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chore: bug fixes #3065
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chore: bug fixes #3065
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/pool.py 2024-08-17 21:38:03.174815+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/pool.py 2024-08-17 21:38:24.979987+00:00
@@ -28,11 +28,11 @@
padding: Union[int, Sequence[int]] = 0,
ceil_mode: bool = False,
count_include_pad: bool = True,
divisor_override: Optional[int] = None,
) -> TRTTensor:
-
+
padding_mode = trt.PaddingMode.EXPLICIT_ROUND_DOWN
if ceil_mode:
padding_mode = trt.PaddingMode.EXPLICIT_ROUND_UP
if divisor_override is not None:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-17 21:38:03.178815+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-17 21:38:25.214966+00:00
@@ -22,11 +22,11 @@
# Extract arguments from full_like
input_tensor = node.args[0]
fill_value = node.args[1]
shape = list(input_tensor.meta["tensor_meta"].shape)
-
+
new_kwargs = {}
for key, val in node.kwargs.items():
if key != "memory_format":
new_kwargs[key] = val
# Replace full_like with full, using the shape as a list
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-17 21:38:03.174815+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-17 21:38:27.095553+00:00
@@ -2699,11 +2699,11 @@
dilation = args_bounds_check(pool_node.args, 4, 1)
ceil_mode = args_bounds_check(pool_node.args, 5, False)
if not isinstance(dilation, (list, tuple)):
dilation = (dilation,)
-
+
for dil in dilation:
if dil != 1:
_LOGGER.debug("Currently we don't support dilation > 1 at any dimension.")
return False
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/full.py 2024-08-18 03:35:59.991813+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/full.py 2024-08-18 03:36:20.489931+00:00
@@ -20,11 +20,11 @@
target: Union[Target, str],
source_ir: Optional[SourceIR],
name: str,
shape: Union[List[int], TRTTensor],
fill_value: Union[int, float, bool],
- dtype: Union[torch.dtype, trt.DataType]
+ dtype: Union[torch.dtype, trt.DataType],
) -> TRTTensor:
output_dtype = _enums.dtype._from(dtype)
if isinstance(shape, List):
# in static shape scenario, shape is a list of int
if all(isinstance(dim, int) for dim in shape):
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-18 03:35:59.995813+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-18 03:36:21.060814+00:00
@@ -34,11 +34,11 @@
input_dtype = input_tensor.meta["tensor_meta"].dtype
input_device = input_tensor.meta["tensor_meta"].device
shape = list(input_tensor.meta["tensor_meta"].shape)
- # There's no memory format argument for torch.full.
+ # There's no memory format argument for torch.full.
# Set the input_device and dtype correspondingly.
new_kwargs = {}
for key, val in node.kwargs.items():
if key != "memory_format":
new_kwargs[key] = val
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-18 03:35:59.991813+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-18 03:36:22.843055+00:00
@@ -2702,11 +2702,11 @@
for dil in dilation:
if dil != 1:
_LOGGER.debug("Currently we don't support dilation > 1 at any dimension.")
return False
-
+
return True
# Note: MaxPool1d uses max_pool2d as it converts to 2D first.
@dynamo_tensorrt_converter(
@@ -3856,7 +3856,7 @@
target,
SourceIR.ATEN,
name,
shape=args[0],
fill_value=args[1],
- dtype=kwargs["dtype"]
- )
+ dtype=kwargs["dtype"],
+ )
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/full.py 2024-08-18 06:00:03.147977+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/impl/full.py 2024-08-18 06:00:23.686044+00:00
@@ -20,11 +20,11 @@
target: Union[Target, str],
source_ir: Optional[SourceIR],
name: str,
shape: Union[List[int], TRTTensor],
fill_value: Union[int, float, bool],
- dtype: Union[torch.dtype, trt.DataType]
+ dtype: Union[torch.dtype, trt.DataType],
) -> TRTTensor:
output_dtype = _enums.dtype._from(dtype)
if isinstance(shape, List):
# in static shape scenario, shape is a list of int
if all(isinstance(dim, int) for dim in shape):
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-18 06:00:03.151977+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/lowering/passes/replace_full_like_with_full.py 2024-08-18 06:00:24.276030+00:00
@@ -34,11 +34,11 @@
input_dtype = input_tensor.meta["tensor_meta"].dtype
input_device = input_tensor.meta["tensor_meta"].device
shape = list(input_tensor.meta["tensor_meta"].shape)
- # There's no memory format argument for torch.full.
+ # There's no memory format argument for torch.full.
# Set the input_device and dtype correspondingly.
new_kwargs = {}
for key, val in node.kwargs.items():
if key != "memory_format":
new_kwargs[key] = val
--- /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-18 06:00:03.147977+00:00
+++ /home/runner/work/TensorRT/TensorRT/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py 2024-08-18 06:00:25.976231+00:00
@@ -2694,11 +2694,11 @@
for dil in dilation:
if dil != 1:
_LOGGER.debug("Currently we don't support dilation > 1 at any dimension.")
return False
-
+
return True
# Note: MaxPool1d uses max_pool2d as it converts to 2D first.
@dynamo_tensorrt_converter(
@@ -3848,7 +3848,7 @@
target,
SourceIR.ATEN,
name,
shape=args[0],
fill_value=args[1],
- dtype=kwargs["dtype"]
- )
+ dtype=kwargs["dtype"],
+ )
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-18 06:00:03.175977+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-18 06:00:28.087506+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-21 00:24:16.805992+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-21 00:24:50.723758+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-21 00:30:09.776031+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-21 00:30:45.350177+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-23 03:05:32.567575+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-23 03:05:56.052071+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-28 21:23:05.146803+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-28 21:23:31.914698+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-28 23:35:05.049467+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-28 23:35:28.258183+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-29 17:37:32.829319+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-29 17:37:56.926341+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-29 23:56:13.538224+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-08-29 23:56:39.163776+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
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There are some changes that do not conform to Python style guidelines:
--- /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-09-10 18:44:52.655743+00:00
+++ /home/runner/work/TensorRT/TensorRT/tests/py/dynamo/conversion/test_pool_aten.py 2024-09-10 18:45:27.216624+00:00
@@ -73,11 +73,13 @@
count_include_pad,
divisor_override,
)
inputs = [torch.randn(1, 3, 32, 32)]
- self.run_test(TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True)
+ self.run_test(
+ TestModule(), inputs, rtol=5e-03, atol=5e-03, use_dynamo_tracer=True
+ )
@parameterized.expand(
[
(3, 1, 0),
(3, 1, 1),
@@ -181,11 +183,11 @@
(3, 3, 3, 3),
torch.float,
(3, 3),
(1, 1),
(1, 1),
- True
+ True,
),
]
)
def test_dynamic_shape_pool2d(
self,
Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.
Checklist: