Merge master into v4 (#11034)

* Add "Aim-spaCy" to spaCy Universe (#10943)

* Add Aim-spaCy to spaCy universe

* Update Aim thumbnail

* Fix author links

Co-authored-by: Paul O'Leary McCann <[email protected]>

* Auto-format code with black (#10945)

Co-authored-by: explosion-bot <[email protected]>

* precomputable_biaffine: avoid concatenation (#10911)

The `forward` of `precomputable_biaffine` performs matrix multiplication
and then `vstack`s the result with padding. This creates a temporary
array used for the output of matrix concatenation.

This change avoids the temporary by pre-allocating an array that is
large enough for the output of matrix multiplication plus padding and
fills the array in-place.

This gave me a small speedup (a bit over 100 WPS) on de_core_news_lg on
M1 Max (after changing thinc-apple-ops to support in-place gemm as BLIS
does).

* Add failing test: `test_matcher_extension_in_set_predicate` (#10948)

* vectors: remove use of float as row number (#10955)

The float -1 was returned rather than the integer -1 as the row for
unknown keys. This doesn't introduce a realy bug, since such floats
cast (without issues) to int in the conversion to NumPy arrays. Still,
it's nice to to do the correct thing :).

* Update for CBlas changes in Thinc 8.1.0.dev2 (#10970)

* Workaround for Typer optional default values with Python calls (#10788)

* Workaround for Typer optional default values with Python calls: added test and workaround.

* @rmitsch Workaround for Typer optional default values with Python calls: reverting some black formatting changes.

Co-authored-by: Sofie Van Landeghem <[email protected]>

* @rmitsch Workaround for Typer optional default values with Python calls: removing return type hint.

Co-authored-by: Sofie Van Landeghem <[email protected]>

* Workaround for Typer optional default values with Python calls: fixed imports, added GitHub issue marker.

* Workaround for Typer optional default values with Python calls: removed forcing of default values for optional arguments in init_config_cli(). Added default values for init_config(). Synchronized default values for init_config_cli() and init_config().

* Workaround for Typer optional default values with Python calls: removed unused import.

* Workaround for Typer optional default values with Python calls: fixed usage of optimize in init_config_cli().

* Workaround for Typer optional default values with Pythhon calls: remove output_file from InitDefaultValues.

* Workaround for Typer optional default values with Python calls: rename class for default init values.

* Workaround for Typer optional default values with Python calls: remove newline.

* remove introduced newlines

* Remove test_init_config_from_python_without_optional_args().

* remove leftover import

* reformat import

* remove duplicate

Co-authored-by: Sofie Van Landeghem <[email protected]>

* Made _initialize_X() methods private. (#10978)

* Auto-format code with black (#10977)

Co-authored-by: explosion-bot <[email protected]>

* account for NER labels with a hyphen in the name (#10960)

* account for NER labels with a hyphen in the name

* cleanup

* fix docstring

* add return type to helper method

* shorter method and few more occurrences

* user helper method across repo

* fix circular import

* partial revert to avoid circular import

* `enable` argument for spacy.load() (#10784)

* Enable flag on spacy.load: foundation for include, enable arguments.

* Enable flag on spacy.load: fixed tests.

* Enable flag on spacy.load: switched from pretrained model to empty model with added pipes for tests.

* Enable flag on spacy.load: switched to more consistent error on misspecification of component activity. Test refactoring. Added  to default config.

* Enable flag on spacy.load: added support for fields not in pipeline.

* Enable flag on spacy.load: removed serialization fields from supported fields.

* Enable flag on spacy.load: removed 'enable' from config again.

* Enable flag on spacy.load: relaxed checks in _resolve_component_activation_status() to allow non-standard pipes.

* Enable flag on spacy.load: fixed relaxed checks for _resolve_component_activation_status() to allow non-standard pipes. Extended tests.

* Enable flag on spacy.load: comments w.r.t. resolution workarounds.

* Enable flag on spacy.load: remove include fields. Update website docs.

* Enable flag on spacy.load: updates w.r.t. changes in master.

* Implement Doc.from_json(): update docstrings.

Co-authored-by: Adriane Boyd <[email protected]>

* Implement Doc.from_json(): remove newline.

Co-authored-by: Adriane Boyd <[email protected]>

* Implement Doc.from_json(): change error message for E1038.

Co-authored-by: Adriane Boyd <[email protected]>

* Enable flag on spacy.load: wrapped docstring for _resolve_component_status() at 80 chars.

* Enable flag on spacy.load: changed exmples for enable flag.

* Remove newline.

Co-authored-by: Sofie Van Landeghem <[email protected]>

* Fix docstring for Language._resolve_component_status().

* Rename E1038 to E1042.

Co-authored-by: Adriane Boyd <[email protected]>
Co-authored-by: Sofie Van Landeghem <[email protected]>

* add counts to verbose list of NER labels (#10957)

* Update linguistic-features.md (#10993)

Change link for downloading fasttext word vectors

* Use thinc-apple-ops>=0.1.0.dev0 with `apple` extras (#10904)

* Use thinc-apple-ops>=0.1.0.dev0 with `apple` extras

Also test with thinc-apple-ops that is at least 0.1.0.dev0.

* Check thinc-apple-ops on macOS with Python 3.10

Co-authored-by: Adriane Boyd <[email protected]>

* Use `pip install --pre` for installing thinc-apple-ops in CI

Co-authored-by: Adriane Boyd <[email protected]>

Co-authored-by: Gor Arakelyan <[email protected]>
Co-authored-by: Paul O'Leary McCann <[email protected]>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: explosion-bot <[email protected]>
Co-authored-by: Madeesh Kannan <[email protected]>
Co-authored-by: Raphael Mitsch <[email protected]>
Co-authored-by: Sofie Van Landeghem <[email protected]>
Co-authored-by: Adriane Boyd <[email protected]>
Co-authored-by: Victoria <[email protected]>

.github/azure-steps.yml

@@ -111,7 +111,7 @@ steps:
     condition: eq(variables['python_version'], '3.8')
 
   - script: |
-      ${{ parameters.prefix }} python -m pip install thinc-apple-ops
+      ${{ parameters.prefix }} python -m pip install --pre thinc-apple-ops
       ${{ parameters.prefix }} python -m pytest --pyargs spacy
     displayName: "Run CPU tests with thinc-apple-ops"
-    condition: and(startsWith(variables['imageName'], 'macos'), eq(variables['python.version'], '3.9'))
+    condition: and(startsWith(variables['imageName'], 'macos'), eq(variables['python.version'], '3.10'))

pyproject.toml

@@ -5,7 +5,7 @@ requires = [
     "cymem>=2.0.2,<2.1.0",
     "preshed>=3.0.2,<3.1.0",
     "murmurhash>=0.28.0,<1.1.0",
-    "thinc>=8.1.0.dev0,<8.2.0",
+    "thinc>=8.1.0.dev2,<8.2.0",
     "pathy",
     "numpy>=1.15.0",
 ]

requirements.txt

@@ -3,7 +3,7 @@ spacy-legacy>=3.0.9,<3.1.0
 spacy-loggers>=1.0.0,<2.0.0
 cymem>=2.0.2,<2.1.0
 preshed>=3.0.2,<3.1.0
-thinc>=8.1.0.dev0,<8.2.0
+thinc>=8.1.0.dev2,<8.2.0
 ml_datasets>=0.2.0,<0.3.0
 murmurhash>=0.28.0,<1.1.0
 wasabi>=0.9.1,<1.1.0

setup.cfg

@@ -38,15 +38,15 @@ setup_requires =
     cymem>=2.0.2,<2.1.0
     preshed>=3.0.2,<3.1.0
     murmurhash>=0.28.0,<1.1.0
-    thinc>=8.1.0.dev0,<8.2.0
+    thinc>=8.1.0.dev2,<8.2.0
 install_requires =
     # Our libraries
     spacy-legacy>=3.0.9,<3.1.0
     spacy-loggers>=1.0.0,<2.0.0
     murmurhash>=0.28.0,<1.1.0
     cymem>=2.0.2,<2.1.0
     preshed>=3.0.2,<3.1.0
-    thinc>=8.1.0.dev0,<8.2.0
+    thinc>=8.1.0.dev2,<8.2.0
     wasabi>=0.9.1,<1.1.0
     srsly>=2.4.3,<3.0.0
     catalogue>=2.0.6,<2.1.0
@@ -104,7 +104,7 @@ cuda114 =
 cuda115 =
     cupy-cuda115>=5.0.0b4,<11.0.0
 apple =
-    thinc-apple-ops>=0.0.4,<1.0.0
+    thinc-apple-ops>=0.1.0.dev0,<1.0.0
 # Language tokenizers with external dependencies
 ja =
     sudachipy>=0.5.2,!=0.6.1

spacy/__init__.py

@@ -32,6 +32,7 @@ def load(
     *,
     vocab: Union[Vocab, bool] = True,
     disable: Iterable[str] = util.SimpleFrozenList(),
+    enable: Iterable[str] = util.SimpleFrozenList(),
     exclude: Iterable[str] = util.SimpleFrozenList(),
     config: Union[Dict[str, Any], Config] = util.SimpleFrozenDict(),
 ) -> Language:
@@ -42,14 +43,21 @@ def load(
     disable (Iterable[str]): Names of pipeline components to disable. Disabled
         pipes will be loaded but they won't be run unless you explicitly
         enable them by calling nlp.enable_pipe.
+    enable (Iterable[str]): Names of pipeline components to enable. All other
+        pipes will be disabled (but can be enabled later using nlp.enable_pipe).
     exclude (Iterable[str]): Names of pipeline components to exclude. Excluded
         components won't be loaded.
     config (Dict[str, Any] / Config): Config overrides as nested dict or dict
         keyed by section values in dot notation.
     RETURNS (Language): The loaded nlp object.
     """
     return util.load_model(
-        name, vocab=vocab, disable=disable, exclude=exclude, config=config
+        name,
+        vocab=vocab,
+        disable=disable,
+        enable=enable,
+        exclude=exclude,
+        config=config,
     )
 
 

spacy/cli/debug_data.py

@@ -10,7 +10,7 @@
 
 from ._util import app, Arg, Opt, show_validation_error, parse_config_overrides
 from ._util import import_code, debug_cli
-from ..training import Example
+from ..training import Example, remove_bilu_prefix
 from ..training.initialize import get_sourced_components
 from ..schemas import ConfigSchemaTraining
 from ..pipeline._parser_internals import nonproj
@@ -361,7 +361,7 @@ def debug_data(
             if label != "-"
         ]
         labels_with_counts = _format_labels(labels_with_counts, counts=True)
-        msg.text(f"Labels in train data: {_format_labels(labels)}", show=verbose)
+        msg.text(f"Labels in train data: {labels_with_counts}", show=verbose)
         missing_labels = model_labels - labels
         if missing_labels:
             msg.warn(
@@ -758,9 +758,9 @@ def _compile_gold(
                     # "Illegal" whitespace entity
                     data["ws_ents"] += 1
                 if label.startswith(("B-", "U-")):
-                    combined_label = label.split("-")[1]
+                    combined_label = remove_bilu_prefix(label)
                     data["ner"][combined_label] += 1
-                if sent_starts[i] == True and label.startswith(("I-", "L-")):
+                if sent_starts[i] and label.startswith(("I-", "L-")):
                     data["boundary_cross_ents"] += 1
                 elif label == "-":
                     data["ner"]["-"] += 1
@@ -908,7 +908,7 @@ def _get_examples_without_label(
     for eg in data:
         if component == "ner":
             labels = [
-                label.split("-")[1]
+                remove_bilu_prefix(label)
                 for label in eg.get_aligned_ner()
                 if label not in ("O", "-", None)
             ]

spacy/cli/init_config.py

@@ -10,6 +10,7 @@
 from .. import util
 from ..language import DEFAULT_CONFIG_PRETRAIN_PATH
 from ..schemas import RecommendationSchema
+from ..util import SimpleFrozenList
 from ._util import init_cli, Arg, Opt, show_validation_error, COMMAND
 from ._util import string_to_list, import_code
 
@@ -24,16 +25,30 @@ class Optimizations(str, Enum):
     accuracy = "accuracy"
 
 
+class InitValues:
+    """
+    Default values for initialization. Dedicated class to allow synchronized default values for init_config_cli() and
+    init_config(), i.e. initialization calls via CLI respectively Python.
+    """
+
+    lang = "en"
+    pipeline = SimpleFrozenList(["tagger", "parser", "ner"])
+    optimize = Optimizations.efficiency
+    gpu = False
+    pretraining = False
+    force_overwrite = False
+
+
 @init_cli.command("config")
 def init_config_cli(
     # fmt: off
     output_file: Path = Arg(..., help="File to save the config to or - for stdout (will only output config and no additional logging info)", allow_dash=True),
-    lang: str = Opt("en", "--lang", "-l", help="Two-letter code of the language to use"),
-    pipeline: str = Opt("tagger,parser,ner", "--pipeline", "-p", help="Comma-separated names of trainable pipeline components to include (without 'tok2vec' or 'transformer')"),
-    optimize: Optimizations = Opt(Optimizations.efficiency.value, "--optimize", "-o", help="Whether to optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger and slower model). This will impact the choice of architecture, pretrained weights and related hyperparameters."),
-    gpu: bool = Opt(False, "--gpu", "-G", help="Whether the model can run on GPU. This will impact the choice of architecture, pretrained weights and related hyperparameters."),
-    pretraining: bool = Opt(False, "--pretraining", "-pt", help="Include config for pretraining (with 'spacy pretrain')"),
-    force_overwrite: bool = Opt(False, "--force", "-F", help="Force overwriting the output file"),
+    lang: str = Opt(InitValues.lang, "--lang", "-l", help="Two-letter code of the language to use"),
+    pipeline: str = Opt(",".join(InitValues.pipeline), "--pipeline", "-p", help="Comma-separated names of trainable pipeline components to include (without 'tok2vec' or 'transformer')"),
+    optimize: Optimizations = Opt(InitValues.optimize, "--optimize", "-o", help="Whether to optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger and slower model). This will impact the choice of architecture, pretrained weights and related hyperparameters."),
+    gpu: bool = Opt(InitValues.gpu, "--gpu", "-G", help="Whether the model can run on GPU. This will impact the choice of architecture, pretrained weights and related hyperparameters."),
+    pretraining: bool = Opt(InitValues.pretraining, "--pretraining", "-pt", help="Include config for pretraining (with 'spacy pretrain')"),
+    force_overwrite: bool = Opt(InitValues.force_overwrite, "--force", "-F", help="Force overwriting the output file"),
     # fmt: on
 ):
     """
@@ -133,11 +148,11 @@ def fill_config(
 
 def init_config(
     *,
-    lang: str,
-    pipeline: List[str],
-    optimize: str,
-    gpu: bool,
-    pretraining: bool = False,
+    lang: str = InitValues.lang,
+    pipeline: List[str] = InitValues.pipeline,
+    optimize: str = InitValues.optimize,
+    gpu: bool = InitValues.gpu,
+    pretraining: bool = InitValues.pretraining,
     silent: bool = True,
 ) -> Config:
     msg = Printer(no_print=silent)

spacy/errors.py

@@ -932,6 +932,8 @@ class Errors(metaclass=ErrorsWithCodes):
     E1040 = ("Doc.from_json requires all tokens to have the same attributes. "
              "Some tokens do not contain annotation for: {partial_attrs}")
     E1041 = ("Expected a string, Doc, or bytes as input, but got: {type}")
+    E1042 = ("Function was called with `{arg1}`={arg1_values} and "
+             "`{arg2}`={arg2_values} but these arguments are conflicting.")
 
 
 # Deprecated model shortcuts, only used in errors and warnings

spacy/kb.pyx

@@ -93,14 +93,14 @@ cdef class KnowledgeBase:
         self.vocab = vocab
         self._create_empty_vectors(dummy_hash=self.vocab.strings[""])
 
-    def initialize_entities(self, int64_t nr_entities):
+    def _initialize_entities(self, int64_t nr_entities):
         self._entry_index = PreshMap(nr_entities + 1)
         self._entries = entry_vec(nr_entities + 1)
 
-    def initialize_vectors(self, int64_t nr_entities):
+    def _initialize_vectors(self, int64_t nr_entities):
         self._vectors_table = float_matrix(nr_entities + 1)
 
-    def initialize_aliases(self, int64_t nr_aliases):
+    def _initialize_aliases(self, int64_t nr_aliases):
         self._alias_index = PreshMap(nr_aliases + 1)
         self._aliases_table = alias_vec(nr_aliases + 1)
 
@@ -155,8 +155,8 @@ cdef class KnowledgeBase:
             raise ValueError(Errors.E140)
 
         nr_entities = len(set(entity_list))
-        self.initialize_entities(nr_entities)
-        self.initialize_vectors(nr_entities)
+        self._initialize_entities(nr_entities)
+        self._initialize_vectors(nr_entities)
 
         i = 0
         cdef KBEntryC entry
@@ -388,9 +388,9 @@ cdef class KnowledgeBase:
             nr_entities = header[0]
             nr_aliases = header[1]
             entity_vector_length = header[2]
-            self.initialize_entities(nr_entities)
-            self.initialize_vectors(nr_entities)
-            self.initialize_aliases(nr_aliases)
+            self._initialize_entities(nr_entities)
+            self._initialize_vectors(nr_entities)
+            self._initialize_aliases(nr_aliases)
             self.entity_vector_length = entity_vector_length
 
         def deserialize_vectors(b):
@@ -512,8 +512,8 @@ cdef class KnowledgeBase:
         cdef int64_t entity_vector_length
         reader.read_header(&nr_entities, &entity_vector_length)
 
-        self.initialize_entities(nr_entities)
-        self.initialize_vectors(nr_entities)
+        self._initialize_entities(nr_entities)
+        self._initialize_vectors(nr_entities)
         self.entity_vector_length = entity_vector_length
 
         # STEP 1: load entity vectors
@@ -552,7 +552,7 @@ cdef class KnowledgeBase:
         # STEP 3: load aliases
         cdef int64_t nr_aliases
         reader.read_alias_length(&nr_aliases)
-        self.initialize_aliases(nr_aliases)
+        self._initialize_aliases(nr_aliases)
 
         cdef int64_t nr_candidates
         cdef vector[int64_t] entry_indices

spacy/language.py

@@ -1,4 +1,4 @@
-from typing import Iterator, Optional, Any, Dict, Callable, Iterable
+from typing import Iterator, Optional, Any, Dict, Callable, Iterable, Collection
 from typing import Union, Tuple, List, Set, Pattern, Sequence
 from typing import NoReturn, TYPE_CHECKING, TypeVar, cast, overload
 
@@ -1694,6 +1694,7 @@ def from_config(
         *,
         vocab: Union[Vocab, bool] = True,
         disable: Iterable[str] = SimpleFrozenList(),
+        enable: Iterable[str] = SimpleFrozenList(),
         exclude: Iterable[str] = SimpleFrozenList(),
         meta: Dict[str, Any] = SimpleFrozenDict(),
         auto_fill: bool = True,
@@ -1708,6 +1709,8 @@ def from_config(
         disable (Iterable[str]): Names of pipeline components to disable.
             Disabled pipes will be loaded but they won't be run unless you
             explicitly enable them by calling nlp.enable_pipe.
+        enable (Iterable[str]): Names of pipeline components to enable. All other
+            pipes will be disabled (and can be enabled using `nlp.enable_pipe`).
         exclude (Iterable[str]): Names of pipeline components to exclude.
             Excluded components won't be loaded.
         meta (Dict[str, Any]): Meta overrides for nlp.meta.
@@ -1861,8 +1864,15 @@ def from_config(
         # Restore the original vocab after sourcing if necessary
         if vocab_b is not None:
             nlp.vocab.from_bytes(vocab_b)
-        disabled_pipes = [*config["nlp"]["disabled"], *disable]
+
+        # Resolve disabled/enabled settings.
+        disabled_pipes = cls._resolve_component_status(
+            [*config["nlp"]["disabled"], *disable],
+            [*config["nlp"].get("enabled", []), *enable],
+            config["nlp"]["pipeline"],
+        )
         nlp._disabled = set(p for p in disabled_pipes if p not in exclude)
+
         nlp.batch_size = config["nlp"]["batch_size"]
         nlp.config = filled if auto_fill else config
         if after_pipeline_creation is not None:
@@ -2014,6 +2024,42 @@ def to_disk(
         serializers["vocab"] = lambda p: self.vocab.to_disk(p, exclude=exclude)
         util.to_disk(path, serializers, exclude)
 
