digest_spec API documentation
             
 
diff --git a/bioimageio/core/io.html b/bioimageio/core/io.html
index c91ce8df..16d24474 100644
--- a/bioimageio/core/io.html
+++ b/bioimageio/core/io.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.io API documentation
             
 
diff --git a/bioimageio/core/model_adapters.html b/bioimageio/core/model_adapters.html
index d5653d53..3b856585 100644
--- a/bioimageio/core/model_adapters.html
+++ b/bioimageio/core/model_adapters.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_keras_model_adapter.html b/bioimageio/core/model_adapters/_keras_model_adapter.html
index 6dd1ef8e..33ce0617 100644
--- a/bioimageio/core/model_adapters/_keras_model_adapter.html
+++ b/bioimageio/core/model_adapters/_keras_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._keras_model_adapter API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_model_adapter.html b/bioimageio/core/model_adapters/_model_adapter.html
index a5cbac4e..ad2c3628 100644
--- a/bioimageio/core/model_adapters/_model_adapter.html
+++ b/bioimageio/core/model_adapters/_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._model_adapter API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_onnx_model_adapter.html b/bioimageio/core/model_adapters/_onnx_model_adapter.html
index 80a84fe3..1c03b47b 100644
--- a/bioimageio/core/model_adapters/_onnx_model_adapter.html
+++ b/bioimageio/core/model_adapters/_onnx_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._onnx_model_adapter API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_pytorch_model_adapter.html b/bioimageio/core/model_adapters/_pytorch_model_adapter.html
index 3427fb88..59236f9d 100644
--- a/bioimageio/core/model_adapters/_pytorch_model_adapter.html
+++ b/bioimageio/core/model_adapters/_pytorch_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._pytorch_model_adapter API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_tensorflow_model_adapter.html b/bioimageio/core/model_adapters/_tensorflow_model_adapter.html
index 431225e5..1f481c0e 100644
--- a/bioimageio/core/model_adapters/_tensorflow_model_adapter.html
+++ b/bioimageio/core/model_adapters/_tensorflow_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._tensorflow_model_adapter API documentation
             
 
diff --git a/bioimageio/core/model_adapters/_torchscript_model_adapter.html b/bioimageio/core/model_adapters/_torchscript_model_adapter.html
index 7154f39a..a1178a5d 100644
--- a/bioimageio/core/model_adapters/_torchscript_model_adapter.html
+++ b/bioimageio/core/model_adapters/_torchscript_model_adapter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.model_adapters._torchscript_model_adapter API documentation
             
 
diff --git a/bioimageio/core/prediction.html b/bioimageio/core/prediction.html
index d981a3af..dc9d4858 100644
--- a/bioimageio/core/prediction.html
+++ b/bioimageio/core/prediction.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.prediction API documentation
             
 
diff --git a/bioimageio/core/proc_ops.html b/bioimageio/core/proc_ops.html
index 08e62b31..7dffd8f8 100644
--- a/bioimageio/core/proc_ops.html
+++ b/bioimageio/core/proc_ops.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.proc_ops API documentation
             
 
diff --git a/bioimageio/core/proc_setup.html b/bioimageio/core/proc_setup.html
index e8c2b236..a4e6d44c 100644
--- a/bioimageio/core/proc_setup.html
+++ b/bioimageio/core/proc_setup.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.proc_setup API documentation
             
 
diff --git a/bioimageio/core/sample.html b/bioimageio/core/sample.html
index 3f6652fa..fe5820cc 100644
--- a/bioimageio/core/sample.html
+++ b/bioimageio/core/sample.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.sample API documentation
             
 
diff --git a/bioimageio/core/stat_calculators.html b/bioimageio/core/stat_calculators.html
index 4fef6811..a3ec7e16 100644
--- a/bioimageio/core/stat_calculators.html
+++ b/bioimageio/core/stat_calculators.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.stat_calculators API documentation
             
 
diff --git a/bioimageio/core/stat_measures.html b/bioimageio/core/stat_measures.html
index 5294f965..c06c6367 100644
--- a/bioimageio/core/stat_measures.html
+++ b/bioimageio/core/stat_measures.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.stat_measures API documentation
             
 
@@ -447,33 +447,33 @@ 

 
     

     
-            
1758def _no_init_or_replace_init(self, *args, **kwargs):
-1759    cls = type(self)
-1760
-1761    if cls._is_protocol:
-1762        raise TypeError('Protocols cannot be instantiated')
-1763
-1764    # Already using a custom `__init__`. No need to calculate correct
-1765    # `__init__` to call. This can lead to RecursionError. See bpo-45121.
-1766    if cls.__init__ is not _no_init_or_replace_init:
-1767        return
-1768
-1769    # Initially, `__init__` of a protocol subclass is set to `_no_init_or_replace_init`.
-1770    # The first instantiation of the subclass will call `_no_init_or_replace_init` which
-1771    # searches for a proper new `__init__` in the MRO. The new `__init__`
-1772    # replaces the subclass' old `__init__` (ie `_no_init_or_replace_init`). Subsequent
-1773    # instantiation of the protocol subclass will thus use the new
-1774    # `__init__` and no longer call `_no_init_or_replace_init`.
-1775    for base in cls.__mro__:
-1776        init = base.__dict__.get('__init__', _no_init_or_replace_init)
-1777        if init is not _no_init_or_replace_init:
-1778            cls.__init__ = init
-1779            break
-1780    else:
-1781        # should not happen
-1782        cls.__init__ = object.__init__
-1783
-1784    cls.__init__(self, *args, **kwargs)
+            
1767def _no_init_or_replace_init(self, *args, **kwargs):
+1768    cls = type(self)
+1769
+1770    if cls._is_protocol:
+1771        raise TypeError('Protocols cannot be instantiated')
+1772
+1773    # Already using a custom `__init__`. No need to calculate correct
+1774    # `__init__` to call. This can lead to RecursionError. See bpo-45121.
+1775    if cls.__init__ is not _no_init_or_replace_init:
+1776        return
+1777
+1778    # Initially, `__init__` of a protocol subclass is set to `_no_init_or_replace_init`.
+1779    # The first instantiation of the subclass will call `_no_init_or_replace_init` which
+1780    # searches for a proper new `__init__` in the MRO. The new `__init__`
+1781    # replaces the subclass' old `__init__` (ie `_no_init_or_replace_init`). Subsequent
+1782    # instantiation of the protocol subclass will thus use the new
+1783    # `__init__` and no longer call `_no_init_or_replace_init`.
+1784    for base in cls.__mro__:
+1785        init = base.__dict__.get('__init__', _no_init_or_replace_init)
+1786        if init is not _no_init_or_replace_init:
+1787            cls.__init__ = init
+1788            break
+1789    else:
+1790        # should not happen
+1791        cls.__init__ = object.__init__
+1792
+1793    cls.__init__(self, *args, **kwargs)
 

 
 
diff --git a/bioimageio/core/tensor.html b/bioimageio/core/tensor.html
index 51feaef8..c3995b0b 100644
--- a/bioimageio/core/tensor.html
+++ b/bioimageio/core/tensor.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.tensor API documentation
             
 
diff --git a/bioimageio/core/utils.html b/bioimageio/core/utils.html
index 98a2854a..ae813bc3 100644
--- a/bioimageio/core/utils.html
+++ b/bioimageio/core/utils.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.utils API documentation
             
 
diff --git a/bioimageio/core/utils/testing.html b/bioimageio/core/utils/testing.html
index bc900563..b92a93a0 100644
--- a/bioimageio/core/utils/testing.html
+++ b/bioimageio/core/utils/testing.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.utils.testing API documentation
             
 
@@ -160,33 +160,33 @@ 

 
     

     
-            
1758def _no_init_or_replace_init(self, *args, **kwargs):
-1759    cls = type(self)
-1760
-1761    if cls._is_protocol:
-1762        raise TypeError('Protocols cannot be instantiated')
-1763
-1764    # Already using a custom `__init__`. No need to calculate correct
-1765    # `__init__` to call. This can lead to RecursionError. See bpo-45121.
-1766    if cls.__init__ is not _no_init_or_replace_init:
-1767        return
-1768
-1769    # Initially, `__init__` of a protocol subclass is set to `_no_init_or_replace_init`.
-1770    # The first instantiation of the subclass will call `_no_init_or_replace_init` which
-1771    # searches for a proper new `__init__` in the MRO. The new `__init__`
-1772    # replaces the subclass' old `__init__` (ie `_no_init_or_replace_init`). Subsequent
-1773    # instantiation of the protocol subclass will thus use the new
-1774    # `__init__` and no longer call `_no_init_or_replace_init`.
-1775    for base in cls.__mro__:
-1776        init = base.__dict__.get('__init__', _no_init_or_replace_init)
-1777        if init is not _no_init_or_replace_init:
-1778            cls.__init__ = init
-1779            break
-1780    else:
-1781        # should not happen
-1782        cls.__init__ = object.__init__
-1783
-1784    cls.__init__(self, *args, **kwargs)
+            
1767def _no_init_or_replace_init(self, *args, **kwargs):
+1768    cls = type(self)
+1769
+1770    if cls._is_protocol:
+1771        raise TypeError('Protocols cannot be instantiated')
+1772
+1773    # Already using a custom `__init__`. No need to calculate correct
+1774    # `__init__` to call. This can lead to RecursionError. See bpo-45121.
+1775    if cls.__init__ is not _no_init_or_replace_init:
+1776        return
+1777
+1778    # Initially, `__init__` of a protocol subclass is set to `_no_init_or_replace_init`.
+1779    # The first instantiation of the subclass will call `_no_init_or_replace_init` which
+1780    # searches for a proper new `__init__` in the MRO. The new `__init__`
+1781    # replaces the subclass' old `__init__` (ie `_no_init_or_replace_init`). Subsequent
+1782    # instantiation of the protocol subclass will thus use the new
+1783    # `__init__` and no longer call `_no_init_or_replace_init`.
+1784    for base in cls.__mro__:
+1785        init = base.__dict__.get('__init__', _no_init_or_replace_init)
+1786        if init is not _no_init_or_replace_init:
+1787            cls.__init__ = init
+1788            break
+1789    else:
+1790        # should not happen
+1791        cls.__init__ = object.__init__
+1792
+1793    cls.__init__(self, *args, **kwargs)
 

 
 
diff --git a/bioimageio/core/weight_converter.html b/bioimageio/core/weight_converter.html
index 61768bb5..15a21149 100644
--- a/bioimageio/core/weight_converter.html
+++ b/bioimageio/core/weight_converter.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter API documentation
             
 
diff --git a/bioimageio/core/weight_converter/keras.html b/bioimageio/core/weight_converter/keras.html
index b944b6fc..6cef40ce 100644
--- a/bioimageio/core/weight_converter/keras.html
+++ b/bioimageio/core/weight_converter/keras.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.keras API documentation
             
 
diff --git a/bioimageio/core/weight_converter/keras/_tensorflow.html b/bioimageio/core/weight_converter/keras/_tensorflow.html
index ab4a7fc7..30ffeeb8 100644
--- a/bioimageio/core/weight_converter/keras/_tensorflow.html
+++ b/bioimageio/core/weight_converter/keras/_tensorflow.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.keras._tensorflow API documentation
             
 
diff --git a/bioimageio/core/weight_converter/torch.html b/bioimageio/core/weight_converter/torch.html
index 5a88fbae..9d5300af 100644
--- a/bioimageio/core/weight_converter/torch.html
+++ b/bioimageio/core/weight_converter/torch.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.torch API documentation
             
 
diff --git a/bioimageio/core/weight_converter/torch/_onnx.html b/bioimageio/core/weight_converter/torch/_onnx.html
index 2be5e682..c7adf701 100644
--- a/bioimageio/core/weight_converter/torch/_onnx.html
+++ b/bioimageio/core/weight_converter/torch/_onnx.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.torch._onnx API documentation
             
 
diff --git a/bioimageio/core/weight_converter/torch/_torchscript.html b/bioimageio/core/weight_converter/torch/_torchscript.html
index f17ba85f..a0569e94 100644
--- a/bioimageio/core/weight_converter/torch/_torchscript.html
+++ b/bioimageio/core/weight_converter/torch/_torchscript.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.torch._torchscript API documentation
             
 
diff --git a/bioimageio/core/weight_converter/torch/_utils.html b/bioimageio/core/weight_converter/torch/_utils.html
index fdd9a312..d4b1641f 100644
--- a/bioimageio/core/weight_converter/torch/_utils.html
+++ b/bioimageio/core/weight_converter/torch/_utils.html
@@ -3,7 +3,7 @@
 
     
     
-    
+    
     bioimageio.core.weight_converter.torch._utils API documentation
             
 
diff --git a/search.js b/search.js
index cf2c42df..fd089161 100644
--- a/search.js
+++ b/search.js
@@ -1,6 +1,6 @@
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\n\n
core-bioimage-io-python
\n\n
Python specific core utilities for bioimage.io resources (in particular models).
\n\n
Installation
\n\n
Via Mamba/Conda
\n\n
The bioimageio.core package can be installed from conda-forge via
\n\n
\n
mamba install -c conda-forge bioimageio.core\n
\n
\n\n
If you do not install any additional deep learning libraries, you will only be able to use general convenience\nfunctionality, but not any functionality for model prediction.\nTo install additional deep learning libraries use:
\n\n
    \n
  • Pytorch/Torchscript:
    \n\n
    CPU installation (if you don't have an nvidia graphics card):
    \n\n
    \n
    mamba install -c pytorch -c conda-forge bioimageio.core pytorch torchvision cpuonly\n
    \n
    \n\n
    GPU installation (for cuda 11.6, please choose the appropriate cuda version for your system):
    \n\n
    \n
    mamba install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.8\n
    \n
    \n\n
    Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to pytorch.org.
    • \n
  • Tensorflow
    \n\n
    Currently only CPU version supported
    \n\n
    \n
    mamba install -c conda-forge bioimageio.core tensorflow\n
    \n
    • \n\n
  • ONNXRuntime
    \n\n
    Currently only cpu version supported
    \n\n
    \n
    mamba install -c conda-forge bioimageio.core onnxruntime\n
    \n
    • \n
\n\n
Via pip
\n\n
The package is also available via pip\n(e.g. with recommended extras onnx and pytorch):
\n\n
\n
pip install "bioimageio.core[onnx,pytorch]"\n
\n
\n\n
Set up Development Environment
\n\n
To set up a development conda environment run the following commands:
\n\n
\n
mamba env create -f dev/env.yaml\nmamba activate core\npip install -e . --no-deps\n
\n
\n\n
There are different environment files available that only install tensorflow or pytorch as dependencies.
\n\n
\ud83d\udcbb Use the Command Line Interface
\n\n
bioimageio.core installs a command line interface (CLI) for testing models and other functionality.\nYou can list all the available commands via:
\n\n
\n
bioimageio\n
\n
\n\n
Check that a model adheres to the model spec:
\n\n
\n
bioimageio validate <MODEL>\n
\n
\n\n
Test a model (including prediction for the test input):
\n\n
\n
bioimageio test-model <MODEL>\n
\n
\n\n
Run prediction for an image stored on disc:
\n\n
\n
bioimageio predict-image <MODEL> --inputs <INPUT> --outputs <OUTPUT>\n
\n
\n\n
Run prediction for multiple images stored on disc:
\n\n
\n
bioimagei predict-images -m <MODEL> -i <INPUT_PATTERN> - o <OUTPUT_FOLDER>\n
\n
\n\n
<INPUT_PATTERN> is a glob pattern to select the desired images, e.g. /path/to/my/images/*.tif.
\n\n
\ud83d\udc0d Use in Python
\n\n
bioimageio.core is a python package that implements prediction with bioimageio models\nincluding standardized pre- and postprocessing operations.\nThese models are described by---and can be loaded with---the bioimageio.spec package.
\n\n
In addition bioimageio.core provides functionality to convert model weight formats.
\n\n
To get an overview of this functionality, check out these example notebooks:
\n\n\n\n
and the developer documentation.
\n\n
Model Specification
\n\n
The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.
\n\n
Changelog
\n\n
0.6.8
\n\n
    \n
  • testing model inference will now check all weight formats\n(previously only the first one for which model adapter creation succeeded had been checked)
    • \n
  • fix predict with blocking (Thanks @thodkatz)
    • \n
\n\n
0.6.7
\n\n
    \n
  • predict() argument inputs may be sample
    • \n
\n\n
0.6.6
\n\n
    \n
  • add aliases to match previous API more closely
    • \n
\n\n
0.6.5
\n\n
    \n
  • improve adapter error messages
    • \n
\n\n
0.6.4
\n\n
    \n
  • add bioimageio validate-format command
    • \n
  • improve error messages and display of command results
    • \n
\n\n
0.6.3
\n\n
    \n
  • Fix #386
    • \n
  • (in model inference testing) stop assuming model inputs are tileable
    • \n
\n\n
0.6.2
\n\n\n\n
0.6.1
\n\n\n\n
0.6.0
\n\n
    \n
  • add compatibility with new bioimageio.spec 0.5 (0.5.2post1)
    • \n
  • improve interfaces
    • \n
\n\n
0.5.10
\n\n\n"}, "bioimageio.core.test_resource": {"fullname": "bioimageio.core.test_resource", "modulename": "bioimageio.core", "qualname": "test_resource", "kind": "function", "doc": "
Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models
\n", "signature": "(\tsource: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],\t*,\tformat_version: Union[Literal['discover', 'latest'], str] = 'discover',\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\tdevices: Optional[List[str]] = None,\tdecimal: int = 4,\texpected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:", "funcdef": "def"}, "bioimageio.core.load_resource": {"fullname": "bioimageio.core.load_resource", "modulename": "bioimageio.core", "qualname": "load_resource", "kind": "function", "doc": "
load a bioimage.io resource description
\n\n
Args:\n    source: Path or URL to an rdf.yaml or a bioimage.io package\n            (zip-file with rdf.yaml in it).\n    format_version: (optional) Use this argument to load the resource and\n                    convert its metadata to a higher format_version.\n    perform_io_checks: Wether or not to perform validation that requires file io,\n                       e.g. downloading a remote files. The existence of local\n                       absolute file paths is still being checked.\n    known_files: Allows to bypass download and hashing of referenced files\n                 (even if perform_io_checks is True).
\n\n
Returns:\n    An object holding all metadata of the bioimage.io resource
\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.load_model": {"fullname": "bioimageio.core.load_model", "modulename": "bioimageio.core", "qualname": "load_model", "kind": "function", "doc": "
load a bioimage.io resource description
\n\n
Args:\n    source: Path or URL to an rdf.yaml or a bioimage.io package\n            (zip-file with rdf.yaml in it).\n    format_version: (optional) Use this argument to load the resource and\n                    convert its metadata to a higher format_version.\n    perform_io_checks: Wether or not to perform validation that requires file io,\n                       e.g. downloading a remote files. The existence of local\n                       absolute file paths is still being checked.\n    known_files: Allows to bypass download and hashing of referenced files\n                 (even if perform_io_checks is True).
\n\n
Returns:\n    An object holding all metadata of the bioimage.io resource
\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.axis": {"fullname": "bioimageio.core.axis", "modulename": "bioimageio.core.axis", "kind": "module", "doc": "
\n"}, "bioimageio.core.axis.AxisId": {"fullname": "bioimageio.core.axis.AxisId", "modulename": "bioimageio.core.axis", "qualname": "AxisId", "kind": "class", "doc": "
str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str
\n\n
Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.
\n", "bases": "bioimageio.spec._internal.types.LowerCaseIdentifier"}, "bioimageio.core.axis.AxisId.root_model": {"fullname": "bioimageio.core.axis.AxisId.root_model", "modulename": "bioimageio.core.axis", "qualname": "AxisId.root_model", "kind": "variable", "doc": "
the pydantic root model to validate the string
\n", "annotation": ": ClassVar[Type[pydantic.root_model.RootModel[Any]]]", "default_value": "<class 'pydantic.root_model.RootModel[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.core.axis.PerAxis": {"fullname": "bioimageio.core.axis.PerAxis", "modulename": "bioimageio.core.axis", "qualname": "PerAxis", "kind": "variable", "doc": "
\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.AxisId, ~T]"}, "bioimageio.core.axis.BatchSize": {"fullname": "bioimageio.core.axis.BatchSize", "modulename": "bioimageio.core.axis", "qualname": "BatchSize", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.axis.AxisLetter": {"fullname": "bioimageio.core.axis.AxisLetter", "modulename": "bioimageio.core.axis", "qualname": "AxisLetter", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x']"}, "bioimageio.core.axis.AxisLike": {"fullname": "bioimageio.core.axis.AxisLike", "modulename": "bioimageio.core.axis", "qualname": "AxisLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], ForwardRef('Axis')]"}, "bioimageio.core.axis.Axis": {"fullname": "bioimageio.core.axis.Axis", "modulename": "bioimageio.core.axis", "qualname": "Axis", "kind": "class", "doc": "
\n"}, "bioimageio.core.axis.Axis.__init__": {"fullname": "bioimageio.core.axis.Axis.__init__", "modulename": "bioimageio.core.axis", "qualname": "Axis.__init__", "kind": "function", "doc": "
\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'])"}, "bioimageio.core.axis.Axis.id": {"fullname": "bioimageio.core.axis.Axis.id", "modulename": "bioimageio.core.axis", "qualname": "Axis.id", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.axis.Axis.type": {"fullname": "bioimageio.core.axis.Axis.type", "modulename": "bioimageio.core.axis", "qualname": "Axis.type", "kind": "variable", "doc": "
\n", "annotation": ": Literal['batch', 'channel', 'index', 'space', 'time']"}, "bioimageio.core.axis.Axis.create": {"fullname": "bioimageio.core.axis.Axis.create", "modulename": "bioimageio.core.axis", "qualname": "Axis.create", "kind": "function", "doc": "
\n", "signature": "(\tcls,\taxis: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]) -> bioimageio.core.axis.Axis:", "funcdef": "def"}, "bioimageio.core.axis.AxisInfo": {"fullname": "bioimageio.core.axis.AxisInfo", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo", "kind": "class", "doc": "
\n", "bases": "Axis"}, "bioimageio.core.axis.AxisInfo.__init__": {"fullname": "bioimageio.core.axis.AxisInfo.__init__", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.__init__", "kind": "function", "doc": "
\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'],\tmaybe_singleton: bool)"}, "bioimageio.core.axis.AxisInfo.maybe_singleton": {"fullname": "bioimageio.core.axis.AxisInfo.maybe_singleton", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.maybe_singleton", "kind": "variable", "doc": "
\n", "annotation": ": bool"}, "bioimageio.core.axis.AxisInfo.create": {"fullname": "bioimageio.core.axis.AxisInfo.create", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.create", "kind": "function", "doc": "
\n", "signature": "(\tcls,\taxis: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis],\tmaybe_singleton: Optional[bool] = None) -> bioimageio.core.axis.AxisInfo:", "funcdef": "def"}, "bioimageio.core.block": {"fullname": "bioimageio.core.block", "modulename": "bioimageio.core.block", "kind": "module", "doc": "
\n"}, "bioimageio.core.block.Block": {"fullname": "bioimageio.core.block.Block", "modulename": "bioimageio.core.block", "qualname": "Block", "kind": "class", "doc": "
A block/tile of a (larger) tensor
\n", "bases": "bioimageio.core.block_meta.BlockMeta"}, "bioimageio.core.block.Block.__init__": {"fullname": "bioimageio.core.block.Block.__init__", "modulename": "bioimageio.core.block", "qualname": "Block.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int,\tdata: bioimageio.core.tensor.Tensor)"}, "bioimageio.core.block.Block.data": {"fullname": "bioimageio.core.block.Block.data", "modulename": "bioimageio.core.block", "qualname": "Block.data", "kind": "variable", "doc": "
the block's tensor, e.g. a (padded) slice of some larger, original tensor
\n", "annotation": ": bioimageio.core.tensor.Tensor"}, "bioimageio.core.block.Block.inner_data": {"fullname": "bioimageio.core.block.Block.inner_data", "modulename": "bioimageio.core.block", "qualname": "Block.inner_data", "kind": "variable", "doc": "
\n"}, "bioimageio.core.block.Block.from_sample_member": {"fullname": "bioimageio.core.block.Block.from_sample_member", "modulename": "bioimageio.core.block", "qualname": "Block.from_sample_member", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tsample_member: bioimageio.core.tensor.Tensor,\tblock: bioimageio.core.block_meta.BlockMeta,\t*,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.get_transformed": {"fullname": "bioimageio.core.block.Block.get_transformed", "modulename": "bioimageio.core.block", "qualname": "Block.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.from_meta": {"fullname": "bioimageio.core.block.Block.from_meta", "modulename": "bioimageio.core.block", "qualname": "Block.from_meta", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tmeta: bioimageio.core.block_meta.BlockMeta,\tdata: bioimageio.core.tensor.Tensor) -> Self:", "funcdef": "def"}, "bioimageio.core.block.split_tensor_into_blocks": {"fullname": "bioimageio.core.block.split_tensor_into_blocks", "modulename": "bioimageio.core.block", "qualname": "split_tensor_into_blocks", "kind": "function", "doc": "
divide a sample tensor into tensor blocks.
\n", "signature": "(\ttensor: bioimageio.core.tensor.Tensor,\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Tuple[int, Generator[bioimageio.core.block.Block, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta": {"fullname": "bioimageio.core.block_meta", "modulename": "bioimageio.core.block_meta", "kind": "module", "doc": "
\n"}, "bioimageio.core.block_meta.LinearAxisTransform": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform", "kind": "class", "doc": "
\n"}, "bioimageio.core.block_meta.LinearAxisTransform.__init__": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.__init__", "kind": "function", "doc": "
\n", "signature": "(axis: bioimageio.spec.model.v0_5.AxisId, scale: float, offset: int)"}, "bioimageio.core.block_meta.LinearAxisTransform.axis": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.axis", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.axis", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.block_meta.LinearAxisTransform.scale": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.scale", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.scale", "kind": "variable", "doc": "
\n", "annotation": ": float"}, "bioimageio.core.block_meta.LinearAxisTransform.offset": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.offset", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.offset", "kind": "variable", "doc": "
\n", "annotation": ": int"}, "bioimageio.core.block_meta.LinearAxisTransform.compute": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.compute", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\ts: int,\tround: Callable[[float], int] = <built-in function floor>) -> int:", "funcdef": "def"}, "bioimageio.core.block_meta.BlockMeta": {"fullname": "bioimageio.core.block_meta.BlockMeta", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta", "kind": "class", "doc": "
Block meta data of a sample member (a tensor in a sample)
\n\n
Figure for illustration:\nThe first 2d block (dashed) of a sample member (bold).\nThe inner slice (thin) is expanded by a halo in both dimensions on both sides.\nThe outer slice reaches from the sample member origin (0, 0) to the right halo point.
\n\n
\u250c \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500  \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2510\n\u2577 halo(left)                         \u2577\n\u2577                                    \u2577\n\u2577  (0, 0)\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2794\n\u2577        \u2503                 \u2502         \u2577  sample member\n\u2577        \u2503      inner      \u2502         \u2577\n\u2577        \u2503   (and outer)   \u2502  outer  \u2577\n\u2577        \u2503      slice      \u2502  slice  \u2577\n\u2577        \u2503                 \u2502         \u2577\n\u2577        \u2523\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518         \u2577\n\u2577        \u2503   outer slice             \u2577\n\u2577        \u2503               halo(right) \u2577\n\u2514 \u2500 \u2500 \u2500 \u2500\u2503\u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500\u2518\n         \u2b07\n
\n\n
note:
\n\n
    \n
  • Inner and outer slices are specified in sample member coordinates.
    • \n
  • The outer_slice of a block at the sample edge may overlap by more than the\nhalo with the neighboring block (the inner slices will not overlap though).
    • \n
\n"}, "bioimageio.core.block_meta.BlockMeta.__init__": {"fullname": "bioimageio.core.block_meta.BlockMeta.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.block_meta.BlockMeta.sample_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.sample_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.sample_shape", "kind": "variable", "doc": "
the axis sizes of the whole (unblocked) sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice", "kind": "variable", "doc": "
inner region (without halo) wrt the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.halo": {"fullname": "bioimageio.core.block_meta.BlockMeta.halo", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.halo", "kind": "variable", "doc": "
halo enlarging the inner region to the block's sizes
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]"}, "bioimageio.core.block_meta.BlockMeta.block_index": {"fullname": "bioimageio.core.block_meta.BlockMeta.block_index", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.block_index", "kind": "variable", "doc": "
the i-th block of the sample
\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.blocks_in_sample": {"fullname": "bioimageio.core.block_meta.BlockMeta.blocks_in_sample", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.blocks_in_sample", "kind": "variable", "doc": "
total number of blocks in the sample
\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.shape", "kind": "variable", "doc": "
axis lengths of the block
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.padding": {"fullname": "bioimageio.core.block_meta.BlockMeta.padding", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.padding", "kind": "variable", "doc": "
padding to realize the halo at the sample edge\nwhere we cannot simply enlarge the inner slice
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.PadWidth]"}, "bioimageio.core.block_meta.BlockMeta.outer_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.outer_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.outer_slice", "kind": "variable", "doc": "
slice of the outer block (without padding) wrt the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.inner_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_shape", "kind": "variable", "doc": "
axis lengths of the inner region (without halo)
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.local_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.local_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.local_slice", "kind": "variable", "doc": "
inner slice wrt the block, not the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.dims": {"fullname": "bioimageio.core.block_meta.BlockMeta.dims", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.dims", "kind": "variable", "doc": "
\n", "annotation": ": Collection[bioimageio.spec.model.v0_5.AxisId]"}, "bioimageio.core.block_meta.BlockMeta.tagged_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.tagged_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.tagged_shape", "kind": "variable", "doc": "
alias for shape
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice_wo_overlap", "kind": "variable", "doc": "
subslice of the inner slice, such that all inner_slice_wo_overlap can be\nstiched together trivially to form the original sample.
\n\n
This can also be used to calculate statistics\nwithout overrepresenting block edge regions.
\n"}, "bioimageio.core.block_meta.BlockMeta.get_transformed": {"fullname": "bioimageio.core.block_meta.BlockMeta.get_transformed", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block_meta.split_shape_into_blocks": {"fullname": "bioimageio.core.block_meta.split_shape_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_shape_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tshape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None) -> Tuple[int, Generator[bioimageio.core.block_meta.BlockMeta, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta.split_multiple_shapes_into_blocks": {"fullname": "bioimageio.core.block_meta.split_multiple_shapes_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_multiple_shapes_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tshapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tstrides: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tbroadcast: bool = False) -> Tuple[int, Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]]]:", "funcdef": "def"}, "bioimageio.core.commands": {"fullname": "bioimageio.core.commands", "modulename": "bioimageio.core.commands", "kind": "module", "doc": "
The Bioimageio class defined here has static methods that constitute the bioimageio command line interface (using fire)
\n"}, "bioimageio.core.commands.Bioimageio": {"fullname": "bioimageio.core.commands.Bioimageio", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio", "kind": "class", "doc": "
\ud83e\udd92 CLI to work with resources shared on bioimage.io
\n\n
library versions:\n  bioimageio.core 0.6.8\n  bioimageio.spec 0.6.8
\n\n
spec format versions:\n        model RDF 0.5.3\n      dataset RDF 0.3.0\n     notebook RDF 0.3.0
\n"}, "bioimageio.core.commands.Bioimageio.package": {"fullname": "bioimageio.core.commands.Bioimageio.package", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.package", "kind": "function", "doc": "
Package a bioimageio resource as a zip file
\n\n
Args:\n    source: RDF source e.g. bioimageio.yaml or http://example.com/rdf.yaml\n    path: output path\n    weight-format: include only this single weight-format
\n", "signature": "(\tsource: str,\tpath: pathlib.Path = PosixPath('bioimageio-package.zip'),\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None):", "funcdef": "def"}, "bioimageio.core.commands.Bioimageio.test": {"fullname": "bioimageio.core.commands.Bioimageio.test", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.test", "kind": "function", "doc": "
test a bioimageio resource
\n\n
Args:\n    source: Path or URL to the bioimageio resource description file\n            (bioimageio.yaml or rdf.yaml) or to a zipped resource\n    weight_format: (model only) The weight format to use\n    devices: Device(s) to use for testing\n    decimal: Precision for numerical comparisons
\n", "signature": "(\tsource: str,\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\t*,\tdevices: Union[str, List[str], NoneType] = None,\tdecimal: int = 4):", "funcdef": "def"}, "bioimageio.core.commands.Bioimageio.validate_format": {"fullname": "bioimageio.core.commands.Bioimageio.validate_format", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.validate_format", "kind": "function", "doc": "
validate the meta data format of a bioimageio resource description
\n\n
Args:\n    source: Path or URL to the bioimageio resource description file\n            (bioimageio.yaml or rdf.yaml) or to a zipped resource
\n", "signature": "(source: str):", "funcdef": "def"}, "bioimageio.core.commands.main": {"fullname": "bioimageio.core.commands.main", "modulename": "bioimageio.core.commands", "qualname": "main", "kind": "function", "doc": "
\n", "signature": "():", "funcdef": "def"}, "bioimageio.core.common": {"fullname": "bioimageio.core.common", "modulename": "bioimageio.core.common", "kind": "module", "doc": "
\n"}, "bioimageio.core.common.DTypeStr": {"fullname": "bioimageio.core.common.DTypeStr", "modulename": "bioimageio.core.common", "qualname": "DTypeStr", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.common.CropWidth": {"fullname": "bioimageio.core.common.CropWidth", "modulename": "bioimageio.core.common", "qualname": "CropWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.CropWidth.__init__": {"fullname": "bioimageio.core.common.CropWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "CropWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.CropWidthLike": {"fullname": "bioimageio.core.common.CropWidthLike", "modulename": "bioimageio.core.common", "qualname": "CropWidthLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.CropWidth]"}, "bioimageio.core.common.CropWhere": {"fullname": "bioimageio.core.common.CropWhere", "modulename": "bioimageio.core.common", "qualname": "CropWhere", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.Halo": {"fullname": "bioimageio.core.common.Halo", "modulename": "bioimageio.core.common", "qualname": "Halo", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.Halo.__init__": {"fullname": "bioimageio.core.common.Halo.__init__", "modulename": "bioimageio.core.common", "qualname": "Halo.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.HaloLike": {"fullname": "bioimageio.core.common.HaloLike", "modulename": "bioimageio.core.common", "qualname": "HaloLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.Halo]"}, "bioimageio.core.common.OverlapWidth": {"fullname": "bioimageio.core.common.OverlapWidth", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.OverlapWidth.__init__": {"fullname": "bioimageio.core.common.OverlapWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidth": {"fullname": "bioimageio.core.common.PadWidth", "modulename": "bioimageio.core.common", "qualname": "PadWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.PadWidth.__init__": {"fullname": "bioimageio.core.common.PadWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "PadWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidthLike": {"fullname": "bioimageio.core.common.PadWidthLike", "modulename": "bioimageio.core.common", "qualname": "PadWidthLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.PadWidth]"}, "bioimageio.core.common.PadMode": {"fullname": "bioimageio.core.common.PadMode", "modulename": "bioimageio.core.common", "qualname": "PadMode", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['edge', 'reflect', 'symmetric']"}, "bioimageio.core.common.PadWhere": {"fullname": "bioimageio.core.common.PadWhere", "modulename": "bioimageio.core.common", "qualname": "PadWhere", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.SliceInfo": {"fullname": "bioimageio.core.common.SliceInfo", "modulename": "bioimageio.core.common", "qualname": "SliceInfo", "kind": "class", "doc": "
SliceInfo(start, stop)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.SliceInfo.__init__": {"fullname": "bioimageio.core.common.SliceInfo.__init__", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.__init__", "kind": "function", "doc": "
Create new instance of SliceInfo(start, stop)
\n", "signature": "(start: int, stop: int)"}, "bioimageio.core.common.SliceInfo.start": {"fullname": "bioimageio.core.common.SliceInfo.start", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.start", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": int"}, "bioimageio.core.common.SliceInfo.stop": {"fullname": "bioimageio.core.common.SliceInfo.stop", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.stop", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": int"}, "bioimageio.core.common.SampleId": {"fullname": "bioimageio.core.common.SampleId", "modulename": "bioimageio.core.common", "qualname": "SampleId", "kind": "variable", "doc": "
\n", "default_value": "typing.Hashable"}, "bioimageio.core.common.MemberId": {"fullname": "bioimageio.core.common.MemberId", "modulename": "bioimageio.core.common", "qualname": "MemberId", "kind": "variable", "doc": "
\n", "default_value": "<class 'bioimageio.spec.model.v0_5.TensorId'>"}, "bioimageio.core.common.PerMember": {"fullname": "bioimageio.core.common.PerMember", "modulename": "bioimageio.core.common", "qualname": "PerMember", "kind": "variable", "doc": "
\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.TensorId, ~T]"}, "bioimageio.core.common.BlockIndex": {"fullname": "bioimageio.core.common.BlockIndex", "modulename": "bioimageio.core.common", "qualname": "BlockIndex", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.TotalNumberOfBlocks": {"fullname": "bioimageio.core.common.TotalNumberOfBlocks", "modulename": "bioimageio.core.common", "qualname": "TotalNumberOfBlocks", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.Frozen": {"fullname": "bioimageio.core.common.Frozen", "modulename": "bioimageio.core.common", "qualname": "Frozen", "kind": "variable", "doc": "
\n", "default_value": "<class 'mappingproxy'>"}, "bioimageio.core.dataset": {"fullname": "bioimageio.core.dataset", "modulename": "bioimageio.core.dataset", "kind": "module", "doc": "
\n"}, "bioimageio.core.dataset.Dataset": {"fullname": "bioimageio.core.dataset.Dataset", "modulename": "bioimageio.core.dataset", "qualname": "Dataset", "kind": "variable", "doc": "
\n", "default_value": "typing.Iterable[bioimageio.core.sample.Sample]"}, "bioimageio.core.digest_spec": {"fullname": "bioimageio.core.digest_spec", "modulename": "bioimageio.core.digest_spec", "kind": "module", "doc": "
\n"}, "bioimageio.core.digest_spec.import_callable": {"fullname": "bioimageio.core.digest_spec.import_callable", "modulename": "bioimageio.core.digest_spec", "qualname": "import_callable", "kind": "function", "doc": "
import a callable (e.g. a torch.nn.Module) from a spec node describing it
\n", "signature": "(\tnode: Union[bioimageio.spec.model.v0_4.CallableFromDepencency, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> Callable[..., Any]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_axes_infos": {"fullname": "bioimageio.core.digest_spec.get_axes_infos", "modulename": "bioimageio.core.digest_spec", "qualname": "get_axes_infos", "kind": "function", "doc": "
get a unified, simplified axis representation from spec axes
\n", "signature": "(\tio_descr: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> List[bioimageio.core.axis.AxisInfo]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_id": {"fullname": "bioimageio.core.digest_spec.get_member_id", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_id", "kind": "function", "doc": "
get the normalized tensor ID, usable as a sample member ID
\n", "signature": "(\ttensor_description: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> bioimageio.spec.model.v0_5.TensorId:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_ids": {"fullname": "bioimageio.core.digest_spec.get_member_ids", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_ids", "kind": "function", "doc": "
get normalized tensor IDs to be used as sample member IDs
\n", "signature": "(\ttensor_descriptions: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]]) -> List[bioimageio.spec.model.v0_5.TensorId]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_inputs": {"fullname": "bioimageio.core.digest_spec.get_test_inputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_inputs", "kind": "function", "doc": "
returns a model's test input sample
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_outputs": {"fullname": "bioimageio.core.digest_spec.get_test_outputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_outputs", "kind": "function", "doc": "
returns a model's test output sample
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta", "kind": "class", "doc": "
IO_SampleBlockMeta(input, output)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.__init__", "kind": "function", "doc": "
Create new instance of IO_SampleBlockMeta(input, output)
\n", "signature": "(\tinput: ForwardRef('SampleBlockMeta'),\toutput: ForwardRef('SampleBlockMeta'))"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.input": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.input", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.input", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.output": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.output", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.output", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.get_input_halo": {"fullname": "bioimageio.core.digest_spec.get_input_halo", "modulename": "bioimageio.core.digest_spec", "qualname": "get_input_halo", "kind": "function", "doc": "
returns which halo input tensors need to be divided into blocks with such that\noutput_halo can be cropped from their outputs without intorducing gaps.
\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\toutput_halo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_block_transform": {"fullname": "bioimageio.core.digest_spec.get_block_transform", "modulename": "bioimageio.core.digest_spec", "qualname": "get_block_transform", "kind": "function", "doc": "
returns how a model's output tensor shapes relate to its input shapes
\n", "signature": "(model: bioimageio.spec.model.v0_5.ModelDescr):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_io_sample_block_metas": {"fullname": "bioimageio.core.digest_spec.get_io_sample_block_metas", "modulename": "bioimageio.core.digest_spec", "qualname": "get_io_sample_block_metas", "kind": "function", "doc": "
returns an iterable yielding meta data for corresponding input and output samples
\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\tinput_sample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tns: Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int],\tbatch_size: int = 1) -> Tuple[int, Iterable[bioimageio.core.digest_spec.IO_SampleBlockMeta]]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_tensor": {"fullname": "bioimageio.core.digest_spec.get_tensor", "modulename": "bioimageio.core.digest_spec", "qualname": "get_tensor", "kind": "function", "doc": "
helper to cast/load various tensor sources
\n", "signature": "(\tsrc: Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path],\tipt: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr]):", "funcdef": "def"}, "bioimageio.core.digest_spec.create_sample_for_model": {"fullname": "bioimageio.core.digest_spec.create_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "create_sample_for_model", "kind": "function", "doc": "
Create a sample from a single set of input(s) for a specific bioimage.io model
\n\n
Args:\n    model: a bioimage.io model description\n    stat: dictionary with sample and dataset statistics (may be updated in-place!)\n    inputs: the input(s) constituting a single sample.
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\t*,\tstat: Optional[Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None,\tsample_id: Hashable = None,\tinputs: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]] = None,\t**kwargs: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.load_sample_for_model": {"fullname": "bioimageio.core.digest_spec.load_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "load_sample_for_model", "kind": "function", "doc": "
load a single sample from paths that can be processed by model
\n", "signature": "(\t*,\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tpaths: Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path],\taxes: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]]] = None,\tstat: Optional[Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None,\tsample_id: Optional[Hashable] = None):", "funcdef": "def"}, "bioimageio.core.io": {"fullname": "bioimageio.core.io", "modulename": "bioimageio.core.io", "kind": "module", "doc": "
\n"}, "bioimageio.core.io.load_image": {"fullname": "bioimageio.core.io.load_image", "modulename": "bioimageio.core.io", "qualname": "load_image", "kind": "function", "doc": "
load a single image as numpy array
\n", "signature": "(\tpath: pathlib.Path,\tis_volume: bool) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.core.io.load_tensor": {"fullname": "bioimageio.core.io.load_tensor", "modulename": "bioimageio.core.io", "qualname": "load_tensor", "kind": "function", "doc": "
\n", "signature": "(\tpath: pathlib.Path,\taxes: Optional[Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]] = None) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.io.save_tensor": {"fullname": "bioimageio.core.io.save_tensor", "modulename": "bioimageio.core.io", "qualname": "save_tensor", "kind": "function", "doc": "
\n", "signature": "(path: pathlib.Path, tensor: bioimageio.core.tensor.Tensor) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_sample": {"fullname": "bioimageio.core.io.save_sample", "modulename": "bioimageio.core.io", "qualname": "save_sample", "kind": "function", "doc": "
save a sample to path
\n\n
path must contain {member_id} and may contain {sample_id},\nwhich are resolved with the sample object.
\n", "signature": "(\tpath: Union[pathlib.Path, str],\tsample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.model_adapters": {"fullname": "bioimageio.core.model_adapters", "modulename": "bioimageio.core.model_adapters", "kind": "module", "doc": "
\n"}, "bioimageio.core.prediction": {"fullname": "bioimageio.core.prediction", "modulename": "bioimageio.core.prediction", "kind": "module", "doc": "
convenience functions for prediction coming soon.\nFor now, please use create_prediction_pipeline to get a PredictionPipeline\nand then PredictionPipeline.predict_sample(sample)\ne..g load samples with core.io.load_sample_for_model()
\n"}, "bioimageio.core.prediction.predict": {"fullname": "bioimageio.core.prediction.predict", "modulename": "bioimageio.core.prediction", "qualname": "predict", "kind": "function", "doc": "
Run prediction for a single set of input(s) with a bioimage.io model
\n\n
Args:\n    model: model to predict with.\n        May be given as RDF source, model description or prediction pipeline.\n    inputs: the input sample or the named input(s) for this model as a dictionary\n    sample_id: the sample id.\n    blocksize_parameter: (optional) tile the input into blocks parametrized by\n        blocksize according to any parametrized axis sizes defined in the model RDF\n    skip_preprocessing: flag to skip the model's preprocessing\n    skip_postprocessing: flag to skip the model's postprocessing\n    save_output_path: A path with {member_id} {sample_id} in it\n        to save the output to.
\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Union[bioimageio.core.sample.Sample, Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: Hashable = 'sample',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.prediction.predict_many": {"fullname": "bioimageio.core.prediction.predict_many", "modulename": "bioimageio.core.prediction", "qualname": "predict_many", "kind": "function", "doc": "
Run prediction for a multiple sets of inputs with a bioimage.io model
\n\n
Args:\n    model: model to predict with.\n        May be given as RDF source, model description or prediction pipeline.\n    inputs: An iterable of the named input(s) for this model as a dictionary.\n    sample_id: the sample id.\n        note: {i} will be formatted as the i-th sample.\n        If {i} (or {i:) is not present and inputs is an iterable {i:03} is appended.\n    blocksize_parameter: (optional) tile the input into blocks parametrized by\n        blocksize according to any parametrized axis sizes defined in the model RDF\n    skip_preprocessing: flag to skip the model's preprocessing\n    skip_postprocessing: flag to skip the model's postprocessing\n    save_output_path: A path with {member_id} {sample_id} in it\n        to save the output to.
\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: str = 'sample{i:03}',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> Iterator[bioimageio.core.sample.Sample]:", "funcdef": "def"}, "bioimageio.core.proc_ops": {"fullname": "bioimageio.core.proc_ops", "modulename": "bioimageio.core.proc_ops", "kind": "module", "doc": "
\n"}, "bioimageio.core.proc_ops.convert_axis_ids": {"fullname": "bioimageio.core.proc_ops.convert_axis_ids", "modulename": "bioimageio.core.proc_ops", "qualname": "convert_axis_ids", "kind": "function", "doc": "
\n", "signature": "(\taxes: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]],\tmode: Literal['per_sample', 'per_dataset']) -> Tuple[bioimageio.spec.model.v0_5.AxisId, ...]:", "funcdef": "def"}, "bioimageio.core.proc_ops.AddKnownDatasetStats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats", "kind": "class", "doc": "
\n", "bases": "bioimageio.core._op_base.BlockedOperator"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.__init__", "kind": "function", "doc": "
\n", "signature": "(\tdataset_stats: Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]])"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.dataset_stats", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.UpdateStats": {"fullname": "bioimageio.core.proc_ops.UpdateStats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats", "kind": "class", "doc": "
Calculates sample and/or dataset measures
\n", "bases": "bioimageio.core._op_base.Operator"}, "bioimageio.core.proc_ops.UpdateStats.__init__": {"fullname": "bioimageio.core.proc_ops.UpdateStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.__init__", "kind": "function", "doc": "
\n", "signature": "(\tstats_calculator: bioimageio.core.stat_calculators.StatsCalculator,\tkeep_updating_initial_dataset_stats: bool = False)"}, "bioimageio.core.proc_ops.UpdateStats.stats_calculator": {"fullname": "bioimageio.core.proc_ops.UpdateStats.stats_calculator", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.stats_calculator", "kind": "variable", "doc": "
StatsCalculator to be used by this operator.
\n", "annotation": ": bioimageio.core.stat_calculators.StatsCalculator"}, "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats": {"fullname": "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.keep_updating_initial_dataset_stats", "kind": "variable", "doc": "
indicates if operator calls should keep updating initial dataset statistics or not;\nif the stats_calculator was not provided with any initial dataset statistics,\nthese are always updated with every new sample.
\n", "annotation": ": bool", "default_value": "False"}, "bioimageio.core.proc_ops.UpdateStats.required_measures": {"fullname": "bioimageio.core.proc_ops.UpdateStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.Binarize": {"fullname": "bioimageio.core.proc_ops.Binarize", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize", "kind": "class", "doc": "
'output = tensor > threshold'.
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Binarize.__init__": {"fullname": "bioimageio.core.proc_ops.Binarize.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tthreshold: Union[float, Sequence[float]],\taxis: Optional[bioimageio.spec.model.v0_5.AxisId] = None)"}, "bioimageio.core.proc_ops.Binarize.threshold": {"fullname": "bioimageio.core.proc_ops.Binarize.threshold", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.threshold", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, Sequence[float]]"}, "bioimageio.core.proc_ops.Binarize.axis": {"fullname": "bioimageio.core.proc_ops.Binarize.axis", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.axis", "kind": "variable", "doc": "
\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.AxisId]", "default_value": "None"}, "bioimageio.core.proc_ops.Binarize.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Binarize.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Binarize.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Binarize.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_5.BinarizeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip": {"fullname": "bioimageio.core.proc_ops.Clip", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Clip.__init__": {"fullname": "bioimageio.core.proc_ops.Clip.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmin: Optional[float] = None,\tmax: Optional[float] = None)"}, "bioimageio.core.proc_ops.Clip.min": {"fullname": "bioimageio.core.proc_ops.Clip.min", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.min", "kind": "variable", "doc": "
minimum value for clipping
\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.max": {"fullname": "bioimageio.core.proc_ops.Clip.max", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.max", "kind": "variable", "doc": "
maximum value for clipping
\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Clip.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Clip.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_5.ClipDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.EnsureDtype.__init__": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'])"}, "bioimageio.core.proc_ops.EnsureDtype.dtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.dtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.dtype", "kind": "variable", "doc": "
\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.EnsureDtypeDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_output_shape": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear": {"fullname": "bioimageio.core.proc_ops.ScaleLinear", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleLinear.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tgain: Union[float, xarray.core.dataarray.DataArray] = 1.0,\toffset: Union[float, xarray.core.dataarray.DataArray] = 0.0)"}, "bioimageio.core.proc_ops.ScaleLinear.gain": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.gain", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.gain", "kind": "variable", "doc": "
multiplicative factor
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "1.0"}, "bioimageio.core.proc_ops.ScaleLinear.offset": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.offset", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.offset", "kind": "variable", "doc": "
additive term
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "0.0"}, "bioimageio.core.proc_ops.ScaleLinear.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleMeanVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]] = None,\treference_tensor: Optional[bioimageio.spec.model.v0_5.TensorId] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleMeanVariance.axes": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.axes", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.axes", "kind": "variable", "doc": "
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\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleMeanVariance.mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.mean", "kind": "variable", "doc": "
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\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_std", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.required_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange": {"fullname": "bioimageio.core.proc_ops.ScaleRange", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleRange.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleRange.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tlower_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\tupper_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleRange.lower_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower_percentile", "kind": "variable", "doc": "
\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.upper_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper_percentile", "kind": "variable", "doc": "
\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.lower": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.upper": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.eps": {"fullname": "bioimageio.core.proc_ops.ScaleRange.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleRange.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleRange.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.required_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.proc_ops.ScaleRange.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.get_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid": {"fullname": "bioimageio.core.proc_ops.Sigmoid", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid", "kind": "class", "doc": "
1 / (1 + e^(-input)).
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Sigmoid.__init__": {"fullname": "bioimageio.core.proc_ops.Sigmoid.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.proc_ops.Sigmoid.required_measures": {"fullname": "bioimageio.core.proc_ops.Sigmoid.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Collection[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.Sigmoid.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_5.SigmoidDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.get_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_descr", "kind": "function", "doc": "
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normalize to zero mean, unit variance.
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\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean],\tstd: Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.std", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance", "kind": "class", "doc": "
normalize to zero mean, unit variance with precomputed values.
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[float, xarray.core.dataarray.DataArray],\tstd: Union[float, xarray.core.dataarray.DataArray],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.std", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ProcDescr": {"fullname": "bioimageio.core.proc_ops.ProcDescr", "modulename": "bioimageio.core.proc_ops", "qualname": "ProcDescr", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Processing": {"fullname": "bioimageio.core.proc_ops.Processing", "modulename": "bioimageio.core.proc_ops", "qualname": "Processing", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]"}, "bioimageio.core.proc_ops.get_proc_class": {"fullname": "bioimageio.core.proc_ops.get_proc_class", "modulename": "bioimageio.core.proc_ops", "qualname": "get_proc_class", "kind": "function", "doc": "
\n", "signature": "(\tproc_spec: Union[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]):", "funcdef": "def"}, "bioimageio.core.proc_setup": {"fullname": "bioimageio.core.proc_setup", "modulename": "bioimageio.core.proc_setup", "kind": "module", "doc": "
\n"}, "bioimageio.core.proc_setup.TensorDescr": {"fullname": "bioimageio.core.proc_setup.TensorDescr", "modulename": "bioimageio.core.proc_setup", "qualname": "TensorDescr", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.core.proc_setup.PreAndPostprocessing": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing", "kind": "class", "doc": "
PreAndPostprocessing(pre, post)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.PreAndPostprocessing.__init__": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.__init__", "kind": "function", "doc": "
Create new instance of PreAndPostprocessing(pre, post)
\n", "signature": "(\tpre: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]],\tpost: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]])"}, "bioimageio.core.proc_setup.PreAndPostprocessing.pre": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.pre", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.PreAndPostprocessing.post": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.post", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.post", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.setup_pre_and_postprocessing": {"fullname": "bioimageio.core.proc_setup.setup_pre_and_postprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "setup_pre_and_postprocessing", "kind": "function", "doc": "
Get pre- and postprocessing operators for a model description.\nuserd in `bioimageio.core.create_prediction_pipeline
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tdataset_for_initial_statistics: Iterable[bioimageio.core.sample.Sample],\tkeep_updating_initial_dataset_stats: bool = False,\tfixed_dataset_stats: Optional[Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None) -> bioimageio.core.proc_setup.PreAndPostprocessing:", "funcdef": "def"}, "bioimageio.core.sample": {"fullname": "bioimageio.core.sample", "modulename": "bioimageio.core.sample", "kind": "module", "doc": "
\n"}, "bioimageio.core.sample.Sample": {"fullname": "bioimageio.core.sample.Sample", "modulename": "bioimageio.core.sample", "qualname": "Sample", "kind": "class", "doc": "
A dataset sample
\n"}, "bioimageio.core.sample.Sample.__init__": {"fullname": "bioimageio.core.sample.Sample.__init__", "modulename": "bioimageio.core.sample", "qualname": "Sample.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmembers: Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]],\tid: Hashable)"}, "bioimageio.core.sample.Sample.members": {"fullname": "bioimageio.core.sample.Sample.members", "modulename": "bioimageio.core.sample", "qualname": "Sample.members", "kind": "variable", "doc": "
the sample's tensors
\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.Sample.stat": {"fullname": "bioimageio.core.sample.Sample.stat", "modulename": "bioimageio.core.sample", "qualname": "Sample.stat", "kind": "variable", "doc": "
sample and dataset statistics
\n", "annotation": ": Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.sample.Sample.id": {"fullname": "bioimageio.core.sample.Sample.id", "modulename": "bioimageio.core.sample", "qualname": "Sample.id", "kind": "variable", "doc": "
identifier within the sample's dataset
\n", "annotation": ": Hashable"}, "bioimageio.core.sample.Sample.shape": {"fullname": "bioimageio.core.sample.Sample.shape", "modulename": "bioimageio.core.sample", "qualname": "Sample.shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.Sample.split_into_blocks": {"fullname": "bioimageio.core.sample.Sample.split_into_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.split_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tself,\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tpad_mode: Literal['edge', 'reflect', 'symmetric'],\tbroadcast: bool = False) -> Tuple[int, Iterable[bioimageio.core.sample.SampleBlockWithOrigin]]:", "funcdef": "def"}, "bioimageio.core.sample.Sample.as_single_block": {"fullname": "bioimageio.core.sample.Sample.as_single_block", "modulename": "bioimageio.core.sample", "qualname": "Sample.as_single_block", "kind": "function", "doc": "
