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Enabled torch compile functional tests for boxes, masks and video
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Annotated exceptions with encountered errors
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@vfdev-5
vfdev-5 committed Nov 8, 2023
1 parent 045465e commit 8410021
Showing 1 changed file with 102 additions and 8 deletions.
110 changes: 102 additions & 8 deletions test/test_transforms_v2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -189,7 +189,7 @@ def _check_functional_scripted_smoke(functional, input, *args, **kwargs):

def _check_functional_torch_compile_smoke(functional, input, *args, **kwargs):
"""Checks if the functional can be torch compiled and the compiled version can be called without error."""
if not isinstance(input, tv_tensors.Image):
if not isinstance(input, torch.Tensor):
return

functional_compiled = torch.compile(functional)
Expand Down Expand Up @@ -1162,7 +1162,22 @@ def test_kernel_video(self):
[make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
)
def test_functional(self, make_input):
check_functional(F.affine, make_input(), **self._MINIMAL_AFFINE_KWARGS)
# TODO: Remove this when fixed
# /usr/local/lib/python3.10/dist-packages/torch/_dynamo/symbolic_convert.py:1573: in UNPACK_SEQUENCE
# assert len(val) == inst.argval
# E AssertionError:
# E
# E from user code:
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 392, in resume_in_affine
# E return kernel(
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 692, in affine_image
# E return _apply_grid_transform(image, grid, interpolation.value, fill=fill)
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 556, in _apply_grid_transform
# E num_channels, input_height, input_width = input_shape[-3:]
check_torch_compile_smoke = False if make_input in (make_bounding_boxes, make_segmentation_mask) else True
check_functional(
F.affine, make_input(), **self._MINIMAL_AFFINE_KWARGS, check_torch_compile_smoke=check_torch_compile_smoke
)

@pytest.mark.parametrize(
("kernel", "input_type"),
Expand Down Expand Up @@ -1586,7 +1601,12 @@ def test_kernel_video(self):
[make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
)
def test_functional(self, make_input):
check_functional(F.rotate, make_input(), **self._MINIMAL_AFFINE_KWARGS)
# TODO: Remove this when fixed
# Error is the same as for TestAffine
check_torch_compile_smoke = False if make_input in (make_bounding_boxes, make_segmentation_mask) else True
check_functional(
F.rotate, make_input(), **self._MINIMAL_AFFINE_KWARGS, check_torch_compile_smoke=check_torch_compile_smoke
)

@pytest.mark.parametrize(
("kernel", "input_type"),
Expand Down Expand Up @@ -2651,8 +2671,38 @@ def test_kernel_video(self):
[make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
)
def test_functional(self, make_input):
# TODO: Remove this when fixed
# - TestElastic.test_functional[make_bounding_boxes]:
# /usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:410: in _fn
# return fn(*args, **kwargs)
# torchvision/transforms/v2/functional/_geometry.py:1705: in elastic
# kernel = _get_kernel(elastic, type(inpt))
# torchvision/transforms/v2/functional/_geometry.py:1706: in resume_in_elastic
# return kernel(inpt, displacement=displacement, interpolation=interpolation, fill=fill)
# torchvision/transforms/v2/functional/_geometry.py:1741: in elastic_image
# raise ValueError(f"Argument displacement shape should be {expected_shape}, but given {displacement.shape}")
# torchvision/transforms/v2/functional/_geometry.py:1741: in resume_in_elastic_image
# raise ValueError(f"Argument displacement shape should be {expected_shape}, but given {displacement.shape}")
# E ValueError: Argument displacement shape should be (1, 1, 4, 2), but given torch.Size([1, 17, 11, 2])
#
# - TestElastic.test_functional[make_segmentation_mask]:
# E AssertionError:
# E
# E from user code:
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 1706, in resume_in_elastic
# E return kernel(inpt, displacement=displacement, interpolation=interpolation, fill=fill)
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 1746, in elastic_image
# E output = _apply_grid_transform(image, grid, interpolation.value, fill=fill)
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 556, in _apply_grid_transform
# E num_channels, input_height, input_width = input_shape[-3:]
check_torch_compile_smoke = False if make_input in (make_bounding_boxes, make_segmentation_mask) else True
input = make_input()
check_functional(F.elastic, input, displacement=self._make_displacement(input))
check_functional(
F.elastic,
input,
displacement=self._make_displacement(input),
check_torch_compile_smoke=check_torch_compile_smoke,
)