+    @staticmethod
+    def _resolve_component_status(
+        disable: Iterable[str], enable: Iterable[str], pipe_names: Collection[str]
+    ) -> Tuple[str, ...]:
+        """Derives whether (1) `disable` and `enable` values are consistent and (2)
+        resolves those to a single set of disabled components. Raises an error in
+        case of inconsistency.
+
+        disable (Iterable[str]): Names of components or serialization fields to disable.
+        enable (Iterable[str]): Names of pipeline components to enable.
+        pipe_names (Iterable[str]): Names of all pipeline components.
+
+        RETURNS (Tuple[str, ...]): Names of components to exclude from pipeline w.r.t.
+                                   specified includes and excludes.
+        """
+
+        if disable is not None and isinstance(disable, str):
+            disable = [disable]
+        to_disable = disable
+
+        if enable:
+            to_disable = [
+                pipe_name for pipe_name in pipe_names if pipe_name not in enable
+            ]
+            if disable and disable != to_disable:
+                raise ValueError(
+                    Errors.E1042.format(
+                        arg1="enable",
+                        arg2="disable",
+                        arg1_values=enable,
+                        arg2_values=disable,
+                    )
+                )
+
+        return tuple(to_disable)
+
     def from_disk(
         self,
         path: Union[str, Path],

spacy/ml/_precomputable_affine.py

@@ -22,9 +22,11 @@ def forward(model, X, is_train):
     nP = model.get_dim("nP")
     nI = model.get_dim("nI")
     W = model.get_param("W")
-    Yf = model.ops.gemm(X, W.reshape((nF * nO * nP, nI)), trans2=True)
+    # Preallocate array for layer output, including padding.
+    Yf = model.ops.alloc2f(X.shape[0] + 1, nF * nO * nP, zeros=False)
+    model.ops.gemm(X, W.reshape((nF * nO * nP, nI)), trans2=True, out=Yf[1:])
     Yf = Yf.reshape((Yf.shape[0], nF, nO, nP))
-    Yf = model.ops.xp.vstack((model.get_param("pad"), Yf))
+    Yf[0] = model.get_param("pad")
 
     def backward(dY_ids):
         # This backprop is particularly tricky, because we get back a different

spacy/ml/parser_model.pyx

@@ -4,6 +4,7 @@ from libc.math cimport exp
 from libc.string cimport memset, memcpy
 from libc.stdlib cimport calloc, free, realloc
 from thinc.backends.linalg cimport Vec, VecVec
+from thinc.backends.cblas cimport saxpy, sgemm
 
 import numpy
 import numpy.random
@@ -112,7 +113,7 @@ cdef void predict_states(CBlas cblas, ActivationsC* A, StateC** states,
         memcpy(A.scores, A.hiddens, n.states * n.classes * sizeof(float))
     else:
         # Compute hidden-to-output
-        cblas.sgemm()(False, True, n.states, n.classes, n.hiddens,
+        sgemm(cblas)(False, True, n.states, n.classes, n.hiddens,
             1.0, <const float *>A.hiddens, n.hiddens,
             <const float *>W.hidden_weights, n.hiddens,
             0.0, A.scores, n.classes)
@@ -147,7 +148,7 @@ cdef void sum_state_features(CBlas cblas, float* output,
             else:
                 idx = token_ids[f] * id_stride + f*O
                 feature = &cached[idx]
-            cblas.saxpy()(O, one, <const float*>feature, 1, &output[b*O], 1)
+            saxpy(cblas)(O, one, <const float*>feature, 1, &output[b*O], 1)
         token_ids += F
 
 

spacy/pipeline/_parser_internals/arc_eager.pyx

@@ -10,6 +10,7 @@ from ...strings cimport hash_string
 from ...structs cimport TokenC
 from ...tokens.doc cimport Doc, set_children_from_heads
 from ...tokens.token cimport MISSING_DEP
+from ...training import split_bilu_label
 from ...training.example cimport Example
 from .stateclass cimport StateClass
 from ._state cimport StateC, ArcC
@@ -687,7 +688,7 @@ cdef class ArcEager(TransitionSystem):
             return self.c[name_or_id]
         name = name_or_id
         if '-' in name:
-            move_str, label_str = name.split('-', 1)
+            move_str, label_str = split_bilu_label(name)
             label = self.strings[label_str]
         else:
             move_str = name