\n", "signature": "(\tself,\thalo: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]] = None):", "funcdef": "def"}, "bioimageio.core.sample.Sample.from_blocks": {"fullname": "bioimageio.core.sample.Sample.from_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.from_blocks", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tsample_blocks: Iterable[bioimageio.core.sample.SampleBlock],\t*,\tfill_value: float = nan) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockBase": {"fullname": "bioimageio.core.sample.SampleBlockBase", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase", "kind": "class", "doc": "
base class for SampleBlockMeta and SampleBlock
\n", "bases": "typing.Generic[~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.__init__": {"fullname": "bioimageio.core.sample.SampleBlockBase.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockBase.sample_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_shape", "kind": "variable", "doc": "
the sample shape this block represents a part of
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.sample_id": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_id", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_id", "kind": "variable", "doc": "
identifier for the sample within its dataset
\n", "annotation": ": Hashable"}, "bioimageio.core.sample.SampleBlockBase.blocks": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks", "kind": "variable", "doc": "
Individual tensor blocks comprising this sample block
\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.block_index": {"fullname": "bioimageio.core.sample.SampleBlockBase.block_index", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.block_index", "kind": "variable", "doc": "
the n-th block of the sample
\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.blocks_in_sample": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks_in_sample", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks_in_sample", "kind": "variable", "doc": "
total number of blocks in the sample
\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.inner_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.inner_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.inner_shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.LinearSampleAxisTransform": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform", "kind": "class", "doc": "
\n", "bases": "bioimageio.core.block_meta.LinearAxisTransform"}, "bioimageio.core.sample.LinearSampleAxisTransform.__init__": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.__init__", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.__init__", "kind": "function", "doc": "
\n", "signature": "(\taxis: bioimageio.spec.model.v0_5.AxisId,\tscale: float,\toffset: int,\tmember: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.sample.LinearSampleAxisTransform.member": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.member", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.member", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.sample.SampleBlockMeta": {"fullname": "bioimageio.core.sample.SampleBlockMeta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta", "kind": "class", "doc": "
Meta data of a dataset sample block
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block_meta.BlockMeta]"}, "bioimageio.core.sample.SampleBlockMeta.__init__": {"fullname": "bioimageio.core.sample.SampleBlockMeta.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockMeta.get_transformed": {"fullname": "bioimageio.core.sample.SampleBlockMeta.get_transformed", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockMeta.with_data": {"fullname": "bioimageio.core.sample.SampleBlockMeta.with_data", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.with_data", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdata: Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\t*,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]) -> bioimageio.core.sample.SampleBlock:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlock": {"fullname": "bioimageio.core.sample.SampleBlock", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock", "kind": "class", "doc": "
A block of a dataset sample
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlock.__init__": {"fullname": "bioimageio.core.sample.SampleBlock.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]])"}, "bioimageio.core.sample.SampleBlock.stat": {"fullname": "bioimageio.core.sample.SampleBlock.stat", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.stat", "kind": "variable", "doc": "
computed statistics
\n", "annotation": ": Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.sample.SampleBlock.members": {"fullname": "bioimageio.core.sample.SampleBlock.members", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.members", "kind": "variable", "doc": "
the sample block's tensors
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.SampleBlock.get_transformed_meta": {"fullname": "bioimageio.core.sample.SampleBlock.get_transformed_meta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.get_transformed_meta", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> bioimageio.core.sample.SampleBlockMeta:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockWithOrigin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin", "kind": "class", "doc": "
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlockWithOrigin.__init__": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]],\torigin: bioimageio.core.sample.Sample)"}, "bioimageio.core.sample.SampleBlockWithOrigin.origin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.origin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.origin", "kind": "variable", "doc": "
the sample this sample black was taken from
\n", "annotation": ": bioimageio.core.sample.Sample"}, "bioimageio.core.sample.sample_block_meta_generator": {"fullname": "bioimageio.core.sample.sample_block_meta_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_meta_generator", "kind": "function", "doc": "
\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable):", "funcdef": "def"}, "bioimageio.core.sample.sample_block_generator": {"fullname": "bioimageio.core.sample.sample_block_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_generator", "kind": "function", "doc": "
\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\torigin: bioimageio.core.sample.Sample,\tpad_mode: Literal['edge', 'reflect', 'symmetric']):", "funcdef": "def"}, "bioimageio.core.stat_calculators": {"fullname": "bioimageio.core.stat_calculators", "modulename": "bioimageio.core.stat_calculators", "kind": "module", "doc": "
\n"}, "bioimageio.core.stat_calculators.MeanCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator", "kind": "class", "doc": "
to calculate sample and dataset mean for in-memory samples
\n"}, "bioimageio.core.stat_calculators.MeanCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute_and_update", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator", "kind": "class", "doc": "
to calculate sample and dataset mean, variance or standard deviation
\n"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator", "kind": "class", "doc": "
to calculate sample percentiles
\n"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator", "kind": "class", "doc": "
to calculate dataset percentiles heuristically by averaging across samples\nnote: the returned dataset percentiles are an estiamte and not mathematically correct
\n"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator", "kind": "class", "doc": "
to calculate dataset percentiles with the experimental crick libray
\n"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, part: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator", "kind": "class", "doc": "
wrapper for measures to match interface of other sample measure calculators
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tmeasure: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile])"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.tensor_name", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.measure", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.SampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SampleMeasureCalculator", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]"}, "bioimageio.core.stat_calculators.DatasetMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetMeasureCalculator", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]"}, "bioimageio.core.stat_calculators.StatsCalculator": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator", "kind": "class", "doc": "
Estimates dataset statistics and computes sample statistics efficiently
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmeasures: Collection[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tinitial_dataset_measures: Optional[Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None)"}, "bioimageio.core.stat_calculators.StatsCalculator.sample_count": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.sample_count", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.sample_count", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.has_dataset_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.update": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.finalize", "kind": "function", "doc": "
returns aggregated dataset statistics
\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update_and_get_all", "kind": "function", "doc": "
Returns sample as well as updated dataset statistics
\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.skip_update_and_get_all", "kind": "function", "doc": "
Returns sample as well as previously computed dataset statistics
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.get_measure_calculators": {"fullname": "bioimageio.core.stat_calculators.get_measure_calculators", "modulename": "bioimageio.core.stat_calculators", "qualname": "get_measure_calculators", "kind": "function", "doc": "
determines which calculators are needed to compute the required measures efficiently
\n", "signature": "(\trequired_measures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]) -> Tuple[List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]], List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.compute_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_dataset_measures", "kind": "function", "doc": "
compute all dataset measures for the given dataset
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_sample_measures": {"fullname": "bioimageio.core.stat_calculators.compute_sample_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_sample_measures", "kind": "function", "doc": "
compute all sample measures for the given sample
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile]],\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_measures": {"fullname": "bioimageio.core.stat_calculators.compute_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_measures", "kind": "function", "doc": "
compute all measures for the given dataset\nsample measures are computed for the last sample in dataset
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest": {"fullname": "bioimageio.core.stat_calculators.TDigest", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest", "kind": "class", "doc": "
\n"}, "bioimageio.core.stat_calculators.TDigest.update": {"fullname": "bioimageio.core.stat_calculators.TDigest.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.update", "kind": "function", "doc": "
\n", "signature": "(self, obj: Any):", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest.quantile": {"fullname": "bioimageio.core.stat_calculators.TDigest.quantile", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.quantile", "kind": "function", "doc": "
\n", "signature": "(self, q: Any) -> Any:", "funcdef": "def"}, "bioimageio.core.stat_calculators.DatasetPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetPercentilesCalculator", "kind": "variable", "doc": "
\n", "annotation": ": Type[Union[bioimageio.core.stat_calculators.MeanPercentilesCalculator, bioimageio.core.stat_calculators.CrickPercentilesCalculator]]", "default_value": "<class 'bioimageio.core.stat_calculators.MeanPercentilesCalculator'>"}, "bioimageio.core.stat_measures": {"fullname": "bioimageio.core.stat_measures", "modulename": "bioimageio.core.stat_measures", "kind": "module", "doc": "
\n"}, "bioimageio.core.stat_measures.MeasureValue": {"fullname": "bioimageio.core.stat_measures.MeasureValue", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureValue", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[float, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.SampleLike": {"fullname": "bioimageio.core.stat_measures.SampleLike", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike", "kind": "class", "doc": "
Base class for protocol classes.
\n\n
Protocol classes are defined as::
\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n
Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).
\n\n
For example::
\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n
See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::
\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.stat_measures.SampleLike.__init__": {"fullname": "bioimageio.core.stat_measures.SampleLike.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.__init__", "kind": "function", "doc": "
\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.stat_measures.SampleLike.members": {"fullname": "bioimageio.core.stat_measures.SampleLike.members", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.members", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.MeasureBase": {"fullname": "bioimageio.core.stat_measures.MeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase", "kind": "class", "doc": "
\n"}, "bioimageio.core.stat_measures.MeasureBase.__init__": {"fullname": "bioimageio.core.stat_measures.MeasureBase.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.__init__", "kind": "function", "doc": "
\n", "signature": "(member_id: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.stat_measures.MeasureBase.member_id": {"fullname": "bioimageio.core.stat_measures.MeasureBase.member_id", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.member_id", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.stat_measures.SampleMeasureBase": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase", "kind": "class", "doc": "
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.SampleMeasureBase.compute": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMeasureBase": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase", "kind": "class", "doc": "
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.DatasetMeasureBase.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.__init__", "kind": "function", "doc": "
\n", "signature": "(member_id: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.stat_measures.SampleMean": {"fullname": "bioimageio.core.stat_measures.SampleMean", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean", "kind": "class", "doc": "
The mean value of a single tensor
\n", "bases": "_Mean, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleMean.__init__": {"fullname": "bioimageio.core.stat_measures.SampleMean.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleMean.compute": {"fullname": "bioimageio.core.stat_measures.SampleMean.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMean": {"fullname": "bioimageio.core.stat_measures.DatasetMean", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean", "kind": "class", "doc": "
The mean value across multiple samples
\n", "bases": "_Mean, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetMean.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetMean.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleStd": {"fullname": "bioimageio.core.stat_measures.SampleStd", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd", "kind": "class", "doc": "
The standard deviation of a single tensor
\n", "bases": "_Std, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleStd.__init__": {"fullname": "bioimageio.core.stat_measures.SampleStd.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleStd.compute": {"fullname": "bioimageio.core.stat_measures.SampleStd.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetStd": {"fullname": "bioimageio.core.stat_measures.DatasetStd", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd", "kind": "class", "doc": "
The standard deviation across multiple samples
\n", "bases": "_Std, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetStd.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetStd.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleVar": {"fullname": "bioimageio.core.stat_measures.SampleVar", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar", "kind": "class", "doc": "
The variance of a single tensor
\n", "bases": "_Var, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleVar.__init__": {"fullname": "bioimageio.core.stat_measures.SampleVar.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleVar.compute": {"fullname": "bioimageio.core.stat_measures.SampleVar.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetVar": {"fullname": "bioimageio.core.stat_measures.DatasetVar", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar", "kind": "class", "doc": "
The variance across multiple samples
\n", "bases": "_Var, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetVar.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetVar.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleQuantile": {"fullname": "bioimageio.core.stat_measures.SampleQuantile", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile", "kind": "class", "doc": "
The nth percentile of a single tensor
\n", "bases": "_Quantile, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleQuantile.__init__": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tq: float,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleQuantile.compute": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetPercentile": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile", "kind": "class", "doc": "
The nth percentile across multiple samples
\n", "bases": "_Quantile, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetPercentile.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tq: float,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleMeasure": {"fullname": "bioimageio.core.stat_measures.SampleMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile]"}, "bioimageio.core.stat_measures.DatasetMeasure": {"fullname": "bioimageio.core.stat_measures.DatasetMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.stat_measures.Measure": {"fullname": "bioimageio.core.stat_measures.Measure", "modulename": "bioimageio.core.stat_measures", "qualname": "Measure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.stat_measures.Stat": {"fullname": "bioimageio.core.stat_measures.Stat", "modulename": "bioimageio.core.stat_measures", "qualname": "Stat", "kind": "variable", "doc": "
\n", "default_value": "typing.Dict[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], typing.Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.stat_measures.MeanMeasure": {"fullname": "bioimageio.core.stat_measures.MeanMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "MeanMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.stat_measures.StdMeasure": {"fullname": "bioimageio.core.stat_measures.StdMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "StdMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.stat_measures.VarMeasure": {"fullname": "bioimageio.core.stat_measures.VarMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "VarMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.DatasetVar]"}, "bioimageio.core.stat_measures.PercentileMeasure": {"fullname": "bioimageio.core.stat_measures.PercentileMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "PercentileMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.tensor": {"fullname": "bioimageio.core.tensor", "modulename": "bioimageio.core.tensor", "kind": "module", "doc": "
\n"}, "bioimageio.core.tensor.Tensor": {"fullname": "bioimageio.core.tensor.Tensor", "modulename": "bioimageio.core.tensor", "qualname": "Tensor", "kind": "class", "doc": "
A wrapper around an xr.DataArray for better integration with bioimageio.spec\nand improved type annotations.
\n", "bases": "bioimageio.core._magic_tensor_ops.MagicTensorOpsMixin"}, "bioimageio.core.tensor.Tensor.__init__": {"fullname": "bioimageio.core.tensor.Tensor.__init__", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.__init__", "kind": "function", "doc": "
\n", "signature": "(\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\tdims: Sequence[bioimageio.spec.model.v0_5.AxisId])"}, "bioimageio.core.tensor.Tensor.from_xarray": {"fullname": "bioimageio.core.tensor.Tensor.from_xarray", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_xarray", "kind": "function", "doc": "
create a Tensor from an xarray data array
\n\n
note for internal use: this factory method is round-trip save\n    for any Tensor's  data property (an xarray.DataArray).
\n", "signature": "(cls, data_array: xarray.core.dataarray.DataArray) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.from_numpy": {"fullname": "bioimageio.core.tensor.Tensor.from_numpy", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_numpy", "kind": "function", "doc": "
create a Tensor from a numpy array
\n\n
Args:\n    array: the nd numpy array\n    axes: A description of the array's axes,\n        if None axes are guessed (which might fail and raise a ValueError.)
\n\n
Raises:\n    ValueError: if axes is None and axes guessing fails.
\n", "signature": "(\tcls,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\t*,\tdims: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis, Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]], NoneType]) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.data": {"fullname": "bioimageio.core.tensor.Tensor.data", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.data", "kind": "variable", "doc": "
\n"}, "bioimageio.core.tensor.Tensor.dims": {"fullname": "bioimageio.core.tensor.Tensor.dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dims", "kind": "variable", "doc": "
Tuple of dimension names associated with this tensor.
\n"}, "bioimageio.core.tensor.Tensor.tagged_shape": {"fullname": "bioimageio.core.tensor.Tensor.tagged_shape", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.tagged_shape", "kind": "variable", "doc": "
(alias for sizes) Ordered, immutable mapping from axis ids to lengths.
\n"}, "bioimageio.core.tensor.Tensor.shape_tuple": {"fullname": "bioimageio.core.tensor.Tensor.shape_tuple", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.shape_tuple", "kind": "variable", "doc": "
Tuple of tensor axes lengths
\n"}, "bioimageio.core.tensor.Tensor.size": {"fullname": "bioimageio.core.tensor.Tensor.size", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.size", "kind": "variable", "doc": "
Number of elements in the tensor.
\n\n
Equal to math.prod(tensor.shape), i.e., the product of the tensors\u2019 dimensions.
\n"}, "bioimageio.core.tensor.Tensor.sum": {"fullname": "bioimageio.core.tensor.Tensor.sum", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sum", "kind": "function", "doc": "
Reduce this Tensor's data by applying sum along some dimension(s).
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.ndim": {"fullname": "bioimageio.core.tensor.Tensor.ndim", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.ndim", "kind": "variable", "doc": "
Number of tensor dimensions.
\n"}, "bioimageio.core.tensor.Tensor.dtype": {"fullname": "bioimageio.core.tensor.Tensor.dtype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dtype", "kind": "variable", "doc": "
\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.tensor.Tensor.sizes": {"fullname": "bioimageio.core.tensor.Tensor.sizes", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sizes", "kind": "variable", "doc": "
Ordered, immutable mapping from axis ids to axis lengths.
\n"}, "bioimageio.core.tensor.Tensor.astype": {"fullname": "bioimageio.core.tensor.Tensor.astype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.astype", "kind": "function", "doc": "
Return tensor cast to dtype
\n\n
note: if dtype is already satisfied copy if copy
\n", "signature": "(\tself,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'],\t*,\tcopy: bool = False):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.clip": {"fullname": "bioimageio.core.tensor.Tensor.clip", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.clip", "kind": "function", "doc": "
Return a tensor whose values are limited to [min, max].\nAt least one of max or min must be given.
\n", "signature": "(self, min: Optional[float] = None, max: Optional[float] = None):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.crop_to": {"fullname": "bioimageio.core.tensor.Tensor.crop_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.crop_to", "kind": "function", "doc": "
crop to match sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.expand_dims": {"fullname": "bioimageio.core.tensor.Tensor.expand_dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.expand_dims", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdims: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Mapping[bioimageio.spec.model.v0_5.AxisId, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.mean": {"fullname": "bioimageio.core.tensor.Tensor.mean", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.mean", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.std": {"fullname": "bioimageio.core.tensor.Tensor.std", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.std", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.var": {"fullname": "bioimageio.core.tensor.Tensor.var", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.var", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad": {"fullname": "bioimageio.core.tensor.Tensor.pad", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad", "kind": "function", "doc": "
\n", "signature": "(\tself,\tpad_width: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.PadWidth]],\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad_to": {"fullname": "bioimageio.core.tensor.Tensor.pad_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad_to", "kind": "function", "doc": "
pad tensor to match sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.quantile": {"fullname": "bioimageio.core.tensor.Tensor.quantile", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.quantile", "kind": "function", "doc": "
\n", "signature": "(\tself,\tq: Union[float, Sequence[float]],\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.resize_to": {"fullname": "bioimageio.core.tensor.Tensor.resize_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.resize_to", "kind": "function", "doc": "
return cropped/padded tensor with sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tpad_mode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric'):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.transpose": {"fullname": "bioimageio.core.tensor.Tensor.transpose", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.transpose", "kind": "function", "doc": "
return a transposed tensor
\n\n
Args:\n    axes: the desired tensor axes
\n", "signature": "(self, axes: Sequence[bioimageio.spec.model.v0_5.AxisId]) -> Self:", "funcdef": "def"}, "bioimageio.core.utils": {"fullname": "bioimageio.core.utils", "modulename": "bioimageio.core.utils", "kind": "module", "doc": "
\n"}, "bioimageio.core.utils.testing": {"fullname": "bioimageio.core.utils.testing", "modulename": "bioimageio.core.utils.testing", "kind": "module", "doc": "
\n"}, "bioimageio.core.utils.testing.test_func": {"fullname": "bioimageio.core.utils.testing.test_func", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func", "kind": "class", "doc": "
Base class for protocol classes.
\n\n
Protocol classes are defined as::
\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n
Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).
\n\n
For example::
\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n
See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::
\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.utils.testing.test_func.__init__": {"fullname": "bioimageio.core.utils.testing.test_func.__init__", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func.__init__", "kind": "function", "doc": "
\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.utils.testing.skip_on": {"fullname": "bioimageio.core.utils.testing.skip_on", "modulename": "bioimageio.core.utils.testing", "qualname": "skip_on", "kind": "function", "doc": "
adapted from https://stackoverflow.com/a/63522579
\n", "signature": "(exception: Type[Exception], reason: str):", "funcdef": "def"}, "bioimageio.core.weight_converter": {"fullname": "bioimageio.core.weight_converter", "modulename": "bioimageio.core.weight_converter", "kind": "module", "doc": "
coming soon
\n"}, "bioimageio.core.weight_converter.keras": {"fullname": "bioimageio.core.weight_converter.keras", "modulename": "bioimageio.core.weight_converter.keras", "kind": "module", "doc": "
\n"}, "bioimageio.core.weight_converter.torch": {"fullname": "bioimageio.core.weight_converter.torch", "modulename": "bioimageio.core.weight_converter.torch", "kind": "module", "doc": "
\n"}}, "docInfo": {"bioimageio.core": {"qualname": 0, "fullname": 2, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 997}, "bioimageio.core.test_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1236, "bases": 0, "doc": 16}, "bioimageio.core.load_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1159, "bases": 0, "doc": 112}, "bioimageio.core.load_model": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1159, "bases": 0, "doc": 112}, "bioimageio.core.axis": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "bioimageio.core.axis.AxisId": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 72}, "bioimageio.core.axis.AxisId.root_model": {"qualname": 3, "fullname": 6, "annotation": 5, "default_value": 17, "signature": 0, "bases": 0, "doc": 10}, 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+    /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"bioimageio.core": {"fullname": "bioimageio.core", "modulename": "bioimageio.core", "kind": "module", "doc": "
\"License\"\n\"PyPI\"\n\"conda-version\"\n\"downloads\"\n\"conda-forge\n\"code
\n\n
core-bioimage-io-python
\n\n
Python specific core utilities for bioimage.io resources (in particular models).
\n\n
Installation
\n\n
Via Mamba/Conda
\n\n
The bioimageio.core package can be installed from conda-forge via
\n\n
\n
mamba install -c conda-forge bioimageio.core\n
\n
\n\n
If you do not install any additional deep learning libraries, you will only be able to use general convenience\nfunctionality, but not any functionality for model prediction.\nTo install additional deep learning libraries use:
\n\n
    \n
  • Pytorch/Torchscript:
    \n\n
    CPU installation (if you don't have an nvidia graphics card):
    \n\n
    \n
    mamba install -c pytorch -c conda-forge bioimageio.core pytorch torchvision cpuonly\n
    \n
    \n\n
    GPU installation (for cuda 11.6, please choose the appropriate cuda version for your system):
    \n\n
    \n
    mamba install -c pytorch -c nvidia -c conda-forge bioimageio.core pytorch torchvision pytorch-cuda=11.8\n
    \n
    \n\n
    Note that the pytorch installation instructions may change in the future. For the latest instructions please refer to pytorch.org.
    • \n
  • Tensorflow
    \n\n
    Currently only CPU version supported
    \n\n
    \n
    mamba install -c conda-forge bioimageio.core tensorflow\n
    \n
    • \n\n
  • ONNXRuntime
    \n\n
    Currently only cpu version supported
    \n\n
    \n
    mamba install -c conda-forge bioimageio.core onnxruntime\n
    \n
    • \n
\n\n
Via pip
\n\n
The package is also available via pip\n(e.g. with recommended extras onnx and pytorch):
\n\n
\n
pip install "bioimageio.core[onnx,pytorch]"\n
\n
\n\n
Set up Development Environment
\n\n
To set up a development conda environment run the following commands:
\n\n
\n
mamba env create -f dev/env.yaml\nmamba activate core\npip install -e . --no-deps\n
\n
\n\n
There are different environment files available that only install tensorflow or pytorch as dependencies.
\n\n
\ud83d\udcbb Use the Command Line Interface
\n\n
bioimageio.core installs a command line interface (CLI) for testing models and other functionality.\nYou can list all the available commands via:
\n\n
\n
bioimageio\n
\n
\n\n
Check that a model adheres to the model spec:
\n\n
\n
bioimageio validate <MODEL>\n
\n
\n\n
Test a model (including prediction for the test input):
\n\n
\n
bioimageio test-model <MODEL>\n
\n
\n\n
Run prediction for an image stored on disc:
\n\n
\n
bioimageio predict-image <MODEL> --inputs <INPUT> --outputs <OUTPUT>\n
\n
\n\n
Run prediction for multiple images stored on disc:
\n\n
\n
bioimagei predict-images -m <MODEL> -i <INPUT_PATTERN> - o <OUTPUT_FOLDER>\n
\n
\n\n
<INPUT_PATTERN> is a glob pattern to select the desired images, e.g. /path/to/my/images/*.tif.
\n\n
\ud83d\udc0d Use in Python
\n\n
bioimageio.core is a python package that implements prediction with bioimageio models\nincluding standardized pre- and postprocessing operations.\nThese models are described by---and can be loaded with---the bioimageio.spec package.
\n\n
In addition bioimageio.core provides functionality to convert model weight formats.
\n\n
To get an overview of this functionality, check out these example notebooks:
\n\n\n\n
and the developer documentation.
\n\n
Model Specification
\n\n
The model specification and its validation tools can be found at https://github.com/bioimage-io/spec-bioimage-io.
\n\n
Changelog
\n\n
0.6.8
\n\n
    \n
  • testing model inference will now check all weight formats\n(previously only the first one for which model adapter creation succeeded had been checked)
    • \n
  • fix predict with blocking (Thanks @thodkatz)
    • \n
\n\n
0.6.7
\n\n
    \n
  • predict() argument inputs may be sample
    • \n
\n\n
0.6.6
\n\n
    \n
  • add aliases to match previous API more closely
    • \n
\n\n
0.6.5
\n\n
    \n
  • improve adapter error messages
    • \n
\n\n
0.6.4
\n\n
    \n
  • add bioimageio validate-format command
    • \n
  • improve error messages and display of command results
    • \n
\n\n
0.6.3
\n\n
    \n
  • Fix #386
    • \n
  • (in model inference testing) stop assuming model inputs are tileable
    • \n
\n\n
0.6.2
\n\n\n\n
0.6.1
\n\n\n\n
0.6.0
\n\n
    \n
  • add compatibility with new bioimageio.spec 0.5 (0.5.2post1)
    • \n
  • improve interfaces
    • \n
\n\n
0.5.10
\n\n\n"}, "bioimageio.core.test_resource": {"fullname": "bioimageio.core.test_resource", "modulename": "bioimageio.core", "qualname": "test_resource", "kind": "function", "doc": "
Test a bioimage.io resource dynamically, e.g. prediction of test tensors for models
\n", "signature": "(\tsource: Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], Dict[str, YamlValue]],\t*,\tformat_version: Union[Literal['discover', 'latest'], str] = 'discover',\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\tdevices: Optional[List[str]] = None,\tabsolute_tolerance: float = 0.00015,\trelative_tolerance: float = 0.0001,\tdecimal: Optional[int] = None,\texpected_type: Optional[str] = None) -> bioimageio.spec.summary.ValidationSummary:", "funcdef": "def"}, "bioimageio.core.load_resource": {"fullname": "bioimageio.core.load_resource", "modulename": "bioimageio.core", "qualname": "load_resource", "kind": "function", "doc": "
load a bioimage.io resource description
\n\n
Args:\n    source: Path or URL to an rdf.yaml or a bioimage.io package\n            (zip-file with rdf.yaml in it).\n    format_version: (optional) Use this argument to load the resource and\n                    convert its metadata to a higher format_version.\n    perform_io_checks: Wether or not to perform validation that requires file io,\n                       e.g. downloading a remote files. The existence of local\n                       absolute file paths is still being checked.\n    known_files: Allows to bypass download and hashing of referenced files\n                 (even if perform_io_checks is True).
\n\n
Returns:\n    An object holding all metadata of the bioimage.io resource
\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.load_model": {"fullname": "bioimageio.core.load_model", "modulename": "bioimageio.core", "qualname": "load_model", "kind": "function", "doc": "
load a bioimage.io resource description
\n\n
Args:\n    source: Path or URL to an rdf.yaml or a bioimage.io package\n            (zip-file with rdf.yaml in it).\n    format_version: (optional) Use this argument to load the resource and\n                    convert its metadata to a higher format_version.\n    perform_io_checks: Wether or not to perform validation that requires file io,\n                       e.g. downloading a remote files. The existence of local\n                       absolute file paths is still being checked.\n    known_files: Allows to bypass download and hashing of referenced files\n                 (even if perform_io_checks is True).
\n\n
Returns:\n    An object holding all metadata of the bioimage.io resource
\n", "signature": "(\tsource: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)]],\t/,\t*,\tformat_version: Union[Literal['discover'], Literal['latest'], str] = 'discover',\tperform_io_checks: bool = True,\tknown_files: Optional[Dict[str, bioimageio.spec._internal.io_basics.Sha256]] = None) -> Union[Annotated[Union[Annotated[Union[bioimageio.spec.application.v0_2.ApplicationDescr, bioimageio.spec.application.v0_3.ApplicationDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.dataset.v0_2.DatasetDescr, bioimageio.spec.dataset.v0_3.DatasetDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.notebook.v0_2.NotebookDescr, bioimageio.spec.notebook.v0_3.NotebookDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.generic.v0_2.GenericDescr, bioimageio.spec.generic.v0_3.GenericDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.spec._internal.common_nodes.InvalidDescr]:", "funcdef": "def"}, "bioimageio.core.axis": {"fullname": "bioimageio.core.axis", "modulename": "bioimageio.core.axis", "kind": "module", "doc": "
\n"}, "bioimageio.core.axis.AxisId": {"fullname": "bioimageio.core.axis.AxisId", "modulename": "bioimageio.core.axis", "qualname": "AxisId", "kind": "class", "doc": "
str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str
\n\n
Create a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to sys.getdefaultencoding().\nerrors defaults to 'strict'.
\n", "bases": "bioimageio.spec._internal.types.LowerCaseIdentifier"}, "bioimageio.core.axis.AxisId.root_model": {"fullname": "bioimageio.core.axis.AxisId.root_model", "modulename": "bioimageio.core.axis", "qualname": "AxisId.root_model", "kind": "variable", "doc": "
the pydantic root model to validate the string
\n", "annotation": ": ClassVar[Type[pydantic.root_model.RootModel[Any]]]", "default_value": "<class 'pydantic.root_model.RootModel[Annotated[str, MinLen, AfterValidator, AfterValidator, Annotated[TypeVar, Predicate], MaxLen]]'>"}, "bioimageio.core.axis.PerAxis": {"fullname": "bioimageio.core.axis.PerAxis", "modulename": "bioimageio.core.axis", "qualname": "PerAxis", "kind": "variable", "doc": "
\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.AxisId, ~T]"}, "bioimageio.core.axis.BatchSize": {"fullname": "bioimageio.core.axis.BatchSize", "modulename": "bioimageio.core.axis", "qualname": "BatchSize", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.axis.AxisLetter": {"fullname": "bioimageio.core.axis.AxisLetter", "modulename": "bioimageio.core.axis", "qualname": "AxisLetter", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x']"}, "bioimageio.core.axis.AxisLike": {"fullname": "bioimageio.core.axis.AxisLike", "modulename": "bioimageio.core.axis", "qualname": "AxisLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[typing.Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], typing.Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], ForwardRef('Axis')]"}, "bioimageio.core.axis.Axis": {"fullname": "bioimageio.core.axis.Axis", "modulename": "bioimageio.core.axis", "qualname": "Axis", "kind": "class", "doc": "
\n"}, "bioimageio.core.axis.Axis.__init__": {"fullname": "bioimageio.core.axis.Axis.__init__", "modulename": "bioimageio.core.axis", "qualname": "Axis.__init__", "kind": "function", "doc": "
\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'])"}, "bioimageio.core.axis.Axis.id": {"fullname": "bioimageio.core.axis.Axis.id", "modulename": "bioimageio.core.axis", "qualname": "Axis.id", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.axis.Axis.type": {"fullname": "bioimageio.core.axis.Axis.type", "modulename": "bioimageio.core.axis", "qualname": "Axis.type", "kind": "variable", "doc": "
\n", "annotation": ": Literal['batch', 'channel', 'index', 'space', 'time']"}, "bioimageio.core.axis.Axis.create": {"fullname": "bioimageio.core.axis.Axis.create", "modulename": "bioimageio.core.axis", "qualname": "Axis.create", "kind": "function", "doc": "
\n", "signature": "(\tcls,\taxis: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]) -> bioimageio.core.axis.Axis:", "funcdef": "def"}, "bioimageio.core.axis.AxisInfo": {"fullname": "bioimageio.core.axis.AxisInfo", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo", "kind": "class", "doc": "
\n", "bases": "Axis"}, "bioimageio.core.axis.AxisInfo.__init__": {"fullname": "bioimageio.core.axis.AxisInfo.__init__", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.__init__", "kind": "function", "doc": "
\n", "signature": "(\tid: bioimageio.spec.model.v0_5.AxisId,\ttype: Literal['batch', 'channel', 'index', 'space', 'time'],\tmaybe_singleton: bool)"}, "bioimageio.core.axis.AxisInfo.maybe_singleton": {"fullname": "bioimageio.core.axis.AxisInfo.maybe_singleton", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.maybe_singleton", "kind": "variable", "doc": "
\n", "annotation": ": bool"}, "bioimageio.core.axis.AxisInfo.create": {"fullname": "bioimageio.core.axis.AxisInfo.create", "modulename": "bioimageio.core.axis", "qualname": "AxisInfo.create", "kind": "function", "doc": "
\n", "signature": "(\tcls,\taxis: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis],\tmaybe_singleton: Optional[bool] = None) -> bioimageio.core.axis.AxisInfo:", "funcdef": "def"}, "bioimageio.core.block": {"fullname": "bioimageio.core.block", "modulename": "bioimageio.core.block", "kind": "module", "doc": "
\n"}, "bioimageio.core.block.Block": {"fullname": "bioimageio.core.block.Block", "modulename": "bioimageio.core.block", "qualname": "Block", "kind": "class", "doc": "
A block/tile of a (larger) tensor
\n", "bases": "bioimageio.core.block_meta.BlockMeta"}, "bioimageio.core.block.Block.__init__": {"fullname": "bioimageio.core.block.Block.__init__", "modulename": "bioimageio.core.block", "qualname": "Block.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int,\tdata: bioimageio.core.tensor.Tensor)"}, "bioimageio.core.block.Block.data": {"fullname": "bioimageio.core.block.Block.data", "modulename": "bioimageio.core.block", "qualname": "Block.data", "kind": "variable", "doc": "
the block's tensor, e.g. a (padded) slice of some larger, original tensor
\n", "annotation": ": bioimageio.core.tensor.Tensor"}, "bioimageio.core.block.Block.inner_data": {"fullname": "bioimageio.core.block.Block.inner_data", "modulename": "bioimageio.core.block", "qualname": "Block.inner_data", "kind": "variable", "doc": "
\n"}, "bioimageio.core.block.Block.from_sample_member": {"fullname": "bioimageio.core.block.Block.from_sample_member", "modulename": "bioimageio.core.block", "qualname": "Block.from_sample_member", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tsample_member: bioimageio.core.tensor.Tensor,\tblock: bioimageio.core.block_meta.BlockMeta,\t*,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.get_transformed": {"fullname": "bioimageio.core.block.Block.get_transformed", "modulename": "bioimageio.core.block", "qualname": "Block.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block.Block.from_meta": {"fullname": "bioimageio.core.block.Block.from_meta", "modulename": "bioimageio.core.block", "qualname": "Block.from_meta", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tmeta: bioimageio.core.block_meta.BlockMeta,\tdata: bioimageio.core.tensor.Tensor) -> Self:", "funcdef": "def"}, "bioimageio.core.block.split_tensor_into_blocks": {"fullname": "bioimageio.core.block.split_tensor_into_blocks", "modulename": "bioimageio.core.block", "qualname": "split_tensor_into_blocks", "kind": "function", "doc": "
divide a sample tensor into tensor blocks.
\n", "signature": "(\ttensor: bioimageio.core.tensor.Tensor,\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None,\tpad_mode: Literal['edge', 'reflect', 'symmetric']) -> Tuple[int, Generator[bioimageio.core.block.Block, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta": {"fullname": "bioimageio.core.block_meta", "modulename": "bioimageio.core.block_meta", "kind": "module", "doc": "
\n"}, "bioimageio.core.block_meta.LinearAxisTransform": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform", "kind": "class", "doc": "
\n"}, "bioimageio.core.block_meta.LinearAxisTransform.__init__": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.__init__", "kind": "function", "doc": "
\n", "signature": "(axis: bioimageio.spec.model.v0_5.AxisId, scale: float, offset: int)"}, "bioimageio.core.block_meta.LinearAxisTransform.axis": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.axis", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.axis", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.AxisId"}, "bioimageio.core.block_meta.LinearAxisTransform.scale": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.scale", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.scale", "kind": "variable", "doc": "
\n", "annotation": ": float"}, "bioimageio.core.block_meta.LinearAxisTransform.offset": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.offset", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.offset", "kind": "variable", "doc": "
\n", "annotation": ": int"}, "bioimageio.core.block_meta.LinearAxisTransform.compute": {"fullname": "bioimageio.core.block_meta.LinearAxisTransform.compute", "modulename": "bioimageio.core.block_meta", "qualname": "LinearAxisTransform.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\ts: int,\tround: Callable[[float], int] = <built-in function floor>) -> int:", "funcdef": "def"}, "bioimageio.core.block_meta.BlockMeta": {"fullname": "bioimageio.core.block_meta.BlockMeta", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta", "kind": "class", "doc": "
Block meta data of a sample member (a tensor in a sample)
\n\n
Figure for illustration:\nThe first 2d block (dashed) of a sample member (bold).\nThe inner slice (thin) is expanded by a halo in both dimensions on both sides.\nThe outer slice reaches from the sample member origin (0, 0) to the right halo point.
\n\n
\u250c \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500  \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2510\n\u2577 halo(left)                         \u2577\n\u2577                                    \u2577\n\u2577  (0, 0)\u250f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u252f\u2501\u2501\u2501\u2794\n\u2577        \u2503                 \u2502         \u2577  sample member\n\u2577        \u2503      inner      \u2502         \u2577\n\u2577        \u2503   (and outer)   \u2502  outer  \u2577\n\u2577        \u2503      slice      \u2502  slice  \u2577\n\u2577        \u2503                 \u2502         \u2577\n\u2577        \u2523\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518         \u2577\n\u2577        \u2503   outer slice             \u2577\n\u2577        \u2503               halo(right) \u2577\n\u2514 \u2500 \u2500 \u2500 \u2500\u2503\u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500 \u2500\u2518\n         \u2b07\n
\n\n
note:
\n\n
    \n
  • Inner and outer slices are specified in sample member coordinates.
    • \n
  • The outer_slice of a block at the sample edge may overlap by more than the\nhalo with the neighboring block (the inner slices will not overlap though).
    • \n
\n"}, "bioimageio.core.block_meta.BlockMeta.__init__": {"fullname": "bioimageio.core.block_meta.BlockMeta.__init__", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tinner_slice: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.block_meta.BlockMeta.sample_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.sample_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.sample_shape", "kind": "variable", "doc": "
the axis sizes of the whole (unblocked) sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice", "kind": "variable", "doc": "
inner region (without halo) wrt the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.halo": {"fullname": "bioimageio.core.block_meta.BlockMeta.halo", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.halo", "kind": "variable", "doc": "
halo enlarging the inner region to the block's sizes
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]"}, "bioimageio.core.block_meta.BlockMeta.block_index": {"fullname": "bioimageio.core.block_meta.BlockMeta.block_index", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.block_index", "kind": "variable", "doc": "
the i-th block of the sample
\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.blocks_in_sample": {"fullname": "bioimageio.core.block_meta.BlockMeta.blocks_in_sample", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.blocks_in_sample", "kind": "variable", "doc": "
total number of blocks in the sample
\n", "annotation": ": int"}, "bioimageio.core.block_meta.BlockMeta.shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.shape", "kind": "variable", "doc": "
axis lengths of the block
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.padding": {"fullname": "bioimageio.core.block_meta.BlockMeta.padding", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.padding", "kind": "variable", "doc": "
padding to realize the halo at the sample edge\nwhere we cannot simply enlarge the inner slice
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.PadWidth]"}, "bioimageio.core.block_meta.BlockMeta.outer_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.outer_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.outer_slice", "kind": "variable", "doc": "
slice of the outer block (without padding) wrt the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.inner_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_shape", "kind": "variable", "doc": "
axis lengths of the inner region (without halo)
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.local_slice": {"fullname": "bioimageio.core.block_meta.BlockMeta.local_slice", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.local_slice", "kind": "variable", "doc": "
inner slice wrt the block, not the sample
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.SliceInfo]"}, "bioimageio.core.block_meta.BlockMeta.dims": {"fullname": "bioimageio.core.block_meta.BlockMeta.dims", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.dims", "kind": "variable", "doc": "
\n", "annotation": ": Collection[bioimageio.spec.model.v0_5.AxisId]"}, "bioimageio.core.block_meta.BlockMeta.tagged_shape": {"fullname": "bioimageio.core.block_meta.BlockMeta.tagged_shape", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.tagged_shape", "kind": "variable", "doc": "
alias for shape
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.AxisId, int]"}, "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap": {"fullname": "bioimageio.core.block_meta.BlockMeta.inner_slice_wo_overlap", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.inner_slice_wo_overlap", "kind": "variable", "doc": "
subslice of the inner slice, such that all inner_slice_wo_overlap can be\nstiched together trivially to form the original sample.
\n\n
This can also be used to calculate statistics\nwithout overrepresenting block edge regions.
\n"}, "bioimageio.core.block_meta.BlockMeta.get_transformed": {"fullname": "bioimageio.core.block_meta.BlockMeta.get_transformed", "modulename": "bioimageio.core.block_meta", "qualname": "BlockMeta.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.block_meta.LinearAxisTransform, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.block_meta.split_shape_into_blocks": {"fullname": "bioimageio.core.block_meta.split_shape_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_shape_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tshape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tblock_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\thalo: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]],\tstride: Optional[Mapping[bioimageio.spec.model.v0_5.AxisId, int]] = None) -> Tuple[int, Generator[bioimageio.core.block_meta.BlockMeta, Any, NoneType]]:", "funcdef": "def"}, "bioimageio.core.block_meta.split_multiple_shapes_into_blocks": {"fullname": "bioimageio.core.block_meta.split_multiple_shapes_into_blocks", "modulename": "bioimageio.core.block_meta", "qualname": "split_multiple_shapes_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tshapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\t*,\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tstrides: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]] = None,\tbroadcast: bool = False) -> Tuple[int, Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]]]:", "funcdef": "def"}, "bioimageio.core.commands": {"fullname": "bioimageio.core.commands", "modulename": "bioimageio.core.commands", "kind": "module", "doc": "
The Bioimageio class defined here has static methods that constitute the bioimageio command line interface (using fire)
