From d4f16cb3fe5093f22ec834a7998bd49800084e1c Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Thu, 2 Nov 2023 12:02:00 -0500
Subject: [PATCH 1/8] Added torch compile checks for functional ops
---
test/test_transforms_v2.py | 31 +++++++++++++++++++++++++++----
1 file changed, 27 insertions(+), 4 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 4f8d0027bd6..06f10fcca71 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -186,7 +186,21 @@ def _check_functional_scripted_smoke(functional, input, *args, **kwargs):
functional_scripted(input.as_subclass(torch.Tensor), *args, **kwargs)
-def check_functional(functional, input, *args, check_scripted_smoke=True, **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):
+ return
+
+ functional_compiled = torch.compile(functional)
+ functional_compiled(input.as_subclass(torch.Tensor), *args, **kwargs)
+
+ explanation = torch._dynamo.explain(functional_compiled)(input.as_subclass(torch.Tensor), *args, **kwargs)
+ # TODO: Set expected values to 2, 1 once fixed the graph break related to function registration
+ assert explanation.graph_count == 2
+ assert explanation.graph_break_count == 1
+
+
+def check_functional(functional, input, *args, check_scripted_smoke=True, check_torch_compile_smoke=True, **kwargs):
unknown_input = object()
with pytest.raises(TypeError, match=re.escape(str(type(unknown_input)))):
functional(unknown_input, *args, **kwargs)
@@ -204,6 +218,9 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, **kwar
if check_scripted_smoke:
_check_functional_scripted_smoke(functional, input, *args, **kwargs)
+ if check_torch_compile_smoke:
+ _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
+
def check_functional_kernel_signature_match(functional, *, kernel, input_type):
"""Checks if the signature of the functional matches the kernel signature."""
@@ -656,6 +673,7 @@ def test_functional(self, size, make_input):
size=size,
antialias=True,
check_scripted_smoke=not isinstance(size, int),
+ check_torch_compile_smoke=False,
)
@pytest.mark.parametrize(
@@ -3469,7 +3487,12 @@ def test_kernel(self, kernel, make_input):
)
def test_functional(self, make_input):
check_functional(
- F.resized_crop, make_input(self.INPUT_SIZE), **self.CROP_KWARGS, size=self.OUTPUT_SIZE, antialias=True
+ F.resized_crop,
+ make_input(self.INPUT_SIZE),
+ **self.CROP_KWARGS,
+ size=self.OUTPUT_SIZE,
+ antialias=True,
+ check_torch_compile_smoke=False,
)
@pytest.mark.parametrize(
@@ -3949,7 +3972,7 @@ 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.perspective, make_input(), **self.MINIMAL_KWARGS)
+ check_functional(F.perspective, make_input(), **self.MINIMAL_KWARGS, check_torch_compile_smoke=False)
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -4106,7 +4129,7 @@ def test_kernel_video(self):
@pytest.mark.parametrize("make_input", [make_image_tensor, make_image_pil, make_image, make_video])
def test_functional(self, make_input):
- check_functional(F.equalize, make_input())
+ check_functional(F.equalize, make_input(), check_torch_compile_smoke=False)
@pytest.mark.parametrize(
("kernel", "input_type"),
From d5ca7b297ee5afc881a341f4a57a52f5ff14dd21 Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Fri, 3 Nov 2023 12:18:13 -0500
Subject: [PATCH 2/8] Fixed failing tests
---
test/test_transforms_v2.py | 11 +++++++----
1 file changed, 7 insertions(+), 4 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 06f10fcca71..afafeb65e71 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -7,6 +7,7 @@
import pickle
import random
import re
+import sys
from copy import deepcopy
from pathlib import Path
from unittest import mock
@@ -195,9 +196,9 @@ def _check_functional_torch_compile_smoke(functional, input, *args, **kwargs):
functional_compiled(input.as_subclass(torch.Tensor), *args, **kwargs)
explanation = torch._dynamo.explain(functional_compiled)(input.as_subclass(torch.Tensor), *args, **kwargs)
- # TODO: Set expected values to 2, 1 once fixed the graph break related to function registration
- assert explanation.graph_count == 2
- assert explanation.graph_break_count == 1
+ # TODO: Set expected values to 1, 0 once fixed the graph break related to function registration
+ assert explanation.graph_count in (1, 2)
+ assert explanation.graph_break_count in (0, 1)
def check_functional(functional, input, *args, check_scripted_smoke=True, check_torch_compile_smoke=True, **kwargs):
@@ -218,7 +219,8 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, check_
if check_scripted_smoke:
_check_functional_scripted_smoke(functional, input, *args, **kwargs)
- if check_torch_compile_smoke:
+ # Skip check on Windows as torch.compile does not work on Win32