@pytest.mark.parametrize(
("kernel", "input_type"),
Expand Down Expand Up @@ -2765,7 +2815,23 @@ def test_kernel_video(self):
[make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
)
def test_functional(self, make_input):
check_functional(F.crop, make_input(self.INPUT_SIZE), **self.MINIMAL_CROP_KWARGS)
# TODO: Remove this when fixed
# E AssertionError:
# E
# E from user code:
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 1324, in resume_in_crop
# E return kernel(inpt, top=top, left=left, height=height, width=width)
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 1343, in crop_image
# E return _pad_with_scalar_fill(image, torch_padding, fill=0, padding_mode="constant")
# E File "vision/torchvision/transforms/v2/functional/_geometry.py", line 1168, in _pad_with_scalar_fill
# E num_channels, height, width = shape[-3:]
check_torch_compile_smoke = False if make_input == make_bounding_boxes else True
check_functional(
F.crop,
make_input(self.INPUT_SIZE),
**self.MINIMAL_CROP_KWARGS,
check_torch_compile_smoke=check_torch_compile_smoke,
)

@pytest.mark.parametrize(
("kernel", "input_type"),
Expand Down Expand Up @@ -3402,7 +3468,18 @@ def test_kernel_inplace(self, old_format, new_format):

@pytest.mark.parametrize(("old_format", "new_format"), old_new_formats)
def test_functional(self, old_format, new_format):
check_functional(F.convert_bounding_box_format, make_bounding_boxes(format=old_format), new_format=new_format)
# TODO: Disabled torch.compile check due to the error:
# torchvision/transforms/v2/functional/_meta.py:219: in convert_bounding_box_format
# raise ValueError("For pure tensor inputs, `old_format` has to be passed.")
# torchvision/transforms/v2/functional/_meta.py:219: in resume_in_convert_bounding_box_format
# raise ValueError("For pure tensor inputs, `old_format` has to be passed.")
# E ValueError: For pure tensor inputs, `old_format` has to be passed.
check_functional(
F.convert_bounding_box_format,
make_bounding_boxes(format=old_format),
new_format=new_format,
check_torch_compile_smoke=False,
)

@pytest.mark.parametrize(("old_format", "new_format"), old_new_formats)
@pytest.mark.parametrize("format_type", ["enum", "str"])
Expand Down Expand Up @@ -3676,7 +3753,18 @@ def test_kernel_video(self):
[make_image_tensor, make_image_pil, make_image, make_bounding_boxes, make_segmentation_mask, make_video],
)
def test_functional(self, make_input):
check_functional(F.pad, make_input(), padding=[1])
# TODO: Remove this when fixed
# E AssertionError:
# E
# E from user code:
# E File "/vision/torchvision/transforms/v2/functional/_geometry.py", line 1104, in resume_in_pad
# E return kernel(inpt, padding=padding, fill=fill, padding_mode=padding_mode)
# E File "/vision/torchvision/transforms/v2/functional/_geometry.py", line 1154, in pad_image
# E return _pad_with_scalar_fill(image, torch_padding, fill=fill, padding_mode=padding_mode)
# E File "/vision/torchvision/transforms/v2/functional/_geometry.py", line 1168, in _pad_with_scalar_fill
# E num_channels, height, width = shape[-3:]
check_torch_compile_smoke = False if make_input in (make_bounding_boxes, make_segmentation_mask) else True
check_functional(F.pad, make_input(), padding=[1], check_torch_compile_smoke=check_torch_compile_smoke)

@pytest.mark.parametrize(
("kernel", "input_type"),
Expand Down Expand Up @@ -4327,7 +4415,13 @@ def test_kernel(self, format, dtype, device):

@pytest.mark.parametrize("format", list(tv_tensors.BoundingBoxFormat))
def test_functional(self, format):
check_functional(F.clamp_bounding_boxes, make_bounding_boxes(format=format))
# TODO: Disabled torch.compile check due to the error:
# torchvision/transforms/v2/functional/_meta.py:219: in convert_bounding_box_format
# raise ValueError("For pure tensor inputs, `old_format` has to be passed.")
# torchvision/transforms/v2/functional/_meta.py:219: in resume_in_convert_bounding_box_format
# raise ValueError("For pure tensor inputs, `old_format` has to be passed.")
# E ValueError: For pure tensor inputs, `old_format` has to be passed.
check_functional(F.clamp_bounding_boxes, make_bounding_boxes(format=format), check_torch_compile_smoke=False)

def test_errors(self):
input_tv_tensor = make_bounding_boxes()
Expand Down

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