\n"}, "bioimageio.core.commands.Bioimageio": {"fullname": "bioimageio.core.commands.Bioimageio", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio", "kind": "class", "doc": "
\ud83e\udd92 CLI to work with resources shared on bioimage.io
\n\n
library versions:\n  bioimageio.core 0.6.8\n  bioimageio.spec 0.6.8
\n\n
spec format versions:\n        model RDF 0.5.3\n      dataset RDF 0.3.0\n     notebook RDF 0.3.0
\n"}, "bioimageio.core.commands.Bioimageio.package": {"fullname": "bioimageio.core.commands.Bioimageio.package", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.package", "kind": "function", "doc": "
Package a bioimageio resource as a zip file
\n\n
Args:\n    source: RDF source e.g. bioimageio.yaml or http://example.com/rdf.yaml\n    path: output path\n    weight-format: include only this single weight-format
\n", "signature": "(\tsource: str,\tpath: pathlib.Path = PosixPath('bioimageio-package.zip'),\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None):", "funcdef": "def"}, "bioimageio.core.commands.Bioimageio.test": {"fullname": "bioimageio.core.commands.Bioimageio.test", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.test", "kind": "function", "doc": "
test a bioimageio resource
\n\n
Args:\n    source: Path or URL to the bioimageio resource description file\n            (bioimageio.yaml or rdf.yaml) or to a zipped resource\n    weight_format: (model only) The weight format to use\n    devices: Device(s) to use for testing\n    decimal: Precision for numerical comparisons
\n", "signature": "(\tsource: str,\tweight_format: Optional[Literal['keras_hdf5', 'onnx', 'pytorch_state_dict', 'tensorflow_js', 'tensorflow_saved_model_bundle', 'torchscript']] = None,\t*,\tdevices: Union[str, List[str], NoneType] = None,\tdecimal: int = 4):", "funcdef": "def"}, "bioimageio.core.commands.Bioimageio.validate_format": {"fullname": "bioimageio.core.commands.Bioimageio.validate_format", "modulename": "bioimageio.core.commands", "qualname": "Bioimageio.validate_format", "kind": "function", "doc": "
validate the meta data format of a bioimageio resource description
\n\n
Args:\n    source: Path or URL to the bioimageio resource description file\n            (bioimageio.yaml or rdf.yaml) or to a zipped resource
\n", "signature": "(source: str):", "funcdef": "def"}, "bioimageio.core.commands.main": {"fullname": "bioimageio.core.commands.main", "modulename": "bioimageio.core.commands", "qualname": "main", "kind": "function", "doc": "
\n", "signature": "():", "funcdef": "def"}, "bioimageio.core.common": {"fullname": "bioimageio.core.common", "modulename": "bioimageio.core.common", "kind": "module", "doc": "
\n"}, "bioimageio.core.common.DTypeStr": {"fullname": "bioimageio.core.common.DTypeStr", "modulename": "bioimageio.core.common", "qualname": "DTypeStr", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.common.CropWidth": {"fullname": "bioimageio.core.common.CropWidth", "modulename": "bioimageio.core.common", "qualname": "CropWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.CropWidth.__init__": {"fullname": "bioimageio.core.common.CropWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "CropWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.CropWidthLike": {"fullname": "bioimageio.core.common.CropWidthLike", "modulename": "bioimageio.core.common", "qualname": "CropWidthLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.CropWidth]"}, "bioimageio.core.common.CropWhere": {"fullname": "bioimageio.core.common.CropWhere", "modulename": "bioimageio.core.common", "qualname": "CropWhere", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.Halo": {"fullname": "bioimageio.core.common.Halo", "modulename": "bioimageio.core.common", "qualname": "Halo", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.Halo.__init__": {"fullname": "bioimageio.core.common.Halo.__init__", "modulename": "bioimageio.core.common", "qualname": "Halo.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.HaloLike": {"fullname": "bioimageio.core.common.HaloLike", "modulename": "bioimageio.core.common", "qualname": "HaloLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.Halo]"}, "bioimageio.core.common.OverlapWidth": {"fullname": "bioimageio.core.common.OverlapWidth", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.OverlapWidth.__init__": {"fullname": "bioimageio.core.common.OverlapWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "OverlapWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidth": {"fullname": "bioimageio.core.common.PadWidth", "modulename": "bioimageio.core.common", "qualname": "PadWidth", "kind": "class", "doc": "
_LeftRight(left, right)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.PadWidth.__init__": {"fullname": "bioimageio.core.common.PadWidth.__init__", "modulename": "bioimageio.core.common", "qualname": "PadWidth.__init__", "kind": "function", "doc": "
Create new instance of _LeftRight(left, right)
\n", "signature": "(left: int, right: int)"}, "bioimageio.core.common.PadWidthLike": {"fullname": "bioimageio.core.common.PadWidthLike", "modulename": "bioimageio.core.common", "qualname": "PadWidthLike", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[int, typing.Tuple[int, int], bioimageio.core.common.PadWidth]"}, "bioimageio.core.common.PadMode": {"fullname": "bioimageio.core.common.PadMode", "modulename": "bioimageio.core.common", "qualname": "PadMode", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['edge', 'reflect', 'symmetric']"}, "bioimageio.core.common.PadWhere": {"fullname": "bioimageio.core.common.PadWhere", "modulename": "bioimageio.core.common", "qualname": "PadWhere", "kind": "variable", "doc": "
\n", "default_value": "typing.Literal['left', 'right', 'left_and_right']"}, "bioimageio.core.common.SliceInfo": {"fullname": "bioimageio.core.common.SliceInfo", "modulename": "bioimageio.core.common", "qualname": "SliceInfo", "kind": "class", "doc": "
SliceInfo(start, stop)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.common.SliceInfo.__init__": {"fullname": "bioimageio.core.common.SliceInfo.__init__", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.__init__", "kind": "function", "doc": "
Create new instance of SliceInfo(start, stop)
\n", "signature": "(start: int, stop: int)"}, "bioimageio.core.common.SliceInfo.start": {"fullname": "bioimageio.core.common.SliceInfo.start", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.start", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": int"}, "bioimageio.core.common.SliceInfo.stop": {"fullname": "bioimageio.core.common.SliceInfo.stop", "modulename": "bioimageio.core.common", "qualname": "SliceInfo.stop", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": int"}, "bioimageio.core.common.SampleId": {"fullname": "bioimageio.core.common.SampleId", "modulename": "bioimageio.core.common", "qualname": "SampleId", "kind": "variable", "doc": "
\n", "default_value": "typing.Hashable"}, "bioimageio.core.common.MemberId": {"fullname": "bioimageio.core.common.MemberId", "modulename": "bioimageio.core.common", "qualname": "MemberId", "kind": "variable", "doc": "
\n", "default_value": "<class 'bioimageio.spec.model.v0_5.TensorId'>"}, "bioimageio.core.common.PerMember": {"fullname": "bioimageio.core.common.PerMember", "modulename": "bioimageio.core.common", "qualname": "PerMember", "kind": "variable", "doc": "
\n", "default_value": "typing.Mapping[bioimageio.spec.model.v0_5.TensorId, ~T]"}, "bioimageio.core.common.BlockIndex": {"fullname": "bioimageio.core.common.BlockIndex", "modulename": "bioimageio.core.common", "qualname": "BlockIndex", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.TotalNumberOfBlocks": {"fullname": "bioimageio.core.common.TotalNumberOfBlocks", "modulename": "bioimageio.core.common", "qualname": "TotalNumberOfBlocks", "kind": "variable", "doc": "
\n", "default_value": "<class 'int'>"}, "bioimageio.core.common.Frozen": {"fullname": "bioimageio.core.common.Frozen", "modulename": "bioimageio.core.common", "qualname": "Frozen", "kind": "variable", "doc": "
\n", "default_value": "<class 'mappingproxy'>"}, "bioimageio.core.dataset": {"fullname": "bioimageio.core.dataset", "modulename": "bioimageio.core.dataset", "kind": "module", "doc": "
\n"}, "bioimageio.core.dataset.Dataset": {"fullname": "bioimageio.core.dataset.Dataset", "modulename": "bioimageio.core.dataset", "qualname": "Dataset", "kind": "variable", "doc": "
\n", "default_value": "typing.Iterable[bioimageio.core.sample.Sample]"}, "bioimageio.core.digest_spec": {"fullname": "bioimageio.core.digest_spec", "modulename": "bioimageio.core.digest_spec", "kind": "module", "doc": "
\n"}, "bioimageio.core.digest_spec.import_callable": {"fullname": "bioimageio.core.digest_spec.import_callable", "modulename": "bioimageio.core.digest_spec", "qualname": "import_callable", "kind": "function", "doc": "
import a callable (e.g. a torch.nn.Module) from a spec node describing it
\n", "signature": "(\tnode: Union[bioimageio.spec.model.v0_4.CallableFromDepencency, bioimageio.spec.model.v0_5.ArchitectureFromLibraryDescr],\t/,\t**kwargs: Unpack[bioimageio.spec._internal.io.HashKwargs]) -> Callable[..., Any]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_axes_infos": {"fullname": "bioimageio.core.digest_spec.get_axes_infos", "modulename": "bioimageio.core.digest_spec", "qualname": "get_axes_infos", "kind": "function", "doc": "
get a unified, simplified axis representation from spec axes
\n", "signature": "(\tio_descr: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> List[bioimageio.core.axis.AxisInfo]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_id": {"fullname": "bioimageio.core.digest_spec.get_member_id", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_id", "kind": "function", "doc": "
get the normalized tensor ID, usable as a sample member ID
\n", "signature": "(\ttensor_description: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]) -> bioimageio.spec.model.v0_5.TensorId:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_member_ids": {"fullname": "bioimageio.core.digest_spec.get_member_ids", "modulename": "bioimageio.core.digest_spec", "qualname": "get_member_ids", "kind": "function", "doc": "
get normalized tensor IDs to be used as sample member IDs
\n", "signature": "(\ttensor_descriptions: Sequence[Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]]) -> List[bioimageio.spec.model.v0_5.TensorId]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_inputs": {"fullname": "bioimageio.core.digest_spec.get_test_inputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_inputs", "kind": "function", "doc": "
returns a model's test input sample
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_test_outputs": {"fullname": "bioimageio.core.digest_spec.get_test_outputs", "modulename": "bioimageio.core.digest_spec", "qualname": "get_test_outputs", "kind": "function", "doc": "
returns a model's test output sample
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta", "kind": "class", "doc": "
IO_SampleBlockMeta(input, output)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.__init__", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.__init__", "kind": "function", "doc": "
Create new instance of IO_SampleBlockMeta(input, output)
\n", "signature": "(\tinput: ForwardRef('SampleBlockMeta'),\toutput: ForwardRef('SampleBlockMeta'))"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.input": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.input", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.input", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.IO_SampleBlockMeta.output": {"fullname": "bioimageio.core.digest_spec.IO_SampleBlockMeta.output", "modulename": "bioimageio.core.digest_spec", "qualname": "IO_SampleBlockMeta.output", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": bioimageio.core.sample.SampleBlockMeta"}, "bioimageio.core.digest_spec.get_input_halo": {"fullname": "bioimageio.core.digest_spec.get_input_halo", "modulename": "bioimageio.core.digest_spec", "qualname": "get_input_halo", "kind": "function", "doc": "
returns which halo input tensors need to be divided into blocks with such that\noutput_halo can be cropped from their outputs without intorducing gaps.
\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\toutput_halo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_block_transform": {"fullname": "bioimageio.core.digest_spec.get_block_transform", "modulename": "bioimageio.core.digest_spec", "qualname": "get_block_transform", "kind": "function", "doc": "
returns how a model's output tensor shapes relate to its input shapes
\n", "signature": "(model: bioimageio.spec.model.v0_5.ModelDescr):", "funcdef": "def"}, "bioimageio.core.digest_spec.get_io_sample_block_metas": {"fullname": "bioimageio.core.digest_spec.get_io_sample_block_metas", "modulename": "bioimageio.core.digest_spec", "qualname": "get_io_sample_block_metas", "kind": "function", "doc": "
returns an iterable yielding meta data for corresponding input and output samples
\n", "signature": "(\tmodel: bioimageio.spec.model.v0_5.ModelDescr,\tinput_sample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tns: Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int],\tbatch_size: int = 1) -> Tuple[int, Iterable[bioimageio.core.digest_spec.IO_SampleBlockMeta]]:", "funcdef": "def"}, "bioimageio.core.digest_spec.get_tensor": {"fullname": "bioimageio.core.digest_spec.get_tensor", "modulename": "bioimageio.core.digest_spec", "qualname": "get_tensor", "kind": "function", "doc": "
helper to cast/load various tensor sources
\n", "signature": "(\tsrc: Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path],\tipt: Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr]):", "funcdef": "def"}, "bioimageio.core.digest_spec.create_sample_for_model": {"fullname": "bioimageio.core.digest_spec.create_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "create_sample_for_model", "kind": "function", "doc": "
Create a sample from a single set of input(s) for a specific bioimage.io model
\n\n
Args:\n    model: a bioimage.io model description\n    stat: dictionary with sample and dataset statistics (may be updated in-place!)\n    inputs: the input(s) constituting a single sample.
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\t*,\tstat: Optional[Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None,\tsample_id: Hashable = None,\tinputs: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]] = None,\t**kwargs: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.digest_spec.load_sample_for_model": {"fullname": "bioimageio.core.digest_spec.load_sample_for_model", "modulename": "bioimageio.core.digest_spec", "qualname": "load_sample_for_model", "kind": "function", "doc": "
load a single sample from paths that can be processed by model
\n", "signature": "(\t*,\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tpaths: Mapping[bioimageio.spec.model.v0_5.TensorId, pathlib.Path],\taxes: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]]] = None,\tstat: Optional[Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None,\tsample_id: Optional[Hashable] = None):", "funcdef": "def"}, "bioimageio.core.io": {"fullname": "bioimageio.core.io", "modulename": "bioimageio.core.io", "kind": "module", "doc": "
\n"}, "bioimageio.core.io.load_image": {"fullname": "bioimageio.core.io.load_image", "modulename": "bioimageio.core.io", "qualname": "load_image", "kind": "function", "doc": "
load a single image as numpy array
\n", "signature": "(\tpath: pathlib.Path,\tis_volume: bool) -> numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]:", "funcdef": "def"}, "bioimageio.core.io.load_tensor": {"fullname": "bioimageio.core.io.load_tensor", "modulename": "bioimageio.core.io", "qualname": "load_tensor", "kind": "function", "doc": "
\n", "signature": "(\tpath: pathlib.Path,\taxes: Optional[Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]]] = None) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.io.save_tensor": {"fullname": "bioimageio.core.io.save_tensor", "modulename": "bioimageio.core.io", "qualname": "save_tensor", "kind": "function", "doc": "
\n", "signature": "(path: pathlib.Path, tensor: bioimageio.core.tensor.Tensor) -> None:", "funcdef": "def"}, "bioimageio.core.io.save_sample": {"fullname": "bioimageio.core.io.save_sample", "modulename": "bioimageio.core.io", "qualname": "save_sample", "kind": "function", "doc": "
save a sample to path
\n\n
path must contain {member_id} and may contain {sample_id},\nwhich are resolved with the sample object.
\n", "signature": "(\tpath: Union[pathlib.Path, str],\tsample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.model_adapters": {"fullname": "bioimageio.core.model_adapters", "modulename": "bioimageio.core.model_adapters", "kind": "module", "doc": "
\n"}, "bioimageio.core.prediction": {"fullname": "bioimageio.core.prediction", "modulename": "bioimageio.core.prediction", "kind": "module", "doc": "
convenience functions for prediction coming soon.\nFor now, please use create_prediction_pipeline to get a PredictionPipeline\nand then PredictionPipeline.predict_sample(sample)\ne..g load samples with core.io.load_sample_for_model()
\n"}, "bioimageio.core.prediction.predict": {"fullname": "bioimageio.core.prediction.predict", "modulename": "bioimageio.core.prediction", "qualname": "predict", "kind": "function", "doc": "
Run prediction for a single set of input(s) with a bioimage.io model
\n\n
Args:\n    model: model to predict with.\n        May be given as RDF source, model description or prediction pipeline.\n    inputs: the input sample or the named input(s) for this model as a dictionary\n    sample_id: the sample id.\n    blocksize_parameter: (optional) tile the input into blocks parametrized by\n        blocksize according to any parametrized axis sizes defined in the model RDF\n    skip_preprocessing: flag to skip the model's preprocessing\n    skip_postprocessing: flag to skip the model's postprocessing\n    save_output_path: A path with {member_id} {sample_id} in it\n        to save the output to.
\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Union[bioimageio.core.sample.Sample, Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: Hashable = 'sample',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> bioimageio.core.sample.Sample:", "funcdef": "def"}, "bioimageio.core.prediction.predict_many": {"fullname": "bioimageio.core.prediction.predict_many", "modulename": "bioimageio.core.prediction", "qualname": "predict_many", "kind": "function", "doc": "
Run prediction for a multiple sets of inputs with a bioimage.io model
\n\n
Args:\n    model: model to predict with.\n        May be given as RDF source, model description or prediction pipeline.\n    inputs: An iterable of the named input(s) for this model as a dictionary.\n    sample_id: the sample id.\n        note: {i} will be formatted as the i-th sample.\n        If {i} (or {i:) is not present and inputs is an iterable {i:03} is appended.\n    blocksize_parameter: (optional) tile the input into blocks parametrized by\n        blocksize according to any parametrized axis sizes defined in the model RDF\n    skip_preprocessing: flag to skip the model's preprocessing\n    skip_postprocessing: flag to skip the model's postprocessing\n    save_output_path: A path with {member_id} {sample_id} in it\n        to save the output to.
\n", "signature": "(\t*,\tmodel: Union[Annotated[Union[bioimageio.spec._internal.url.HttpUrl, bioimageio.spec._internal.io.RelativeFilePath, Annotated[pathlib.Path, PathType(path_type='file')]], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])], str, Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=2083, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr, bioimageio.core._prediction_pipeline.PredictionPipeline],\tinputs: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, Union[bioimageio.core.tensor.Tensor, xarray.core.dataarray.DataArray, numpy.ndarray[Any, numpy.dtype[Any]], pathlib.Path]]],\tsample_id: str = 'sample{i:03}',\tblocksize_parameter: Union[int, Mapping[Tuple[bioimageio.spec.model.v0_5.TensorId, bioimageio.spec.model.v0_5.AxisId], int], NoneType] = None,\tskip_preprocessing: bool = False,\tskip_postprocessing: bool = False,\tsave_output_path: Union[pathlib.Path, str, NoneType] = None) -> Iterator[bioimageio.core.sample.Sample]:", "funcdef": "def"}, "bioimageio.core.proc_ops": {"fullname": "bioimageio.core.proc_ops", "modulename": "bioimageio.core.proc_ops", "kind": "module", "doc": "
\n"}, "bioimageio.core.proc_ops.convert_axis_ids": {"fullname": "bioimageio.core.proc_ops.convert_axis_ids", "modulename": "bioimageio.core.proc_ops", "qualname": "convert_axis_ids", "kind": "function", "doc": "
\n", "signature": "(\taxes: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Annotated[str, RestrictCharacters(alphabet='czyx'), AfterValidator(func=<function validate_unique_entries>)]],\tmode: Literal['per_sample', 'per_dataset']) -> Tuple[bioimageio.spec.model.v0_5.AxisId, ...]:", "funcdef": "def"}, "bioimageio.core.proc_ops.AddKnownDatasetStats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats", "kind": "class", "doc": "
\n", "bases": "bioimageio.core._op_base.BlockedOperator"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.__init__", "kind": "function", "doc": "
\n", "signature": "(\tdataset_stats: Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]])"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.dataset_stats", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures": {"fullname": "bioimageio.core.proc_ops.AddKnownDatasetStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "AddKnownDatasetStats.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.UpdateStats": {"fullname": "bioimageio.core.proc_ops.UpdateStats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats", "kind": "class", "doc": "
Calculates sample and/or dataset measures
\n", "bases": "bioimageio.core._op_base.Operator"}, "bioimageio.core.proc_ops.UpdateStats.__init__": {"fullname": "bioimageio.core.proc_ops.UpdateStats.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.__init__", "kind": "function", "doc": "
\n", "signature": "(\tstats_calculator: bioimageio.core.stat_calculators.StatsCalculator,\tkeep_updating_initial_dataset_stats: bool = False)"}, "bioimageio.core.proc_ops.UpdateStats.stats_calculator": {"fullname": "bioimageio.core.proc_ops.UpdateStats.stats_calculator", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.stats_calculator", "kind": "variable", "doc": "
StatsCalculator to be used by this operator.
\n", "annotation": ": bioimageio.core.stat_calculators.StatsCalculator"}, "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats": {"fullname": "bioimageio.core.proc_ops.UpdateStats.keep_updating_initial_dataset_stats", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.keep_updating_initial_dataset_stats", "kind": "variable", "doc": "
indicates if operator calls should keep updating initial dataset statistics or not;\nif the stats_calculator was not provided with any initial dataset statistics,\nthese are always updated with every new sample.
\n", "annotation": ": bool", "default_value": "False"}, "bioimageio.core.proc_ops.UpdateStats.required_measures": {"fullname": "bioimageio.core.proc_ops.UpdateStats.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "UpdateStats.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.Binarize": {"fullname": "bioimageio.core.proc_ops.Binarize", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize", "kind": "class", "doc": "
'output = tensor > threshold'.
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Binarize.__init__": {"fullname": "bioimageio.core.proc_ops.Binarize.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tthreshold: Union[float, Sequence[float]],\taxis: Optional[bioimageio.spec.model.v0_5.AxisId] = None)"}, "bioimageio.core.proc_ops.Binarize.threshold": {"fullname": "bioimageio.core.proc_ops.Binarize.threshold", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.threshold", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, Sequence[float]]"}, "bioimageio.core.proc_ops.Binarize.axis": {"fullname": "bioimageio.core.proc_ops.Binarize.axis", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.axis", "kind": "variable", "doc": "
\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.AxisId]", "default_value": "None"}, "bioimageio.core.proc_ops.Binarize.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Binarize.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Binarize.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Binarize.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Binarize.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_5.BinarizeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip": {"fullname": "bioimageio.core.proc_ops.Clip", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Clip.__init__": {"fullname": "bioimageio.core.proc_ops.Clip.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmin: Optional[float] = None,\tmax: Optional[float] = None)"}, "bioimageio.core.proc_ops.Clip.min": {"fullname": "bioimageio.core.proc_ops.Clip.min", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.min", "kind": "variable", "doc": "
minimum value for clipping
\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.max": {"fullname": "bioimageio.core.proc_ops.Clip.max", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.max", "kind": "variable", "doc": "
maximum value for clipping
\n", "annotation": ": Optional[float]", "default_value": "None"}, "bioimageio.core.proc_ops.Clip.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Clip.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Clip.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Clip.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Clip.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_5.ClipDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.EnsureDtype.__init__": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'])"}, "bioimageio.core.proc_ops.EnsureDtype.dtype": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.dtype", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.dtype", "kind": "variable", "doc": "
\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.EnsureDtypeDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_descr": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.EnsureDtype.get_output_shape": {"fullname": "bioimageio.core.proc_ops.EnsureDtype.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "EnsureDtype.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear": {"fullname": "bioimageio.core.proc_ops.ScaleLinear", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleLinear.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tgain: Union[float, xarray.core.dataarray.DataArray] = 1.0,\toffset: Union[float, xarray.core.dataarray.DataArray] = 0.0)"}, "bioimageio.core.proc_ops.ScaleLinear.gain": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.gain", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.gain", "kind": "variable", "doc": "
multiplicative factor
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "1.0"}, "bioimageio.core.proc_ops.ScaleLinear.offset": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.offset", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.offset", "kind": "variable", "doc": "
additive term
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]", "default_value": "0.0"}, "bioimageio.core.proc_ops.ScaleLinear.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleLinear.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleLinear.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleMeanVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]] = None,\treference_tensor: Optional[bioimageio.spec.model.v0_5.TensorId] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleMeanVariance.axes": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.axes", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.axes", "kind": "variable", "doc": "
\n", "annotation": ": Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.reference_tensor", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.reference_tensor", "kind": "variable", "doc": "
\n", "annotation": ": Optional[bioimageio.spec.model.v0_5.TensorId]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleMeanVariance.eps": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleMeanVariance.mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.std", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.ref_std", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.ref_std", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.required_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleMeanVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleMeanVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange": {"fullname": "bioimageio.core.proc_ops.ScaleRange", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange", "kind": "class", "doc": "
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ScaleRange.__init__": {"fullname": "bioimageio.core.proc_ops.ScaleRange.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tlower_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\tupper_percentile: dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]] = None,\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ScaleRange.lower_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower_percentile", "kind": "variable", "doc": "
\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.upper_percentile": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper_percentile", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper_percentile", "kind": "variable", "doc": "
\n", "annotation": ": dataclasses.InitVar[typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile, NoneType]]", "default_value": "None"}, "bioimageio.core.proc_ops.ScaleRange.lower": {"fullname": "bioimageio.core.proc_ops.ScaleRange.lower", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.lower", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.upper": {"fullname": "bioimageio.core.proc_ops.ScaleRange.upper", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.upper", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.proc_ops.ScaleRange.eps": {"fullname": "bioimageio.core.proc_ops.ScaleRange.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ScaleRange.required_measures": {"fullname": "bioimageio.core.proc_ops.ScaleRange.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.required_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.proc_ops.ScaleRange.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ScaleRange.get_descr": {"fullname": "bioimageio.core.proc_ops.ScaleRange.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ScaleRange.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid": {"fullname": "bioimageio.core.proc_ops.Sigmoid", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid", "kind": "class", "doc": "
1 / (1 + e^(-input)).
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.Sigmoid.__init__": {"fullname": "bioimageio.core.proc_ops.Sigmoid.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.proc_ops.Sigmoid.required_measures": {"fullname": "bioimageio.core.proc_ops.Sigmoid.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Collection[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]"}, "bioimageio.core.proc_ops.Sigmoid.get_output_shape": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_5.SigmoidDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.Sigmoid.get_descr": {"fullname": "bioimageio.core.proc_ops.Sigmoid.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "Sigmoid.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance", "kind": "class", "doc": "
normalize to zero mean, unit variance.
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean],\tstd: Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.std", "kind": "variable", "doc": "
\n", "annotation": ": Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.required_measures", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.required_measures", "kind": "variable", "doc": "
\n", "annotation": ": Set[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]]"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: Union[bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr],\tmember_id: bioimageio.spec.model.v0_5.TensorId):", "funcdef": "def"}, "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.ZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "ZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance", "kind": "class", "doc": "
normalize to zero mean, unit variance with precomputed values.
\n", "bases": "_SimpleOperator"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.__init__", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.__init__", "kind": "function", "doc": "
\n", "signature": "(\tinput: bioimageio.spec.model.v0_5.TensorId,\toutput: bioimageio.spec.model.v0_5.TensorId,\tmean: Union[float, xarray.core.dataarray.DataArray],\tstd: Union[float, xarray.core.dataarray.DataArray],\teps: float = 1e-06)"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.mean", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.mean", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.std", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.std", "kind": "variable", "doc": "
\n", "annotation": ": Union[float, xarray.core.dataarray.DataArray]"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.eps", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.eps", "kind": "variable", "doc": "
\n", "annotation": ": float", "default_value": "1e-06"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_output_shape", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_output_shape", "kind": "function", "doc": "
\n", "signature": "(\tself,\tinput_shape: Mapping[bioimageio.spec.model.v0_5.AxisId, int]) -> Mapping[bioimageio.spec.model.v0_5.AxisId, int]:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.from_proc_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.from_proc_descr", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tdescr: bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr,\tmember_id: bioimageio.spec.model.v0_5.TensorId) -> Self:", "funcdef": "def"}, "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr": {"fullname": "bioimageio.core.proc_ops.FixedZeroMeanUnitVariance.get_descr", "modulename": "bioimageio.core.proc_ops", "qualname": "FixedZeroMeanUnitVariance.get_descr", "kind": "function", "doc": "
\n", "signature": "(self):", "funcdef": "def"}, "bioimageio.core.proc_ops.ProcDescr": {"fullname": "bioimageio.core.proc_ops.ProcDescr", "modulename": "bioimageio.core.proc_ops", "qualname": "ProcDescr", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], typing.Annotated[typing.Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]"}, "bioimageio.core.proc_ops.Processing": {"fullname": "bioimageio.core.proc_ops.Processing", "modulename": "bioimageio.core.proc_ops", "qualname": "Processing", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]"}, "bioimageio.core.proc_ops.get_proc_class": {"fullname": "bioimageio.core.proc_ops.get_proc_class", "modulename": "bioimageio.core.proc_ops", "qualname": "get_proc_class", "kind": "function", "doc": "
\n", "signature": "(\tproc_spec: Union[Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_4.BinarizeDescr, bioimageio.spec.model.v0_4.ClipDescr, bioimageio.spec.model.v0_4.ScaleLinearDescr, bioimageio.spec.model.v0_4.SigmoidDescr, bioimageio.spec.model.v0_4.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_4.ScaleRangeDescr, bioimageio.spec.model.v0_4.ScaleMeanVarianceDescr], Discriminator(discriminator='name', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BinarizeDescr, bioimageio.spec.model.v0_5.ClipDescr, bioimageio.spec.model.v0_5.EnsureDtypeDescr, bioimageio.spec.model.v0_5.ScaleLinearDescr, bioimageio.spec.model.v0_5.SigmoidDescr, bioimageio.spec.model.v0_5.FixedZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ZeroMeanUnitVarianceDescr, bioimageio.spec.model.v0_5.ScaleRangeDescr, bioimageio.spec.model.v0_5.ScaleMeanVarianceDescr], Discriminator(discriminator='id', custom_error_type=None, custom_error_message=None, custom_error_context=None)]]):", "funcdef": "def"}, "bioimageio.core.proc_setup": {"fullname": "bioimageio.core.proc_setup", "modulename": "bioimageio.core.proc_setup", "kind": "module", "doc": "
\n"}, "bioimageio.core.proc_setup.TensorDescr": {"fullname": "bioimageio.core.proc_setup.TensorDescr", "modulename": "bioimageio.core.proc_setup", "qualname": "TensorDescr", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.spec.model.v0_4.InputTensorDescr, bioimageio.spec.model.v0_4.OutputTensorDescr, bioimageio.spec.model.v0_5.InputTensorDescr, bioimageio.spec.model.v0_5.OutputTensorDescr]"}, "bioimageio.core.proc_setup.PreAndPostprocessing": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing", "kind": "class", "doc": "
PreAndPostprocessing(pre, post)
\n", "bases": "typing.NamedTuple"}, "bioimageio.core.proc_setup.PreAndPostprocessing.__init__": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.__init__", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.__init__", "kind": "function", "doc": "
Create new instance of PreAndPostprocessing(pre, post)
\n", "signature": "(\tpre: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]],\tpost: List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]])"}, "bioimageio.core.proc_setup.PreAndPostprocessing.pre": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.pre", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.pre", "kind": "variable", "doc": "
Alias for field number 0
\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.PreAndPostprocessing.post": {"fullname": "bioimageio.core.proc_setup.PreAndPostprocessing.post", "modulename": "bioimageio.core.proc_setup", "qualname": "PreAndPostprocessing.post", "kind": "variable", "doc": "
Alias for field number 1
\n", "annotation": ": List[Union[bioimageio.core.proc_ops.AddKnownDatasetStats, bioimageio.core.proc_ops.Binarize, bioimageio.core.proc_ops.Clip, bioimageio.core.proc_ops.EnsureDtype, bioimageio.core.proc_ops.FixedZeroMeanUnitVariance, bioimageio.core.proc_ops.ScaleLinear, bioimageio.core.proc_ops.ScaleMeanVariance, bioimageio.core.proc_ops.ScaleRange, bioimageio.core.proc_ops.Sigmoid, bioimageio.core.proc_ops.UpdateStats, bioimageio.core.proc_ops.ZeroMeanUnitVariance]]"}, "bioimageio.core.proc_setup.setup_pre_and_postprocessing": {"fullname": "bioimageio.core.proc_setup.setup_pre_and_postprocessing", "modulename": "bioimageio.core.proc_setup", "qualname": "setup_pre_and_postprocessing", "kind": "function", "doc": "
Get pre- and postprocessing operators for a model description.\nuserd in `bioimageio.core.create_prediction_pipeline
\n", "signature": "(\tmodel: Annotated[Union[bioimageio.spec.model.v0_4.ModelDescr, bioimageio.spec.model.v0_5.ModelDescr], Discriminator(discriminator='format_version', custom_error_type=None, custom_error_message=None, custom_error_context=None)],\tdataset_for_initial_statistics: Iterable[bioimageio.core.sample.Sample],\tkeep_updating_initial_dataset_stats: bool = False,\tfixed_dataset_stats: Optional[Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None) -> bioimageio.core.proc_setup.PreAndPostprocessing:", "funcdef": "def"}, "bioimageio.core.sample": {"fullname": "bioimageio.core.sample", "modulename": "bioimageio.core.sample", "kind": "module", "doc": "
\n"}, "bioimageio.core.sample.Sample": {"fullname": "bioimageio.core.sample.Sample", "modulename": "bioimageio.core.sample", "qualname": "Sample", "kind": "class", "doc": "
A dataset sample
\n"}, "bioimageio.core.sample.Sample.__init__": {"fullname": "bioimageio.core.sample.Sample.__init__", "modulename": "bioimageio.core.sample", "qualname": "Sample.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmembers: Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]],\tid: Hashable)"}, "bioimageio.core.sample.Sample.members": {"fullname": "bioimageio.core.sample.Sample.members", "modulename": "bioimageio.core.sample", "qualname": "Sample.members", "kind": "variable", "doc": "
the sample's tensors
\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.Sample.stat": {"fullname": "bioimageio.core.sample.Sample.stat", "modulename": "bioimageio.core.sample", "qualname": "Sample.stat", "kind": "variable", "doc": "
sample and dataset statistics
\n", "annotation": ": Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.sample.Sample.id": {"fullname": "bioimageio.core.sample.Sample.id", "modulename": "bioimageio.core.sample", "qualname": "Sample.id", "kind": "variable", "doc": "
identifier within the sample's dataset
\n", "annotation": ": Hashable"}, "bioimageio.core.sample.Sample.shape": {"fullname": "bioimageio.core.sample.Sample.shape", "modulename": "bioimageio.core.sample", "qualname": "Sample.shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.Sample.split_into_blocks": {"fullname": "bioimageio.core.sample.Sample.split_into_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.split_into_blocks", "kind": "function", "doc": "
\n", "signature": "(\tself,\tblock_shapes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\thalo: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.Halo]]],\tpad_mode: Literal['edge', 'reflect', 'symmetric'],\tbroadcast: bool = False) -> Tuple[int, Iterable[bioimageio.core.sample.SampleBlockWithOrigin]]:", "funcdef": "def"}, "bioimageio.core.sample.Sample.as_single_block": {"fullname": "bioimageio.core.sample.Sample.as_single_block", "modulename": "bioimageio.core.sample", "qualname": "Sample.as_single_block", "kind": "function", "doc": "
\n", "signature": "(\tself,\thalo: Optional[Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, bioimageio.core.common.Halo]]] = None):", "funcdef": "def"}, "bioimageio.core.sample.Sample.from_blocks": {"fullname": "bioimageio.core.sample.Sample.from_blocks", "modulename": "bioimageio.core.sample", "qualname": "Sample.from_blocks", "kind": "function", "doc": "
\n", "signature": "(\tcls,\tsample_blocks: Iterable[bioimageio.core.sample.SampleBlock],\t*,\tfill_value: float = nan) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockBase": {"fullname": "bioimageio.core.sample.SampleBlockBase", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase", "kind": "class", "doc": "
base class for SampleBlockMeta and SampleBlock
\n", "bases": "typing.Generic[~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.__init__": {"fullname": "bioimageio.core.sample.SampleBlockBase.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockBase.sample_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_shape", "kind": "variable", "doc": "
the sample shape this block represents a part of
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.sample_id": {"fullname": "bioimageio.core.sample.SampleBlockBase.sample_id", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.sample_id", "kind": "variable", "doc": "
identifier for the sample within its dataset
\n", "annotation": ": Hashable"}, "bioimageio.core.sample.SampleBlockBase.blocks": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks", "kind": "variable", "doc": "
Individual tensor blocks comprising this sample block
\n", "annotation": ": Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT]"}, "bioimageio.core.sample.SampleBlockBase.block_index": {"fullname": "bioimageio.core.sample.SampleBlockBase.block_index", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.block_index", "kind": "variable", "doc": "
the n-th block of the sample
\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.blocks_in_sample": {"fullname": "bioimageio.core.sample.SampleBlockBase.blocks_in_sample", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.blocks_in_sample", "kind": "variable", "doc": "
total number of blocks in the sample
\n", "annotation": ": int"}, "bioimageio.core.sample.SampleBlockBase.shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.SampleBlockBase.inner_shape": {"fullname": "bioimageio.core.sample.SampleBlockBase.inner_shape", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockBase.inner_shape", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]]"}, "bioimageio.core.sample.LinearSampleAxisTransform": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform", "kind": "class", "doc": "
\n", "bases": "bioimageio.core.block_meta.LinearAxisTransform"}, "bioimageio.core.sample.LinearSampleAxisTransform.__init__": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.__init__", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.__init__", "kind": "function", "doc": "
\n", "signature": "(\taxis: bioimageio.spec.model.v0_5.AxisId,\tscale: float,\toffset: int,\tmember: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.sample.LinearSampleAxisTransform.member": {"fullname": "bioimageio.core.sample.LinearSampleAxisTransform.member", "modulename": "bioimageio.core.sample", "qualname": "LinearSampleAxisTransform.member", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.sample.SampleBlockMeta": {"fullname": "bioimageio.core.sample.SampleBlockMeta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta", "kind": "class", "doc": "
Meta data of a dataset sample block
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block_meta.BlockMeta]"}, "bioimageio.core.sample.SampleBlockMeta.__init__": {"fullname": "bioimageio.core.sample.SampleBlockMeta.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int)"}, "bioimageio.core.sample.SampleBlockMeta.get_transformed": {"fullname": "bioimageio.core.sample.SampleBlockMeta.get_transformed", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.get_transformed", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> Self:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockMeta.with_data": {"fullname": "bioimageio.core.sample.SampleBlockMeta.with_data", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockMeta.with_data", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdata: Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor],\t*,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]) -> bioimageio.core.sample.SampleBlock:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlock": {"fullname": "bioimageio.core.sample.SampleBlock", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock", "kind": "class", "doc": "
A block of a dataset sample
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlock.__init__": {"fullname": "bioimageio.core.sample.SampleBlock.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]])"}, "bioimageio.core.sample.SampleBlock.stat": {"fullname": "bioimageio.core.sample.SampleBlock.stat", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.stat", "kind": "variable", "doc": "
computed statistics
\n", "annotation": ": Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.sample.SampleBlock.members": {"fullname": "bioimageio.core.sample.SampleBlock.members", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.members", "kind": "variable", "doc": "
the sample block's tensors
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.sample.SampleBlock.get_transformed_meta": {"fullname": "bioimageio.core.sample.SampleBlock.get_transformed_meta", "modulename": "bioimageio.core.sample", "qualname": "SampleBlock.get_transformed_meta", "kind": "function", "doc": "
\n", "signature": "(\tself,\tnew_axes: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, Union[bioimageio.core.sample.LinearSampleAxisTransform, int]]]) -> bioimageio.core.sample.SampleBlockMeta:", "funcdef": "def"}, "bioimageio.core.sample.SampleBlockWithOrigin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin", "kind": "class", "doc": "
\n", "bases": "bioimageio.core.sample.SampleBlockBase[bioimageio.core.block.Block]"}, "bioimageio.core.sample.SampleBlockWithOrigin.__init__": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.__init__", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.__init__", "kind": "function", "doc": "
\n", "signature": "(\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable,\tblocks: Dict[bioimageio.spec.model.v0_5.TensorId, ~BlockT],\tblock_index: int,\tblocks_in_sample: int,\tstat: Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]],\torigin: bioimageio.core.sample.Sample)"}, "bioimageio.core.sample.SampleBlockWithOrigin.origin": {"fullname": "bioimageio.core.sample.SampleBlockWithOrigin.origin", "modulename": "bioimageio.core.sample", "qualname": "SampleBlockWithOrigin.origin", "kind": "variable", "doc": "
the sample this sample black was taken from
\n", "annotation": ": bioimageio.core.sample.Sample"}, "bioimageio.core.sample.sample_block_meta_generator": {"fullname": "bioimageio.core.sample.sample_block_meta_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_meta_generator", "kind": "function", "doc": "
\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\tsample_shape: Mapping[bioimageio.spec.model.v0_5.TensorId, Mapping[bioimageio.spec.model.v0_5.AxisId, int]],\tsample_id: Hashable):", "funcdef": "def"}, "bioimageio.core.sample.sample_block_generator": {"fullname": "bioimageio.core.sample.sample_block_generator", "modulename": "bioimageio.core.sample", "qualname": "sample_block_generator", "kind": "function", "doc": "
\n", "signature": "(\tblocks: Iterable[Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.block_meta.BlockMeta]],\t*,\torigin: bioimageio.core.sample.Sample,\tpad_mode: Literal['edge', 'reflect', 'symmetric']):", "funcdef": "def"}, "bioimageio.core.stat_calculators": {"fullname": "bioimageio.core.stat_calculators", "modulename": "bioimageio.core.stat_calculators", "kind": "module", "doc": "
\n"}, "bioimageio.core.stat_calculators.MeanCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator", "kind": "class", "doc": "
to calculate sample and dataset mean for in-memory samples
\n"}, "bioimageio.core.stat_calculators.MeanCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.compute_and_update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.compute_and_update", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetMean, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator", "kind": "class", "doc": "
to calculate sample and dataset mean, variance or standard deviation
\n"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]])"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleStd], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanVarStdCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanVarStdCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetStd], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator", "kind": "class", "doc": "
to calculate sample percentiles
\n"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.SamplePercentilesCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "SamplePercentilesCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[bioimageio.core.stat_measures.SampleQuantile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator", "kind": "class", "doc": "
to calculate dataset percentiles heuristically by averaging across samples\nnote: the returned dataset percentiles are an estiamte and not mathematically correct
\n"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, sample: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.MeanPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "MeanPercentilesCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator", "kind": "class", "doc": "
to calculate dataset percentiles with the experimental crick libray
\n"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Sequence[bioimageio.spec.model.v0_5.AxisId]],\tqs: Collection[float])"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.update", "kind": "function", "doc": "
\n", "signature": "(self, part: bioimageio.core.sample.Sample):", "funcdef": "def"}, "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.CrickPercentilesCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "CrickPercentilesCalculator.finalize", "kind": "function", "doc": "
\n", "signature": "(\tself) -> Dict[bioimageio.core.stat_measures.DatasetPercentile, Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator", "kind": "class", "doc": "
wrapper for measures to match interface of other sample measure calculators
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tmeasure: Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile])"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.tensor_name", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.tensor_name", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.measure", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.measure", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute": {"fullname": "bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator.compute", "modulename": "bioimageio.core.stat_calculators", "qualname": "NaiveSampleMeasureCalculator.compute", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.SampleMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.SampleMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "SampleMeasureCalculator", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]"}, "bioimageio.core.stat_calculators.DatasetMeasureCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetMeasureCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetMeasureCalculator", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]"}, "bioimageio.core.stat_calculators.StatsCalculator": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator", "kind": "class", "doc": "
Estimates dataset statistics and computes sample statistics efficiently
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.__init__": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.__init__", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmeasures: Collection[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tinitial_dataset_measures: Optional[Mapping[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]] = None)"}, "bioimageio.core.stat_calculators.StatsCalculator.sample_count": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.sample_count", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.sample_count", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.has_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.has_dataset_measures", "kind": "variable", "doc": "
\n"}, "bioimageio.core.stat_calculators.StatsCalculator.update": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update", "kind": "function", "doc": "
\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> None:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.finalize": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.finalize", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.finalize", "kind": "function", "doc": "
returns aggregated dataset statistics
\n", "signature": "(\tself) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.update_and_get_all", "kind": "function", "doc": "
Returns sample as well as updated dataset statistics
\n", "signature": "(\tself,\tsample: Union[bioimageio.core.sample.Sample, Iterable[bioimageio.core.sample.Sample]]) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all": {"fullname": "bioimageio.core.stat_calculators.StatsCalculator.skip_update_and_get_all", "modulename": "bioimageio.core.stat_calculators", "qualname": "StatsCalculator.skip_update_and_get_all", "kind": "function", "doc": "
Returns sample as well as previously computed dataset statistics
\n", "signature": "(\tself,\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.get_measure_calculators": {"fullname": "bioimageio.core.stat_calculators.get_measure_calculators", "modulename": "bioimageio.core.stat_calculators", "qualname": "get_measure_calculators", "kind": "function", "doc": "
determines which calculators are needed to compute the required measures efficiently
\n", "signature": "(\trequired_measures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]]) -> Tuple[List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.SamplePercentilesCalculator, bioimageio.core.stat_calculators.NaiveSampleMeasureCalculator]], List[Union[bioimageio.core.stat_calculators.MeanCalculator, bioimageio.core.stat_calculators.MeanVarStdCalculator, bioimageio.core.stat_calculators.MeanPercentilesCalculator]]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_dataset_measures": {"fullname": "bioimageio.core.stat_calculators.compute_dataset_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_dataset_measures", "kind": "function", "doc": "
compute all dataset measures for the given dataset
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_sample_measures": {"fullname": "bioimageio.core.stat_calculators.compute_sample_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_sample_measures", "kind": "function", "doc": "
compute all sample measures for the given sample
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile]],\tsample: bioimageio.core.sample.Sample) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.compute_measures": {"fullname": "bioimageio.core.stat_calculators.compute_measures", "modulename": "bioimageio.core.stat_calculators", "qualname": "compute_measures", "kind": "function", "doc": "
compute all measures for the given dataset\nsample measures are computed for the last sample in dataset
\n", "signature": "(\tmeasures: Iterable[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]],\tdataset: Iterable[bioimageio.core.sample.Sample]) -> Dict[Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], Union[float, bioimageio.core.tensor.Tensor]]:", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest": {"fullname": "bioimageio.core.stat_calculators.TDigest", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest", "kind": "class", "doc": "
\n"}, "bioimageio.core.stat_calculators.TDigest.update": {"fullname": "bioimageio.core.stat_calculators.TDigest.update", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.update", "kind": "function", "doc": "
\n", "signature": "(self, obj: Any):", "funcdef": "def"}, "bioimageio.core.stat_calculators.TDigest.quantile": {"fullname": "bioimageio.core.stat_calculators.TDigest.quantile", "modulename": "bioimageio.core.stat_calculators", "qualname": "TDigest.quantile", "kind": "function", "doc": "
\n", "signature": "(self, q: Any) -> Any:", "funcdef": "def"}, "bioimageio.core.stat_calculators.DatasetPercentilesCalculator": {"fullname": "bioimageio.core.stat_calculators.DatasetPercentilesCalculator", "modulename": "bioimageio.core.stat_calculators", "qualname": "DatasetPercentilesCalculator", "kind": "variable", "doc": "
\n", "annotation": ": Type[Union[bioimageio.core.stat_calculators.MeanPercentilesCalculator, bioimageio.core.stat_calculators.CrickPercentilesCalculator]]", "default_value": "<class 'bioimageio.core.stat_calculators.MeanPercentilesCalculator'>"}, "bioimageio.core.stat_measures": {"fullname": "bioimageio.core.stat_measures", "modulename": "bioimageio.core.stat_measures", "kind": "module", "doc": "
\n"}, "bioimageio.core.stat_measures.MeasureValue": {"fullname": "bioimageio.core.stat_measures.MeasureValue", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureValue", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[float, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.SampleLike": {"fullname": "bioimageio.core.stat_measures.SampleLike", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike", "kind": "class", "doc": "
Base class for protocol classes.
\n\n
Protocol classes are defined as::
\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n
Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).
\n\n
For example::
\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n
See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::
\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.stat_measures.SampleLike.__init__": {"fullname": "bioimageio.core.stat_measures.SampleLike.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.__init__", "kind": "function", "doc": "
\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.stat_measures.SampleLike.members": {"fullname": "bioimageio.core.stat_measures.SampleLike.members", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleLike.members", "kind": "variable", "doc": "
\n", "annotation": ": Mapping[bioimageio.spec.model.v0_5.TensorId, bioimageio.core.tensor.Tensor]"}, "bioimageio.core.stat_measures.MeasureBase": {"fullname": "bioimageio.core.stat_measures.MeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase", "kind": "class", "doc": "
\n"}, "bioimageio.core.stat_measures.MeasureBase.__init__": {"fullname": "bioimageio.core.stat_measures.MeasureBase.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.__init__", "kind": "function", "doc": "
\n", "signature": "(member_id: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.stat_measures.MeasureBase.member_id": {"fullname": "bioimageio.core.stat_measures.MeasureBase.member_id", "modulename": "bioimageio.core.stat_measures", "qualname": "MeasureBase.member_id", "kind": "variable", "doc": "
\n", "annotation": ": bioimageio.spec.model.v0_5.TensorId"}, "bioimageio.core.stat_measures.SampleMeasureBase": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase", "kind": "class", "doc": "
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.SampleMeasureBase.compute": {"fullname": "bioimageio.core.stat_measures.SampleMeasureBase.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasureBase.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMeasureBase": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase", "kind": "class", "doc": "
\n", "bases": "MeasureBase, abc.ABC"}, "bioimageio.core.stat_measures.DatasetMeasureBase.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetMeasureBase.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasureBase.__init__", "kind": "function", "doc": "
\n", "signature": "(member_id: bioimageio.spec.model.v0_5.TensorId)"}, "bioimageio.core.stat_measures.SampleMean": {"fullname": "bioimageio.core.stat_measures.SampleMean", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean", "kind": "class", "doc": "
The mean value of a single tensor
\n", "bases": "_Mean, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleMean.__init__": {"fullname": "bioimageio.core.stat_measures.SampleMean.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleMean.compute": {"fullname": "bioimageio.core.stat_measures.SampleMean.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMean.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetMean": {"fullname": "bioimageio.core.stat_measures.DatasetMean", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean", "kind": "class", "doc": "
The mean value across multiple samples
\n", "bases": "_Mean, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetMean.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetMean.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMean.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleStd": {"fullname": "bioimageio.core.stat_measures.SampleStd", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd", "kind": "class", "doc": "
The standard deviation of a single tensor
\n", "bases": "_Std, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleStd.__init__": {"fullname": "bioimageio.core.stat_measures.SampleStd.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleStd.compute": {"fullname": "bioimageio.core.stat_measures.SampleStd.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleStd.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetStd": {"fullname": "bioimageio.core.stat_measures.DatasetStd", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd", "kind": "class", "doc": "
The standard deviation across multiple samples
\n", "bases": "_Std, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetStd.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetStd.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetStd.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleVar": {"fullname": "bioimageio.core.stat_measures.SampleVar", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar", "kind": "class", "doc": "
The variance of a single tensor
\n", "bases": "_Var, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleVar.__init__": {"fullname": "bioimageio.core.stat_measures.SampleVar.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleVar.compute": {"fullname": "bioimageio.core.stat_measures.SampleVar.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleVar.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetVar": {"fullname": "bioimageio.core.stat_measures.DatasetVar", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar", "kind": "class", "doc": "
The variance across multiple samples
\n", "bases": "_Var, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetVar.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetVar.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetVar.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleQuantile": {"fullname": "bioimageio.core.stat_measures.SampleQuantile", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile", "kind": "class", "doc": "
The nth percentile of a single tensor
\n", "bases": "_Quantile, SampleMeasureBase"}, "bioimageio.core.stat_measures.SampleQuantile.__init__": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tq: float,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleQuantile.compute": {"fullname": "bioimageio.core.stat_measures.SampleQuantile.compute", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleQuantile.compute", "kind": "function", "doc": "
compute the measure
\n", "signature": "(\tself,\tsample: bioimageio.core.stat_measures.SampleLike) -> Union[float, bioimageio.core.tensor.Tensor]:", "funcdef": "def"}, "bioimageio.core.stat_measures.DatasetPercentile": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile", "kind": "class", "doc": "
The nth percentile across multiple samples
\n", "bases": "_Quantile, DatasetMeasureBase"}, "bioimageio.core.stat_measures.DatasetPercentile.__init__": {"fullname": "bioimageio.core.stat_measures.DatasetPercentile.__init__", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetPercentile.__init__", "kind": "function", "doc": "
\n", "signature": "(\tmember_id: bioimageio.spec.model.v0_5.TensorId,\tq: float,\taxes: Optional[Tuple[bioimageio.spec.model.v0_5.AxisId, ...]] = None)"}, "bioimageio.core.stat_measures.SampleMeasure": {"fullname": "bioimageio.core.stat_measures.SampleMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "SampleMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile]"}, "bioimageio.core.stat_measures.DatasetMeasure": {"fullname": "bioimageio.core.stat_measures.DatasetMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "DatasetMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.stat_measures.Measure": {"fullname": "bioimageio.core.stat_measures.Measure", "modulename": "bioimageio.core.stat_measures", "qualname": "Measure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.stat_measures.Stat": {"fullname": "bioimageio.core.stat_measures.Stat", "modulename": "bioimageio.core.stat_measures", "qualname": "Stat", "kind": "variable", "doc": "
\n", "default_value": "typing.Dict[typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetMean, bioimageio.core.stat_measures.DatasetStd, bioimageio.core.stat_measures.DatasetVar, bioimageio.core.stat_measures.DatasetPercentile], typing.Union[float, bioimageio.core.tensor.Tensor]]"}, "bioimageio.core.stat_measures.MeanMeasure": {"fullname": "bioimageio.core.stat_measures.MeanMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "MeanMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleMean, bioimageio.core.stat_measures.DatasetMean]"}, "bioimageio.core.stat_measures.StdMeasure": {"fullname": "bioimageio.core.stat_measures.StdMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "StdMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleStd, bioimageio.core.stat_measures.DatasetStd]"}, "bioimageio.core.stat_measures.VarMeasure": {"fullname": "bioimageio.core.stat_measures.VarMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "VarMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleVar, bioimageio.core.stat_measures.DatasetVar]"}, "bioimageio.core.stat_measures.PercentileMeasure": {"fullname": "bioimageio.core.stat_measures.PercentileMeasure", "modulename": "bioimageio.core.stat_measures", "qualname": "PercentileMeasure", "kind": "variable", "doc": "
\n", "default_value": "typing.Union[bioimageio.core.stat_measures.SampleQuantile, bioimageio.core.stat_measures.DatasetPercentile]"}, "bioimageio.core.tensor": {"fullname": "bioimageio.core.tensor", "modulename": "bioimageio.core.tensor", "kind": "module", "doc": "
\n"}, "bioimageio.core.tensor.Tensor": {"fullname": "bioimageio.core.tensor.Tensor", "modulename": "bioimageio.core.tensor", "qualname": "Tensor", "kind": "class", "doc": "
A wrapper around an xr.DataArray for better integration with bioimageio.spec\nand improved type annotations.
\n", "bases": "bioimageio.core._magic_tensor_ops.MagicTensorOpsMixin"}, "bioimageio.core.tensor.Tensor.__init__": {"fullname": "bioimageio.core.tensor.Tensor.__init__", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.__init__", "kind": "function", "doc": "
\n", "signature": "(\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\tdims: Sequence[bioimageio.spec.model.v0_5.AxisId])"}, "bioimageio.core.tensor.Tensor.from_xarray": {"fullname": "bioimageio.core.tensor.Tensor.from_xarray", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_xarray", "kind": "function", "doc": "
create a Tensor from an xarray data array
\n\n
note for internal use: this factory method is round-trip save\n    for any Tensor's  data property (an xarray.DataArray).
\n", "signature": "(cls, data_array: xarray.core.dataarray.DataArray) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.from_numpy": {"fullname": "bioimageio.core.tensor.Tensor.from_numpy", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.from_numpy", "kind": "function", "doc": "
create a Tensor from a numpy array
\n\n
Args:\n    array: the nd numpy array\n    axes: A description of the array's axes,\n        if None axes are guessed (which might fail and raise a ValueError.)
\n\n
Raises:\n    ValueError: if axes is None and axes guessing fails.
\n", "signature": "(\tcls,\tarray: numpy.ndarray[typing.Any, numpy.dtype[typing.Any]],\t*,\tdims: Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis, Sequence[Union[Literal['b', 'i', 't', 'c', 'z', 'y', 'x'], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexInputAxis, bioimageio.spec.model.v0_5.TimeInputAxis, bioimageio.spec.model.v0_5.SpaceInputAxis], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[bioimageio.spec.model.v0_5.BatchAxis, bioimageio.spec.model.v0_5.ChannelAxis, bioimageio.spec.model.v0_5.IndexOutputAxis, Annotated[Union[Annotated[bioimageio.spec.model.v0_5.TimeOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.TimeOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)], Annotated[Union[Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxis, Tag(tag='wo_halo')], Annotated[bioimageio.spec.model.v0_5.SpaceOutputAxisWithHalo, Tag(tag='with_halo')]], Discriminator(discriminator=<function _get_halo_axis_discriminator_value>, custom_error_type=None, custom_error_message=None, custom_error_context=None)]], Discriminator(discriminator='type', custom_error_type=None, custom_error_message=None, custom_error_context=None)], bioimageio.core.axis.Axis]], NoneType]) -> bioimageio.core.tensor.Tensor:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.data": {"fullname": "bioimageio.core.tensor.Tensor.data", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.data", "kind": "variable", "doc": "
\n"}, "bioimageio.core.tensor.Tensor.dims": {"fullname": "bioimageio.core.tensor.Tensor.dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dims", "kind": "variable", "doc": "
Tuple of dimension names associated with this tensor.
\n"}, "bioimageio.core.tensor.Tensor.tagged_shape": {"fullname": "bioimageio.core.tensor.Tensor.tagged_shape", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.tagged_shape", "kind": "variable", "doc": "
(alias for sizes) Ordered, immutable mapping from axis ids to lengths.
\n"}, "bioimageio.core.tensor.Tensor.shape_tuple": {"fullname": "bioimageio.core.tensor.Tensor.shape_tuple", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.shape_tuple", "kind": "variable", "doc": "
Tuple of tensor axes lengths
\n"}, "bioimageio.core.tensor.Tensor.size": {"fullname": "bioimageio.core.tensor.Tensor.size", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.size", "kind": "variable", "doc": "
Number of elements in the tensor.
\n\n
Equal to math.prod(tensor.shape), i.e., the product of the tensors\u2019 dimensions.
\n"}, "bioimageio.core.tensor.Tensor.sum": {"fullname": "bioimageio.core.tensor.Tensor.sum", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sum", "kind": "function", "doc": "
Reduce this Tensor's data by applying sum along some dimension(s).
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.ndim": {"fullname": "bioimageio.core.tensor.Tensor.ndim", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.ndim", "kind": "variable", "doc": "
Number of tensor dimensions.
\n"}, "bioimageio.core.tensor.Tensor.dtype": {"fullname": "bioimageio.core.tensor.Tensor.dtype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.dtype", "kind": "variable", "doc": "
\n", "annotation": ": Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64']"}, "bioimageio.core.tensor.Tensor.sizes": {"fullname": "bioimageio.core.tensor.Tensor.sizes", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.sizes", "kind": "variable", "doc": "
Ordered, immutable mapping from axis ids to axis lengths.
\n"}, "bioimageio.core.tensor.Tensor.astype": {"fullname": "bioimageio.core.tensor.Tensor.astype", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.astype", "kind": "function", "doc": "
Return tensor cast to dtype
\n\n
note: if dtype is already satisfied copy if copy
\n", "signature": "(\tself,\tdtype: Literal['bool', 'float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64'],\t*,\tcopy: bool = False):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.clip": {"fullname": "bioimageio.core.tensor.Tensor.clip", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.clip", "kind": "function", "doc": "
Return a tensor whose values are limited to [min, max].\nAt least one of max or min must be given.
\n", "signature": "(self, min: Optional[float] = None, max: Optional[float] = None):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.crop_to": {"fullname": "bioimageio.core.tensor.Tensor.crop_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.crop_to", "kind": "function", "doc": "
crop to match sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.expand_dims": {"fullname": "bioimageio.core.tensor.Tensor.expand_dims", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.expand_dims", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdims: Union[Sequence[bioimageio.spec.model.v0_5.AxisId], Mapping[bioimageio.spec.model.v0_5.AxisId, int]]) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.mean": {"fullname": "bioimageio.core.tensor.Tensor.mean", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.mean", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.std": {"fullname": "bioimageio.core.tensor.Tensor.std", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.std", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.var": {"fullname": "bioimageio.core.tensor.Tensor.var", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.var", "kind": "function", "doc": "
\n", "signature": "(\tself,\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad": {"fullname": "bioimageio.core.tensor.Tensor.pad", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad", "kind": "function", "doc": "
\n", "signature": "(\tself,\tpad_width: Mapping[bioimageio.spec.model.v0_5.AxisId, Union[int, Tuple[int, int], bioimageio.core.common.PadWidth]],\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.pad_to": {"fullname": "bioimageio.core.tensor.Tensor.pad_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.pad_to", "kind": "function", "doc": "
pad tensor to match sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tmode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric') -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.quantile": {"fullname": "bioimageio.core.tensor.Tensor.quantile", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.quantile", "kind": "function", "doc": "
\n", "signature": "(\tself,\tq: Union[float, Sequence[float]],\tdim: Union[bioimageio.spec.model.v0_5.AxisId, Sequence[bioimageio.spec.model.v0_5.AxisId], NoneType] = None) -> Self:", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.resize_to": {"fullname": "bioimageio.core.tensor.Tensor.resize_to", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.resize_to", "kind": "function", "doc": "
return cropped/padded tensor with sizes
\n", "signature": "(\tself,\tsizes: Mapping[bioimageio.spec.model.v0_5.AxisId, int],\t*,\tpad_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tcrop_where: Union[Literal['left', 'right', 'left_and_right'], Mapping[bioimageio.spec.model.v0_5.AxisId, Literal['left', 'right', 'left_and_right']]] = 'left_and_right',\tpad_mode: Literal['edge', 'reflect', 'symmetric'] = 'symmetric'):", "funcdef": "def"}, "bioimageio.core.tensor.Tensor.transpose": {"fullname": "bioimageio.core.tensor.Tensor.transpose", "modulename": "bioimageio.core.tensor", "qualname": "Tensor.transpose", "kind": "function", "doc": "
return a transposed tensor
\n\n
Args:\n    axes: the desired tensor axes
\n", "signature": "(self, axes: Sequence[bioimageio.spec.model.v0_5.AxisId]) -> Self:", "funcdef": "def"}, "bioimageio.core.utils": {"fullname": "bioimageio.core.utils", "modulename": "bioimageio.core.utils", "kind": "module", "doc": "
\n"}, "bioimageio.core.utils.testing": {"fullname": "bioimageio.core.utils.testing", "modulename": "bioimageio.core.utils.testing", "kind": "module", "doc": "
\n"}, "bioimageio.core.utils.testing.test_func": {"fullname": "bioimageio.core.utils.testing.test_func", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func", "kind": "class", "doc": "
Base class for protocol classes.
\n\n
Protocol classes are defined as::
\n\n
class Proto(Protocol):\n    def meth(self) -> int:\n        ...\n
\n\n
Such classes are primarily used with static type checkers that recognize\nstructural subtyping (static duck-typing).
\n\n
For example::
\n\n
class C:\n    def meth(self) -> int:\n        return 0\n\ndef func(x: Proto) -> int:\n    return x.meth()\n\nfunc(C())  # Passes static type check\n
\n\n
See PEP 544 for details. Protocol classes decorated with\n@typing.runtime_checkable act as simple-minded runtime protocols that check\nonly the presence of given attributes, ignoring their type signatures.\nProtocol classes can be generic, they are defined as::
\n\n
class GenProto[T](Protocol):\n    def meth(self) -> T:\n        ...\n
\n", "bases": "typing.Protocol"}, "bioimageio.core.utils.testing.test_func.__init__": {"fullname": "bioimageio.core.utils.testing.test_func.__init__", "modulename": "bioimageio.core.utils.testing", "qualname": "test_func.__init__", "kind": "function", "doc": "
\n", "signature": "(*args, **kwargs)"}, "bioimageio.core.utils.testing.skip_on": {"fullname": "bioimageio.core.utils.testing.skip_on", "modulename": "bioimageio.core.utils.testing", "qualname": "skip_on", "kind": "function", "doc": "
adapted from https://stackoverflow.com/a/63522579
\n", "signature": "(exception: Type[Exception], reason: str):", "funcdef": "def"}, "bioimageio.core.weight_converter": {"fullname": "bioimageio.core.weight_converter", "modulename": "bioimageio.core.weight_converter", "kind": "module", "doc": "
coming soon
\n"}, "bioimageio.core.weight_converter.keras": {"fullname": "bioimageio.core.weight_converter.keras", "modulename": "bioimageio.core.weight_converter.keras", "kind": "module", "doc": "
\n"}, "bioimageio.core.weight_converter.torch": {"fullname": "bioimageio.core.weight_converter.torch", "modulename": "bioimageio.core.weight_converter.torch", "kind": "module", "doc": "
\n"}}, "docInfo": {"bioimageio.core": {"qualname": 0, "fullname": 2, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 997}, "bioimageio.core.test_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1282, "bases": 0, "doc": 16}, "bioimageio.core.load_resource": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1159, "bases": 0, "doc": 112}, "bioimageio.core.load_model": {"qualname": 2, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 1159, "bases": 0, "doc": 112}, "bioimageio.core.axis": {"qualname": 0, "fullname": 3, "annotation": 0, "default_value": 0, "signature": 0, "bases": 0, "doc": 3}, "bioimageio.core.axis.AxisId": {"qualname": 1, "fullname": 4, "annotation": 0, "default_value": 0, "signature": 0, "bases": 5, "doc": 72}, "bioimageio.core.axis.AxisId.root_model": {"qualname": 3, "fullname": 6, "annotation": 5, "default_value": 17, "signature": 0, "bases": 0, "doc": 10}, 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     // mirrored in build-search-index.js (part 1)
     // Also split on html tags. this is a cheap heuristic, but good enough.