+ if check_torch_compile_smoke and sys.platform != "win32":
_check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
@@ -1982,6 +1984,7 @@ def test_functional(self, make_input, input_dtype, output_dtype, device, scale):
make_input(dtype=input_dtype, device=device),
dtype=output_dtype,
scale=scale,
+
)
@pytest.mark.parametrize(
From 6fce5da7da61925f8847b275bf6e4b229d0d9333 Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Fri, 3 Nov 2023 12:24:26 -0500
Subject: [PATCH 3/8] Fixed lint
---
test/test_transforms_v2.py | 1 -
1 file changed, 1 deletion(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index afafeb65e71..dac560d6b41 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -1984,7 +1984,6 @@ def test_functional(self, make_input, input_dtype, output_dtype, device, scale):
make_input(dtype=input_dtype, device=device),
dtype=output_dtype,
scale=scale,
-
)
@pytest.mark.parametrize(
From 829a2d3da334185026a000e176db20a9552f4f45 Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Mon, 6 Nov 2023 07:10:33 -0600
Subject: [PATCH 4/8] Fixed depr warning problem
---
test/test_transforms_v2.py | 8 +++++++-
1 file changed, 7 insertions(+), 1 deletion(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index dac560d6b41..5ed2fe76ce0 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -221,7 +221,13 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, check_
# Skip check on Windows as torch.compile does not work on Win32
if check_torch_compile_smoke and sys.platform != "win32":
- _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
+ # Temporary fix to catch deprectation warning
+ # This can be removed once https://github.com/pytorch/pytorch/pull/113023 is merged:
+ import warnings
+
+ with warnings.catch_warnings():
+ warnings.filterwarnings("ignore", category=DeprecationWarning)
+ _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
def check_functional_kernel_signature_match(functional, *, kernel, input_type):
From 7f91053e219946189acb38c987e36c1bdfcb607c Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Tue, 7 Nov 2023 04:38:22 -0600
Subject: [PATCH 5/8] Removed temporary fixes
---
test/test_transforms_v2.py | 10 ++--------
1 file changed, 2 insertions(+), 8 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 5ed2fe76ce0..38136152f39 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -221,13 +221,7 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, check_
# Skip check on Windows as torch.compile does not work on Win32
if check_torch_compile_smoke and sys.platform != "win32":
- # Temporary fix to catch deprectation warning
- # This can be removed once https://github.com/pytorch/pytorch/pull/113023 is merged:
- import warnings
-
- with warnings.catch_warnings():
- warnings.filterwarnings("ignore", category=DeprecationWarning)
- _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
+ _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
def check_functional_kernel_signature_match(functional, *, kernel, input_type):
@@ -4137,7 +4131,7 @@ def test_kernel_video(self):
@pytest.mark.parametrize("make_input", [make_image_tensor, make_image_pil, make_image, make_video])
def test_functional(self, make_input):
- check_functional(F.equalize, make_input(), check_torch_compile_smoke=False)
+ check_functional(F.equalize, make_input())
@pytest.mark.parametrize(
("kernel", "input_type"),
From 84100215138a7d78a5396bec1e688bd27f7e53f7 Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Wed, 8 Nov 2023 02:59:51 -0600
Subject: [PATCH 6/8] Enabled torch compile functional tests for boxes, masks
and video Annotated exceptions with encountered errors
---
test/test_transforms_v2.py | 110 ++++++++++++++++++++++++++++++++++---
1 file changed, 102 insertions(+), 8 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 38136152f39..4e3c6bf49dc 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -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)
@@ -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"),
@@ -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"),
@@ -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"),
@@ -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"),
@@ -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"])
@@ -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"),
@@ -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()
From d18565643598dfeb419e96d009052e17e21b790e Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Wed, 8 Nov 2023 04:21:33 -0600
Subject: [PATCH 7/8] Fixed failing compiled execs
---
test/test_transforms_v2.py | 115 +++--------------------------
torchvision/tv_tensors/__init__.py | 4 +
2 files changed, 14 insertions(+), 105 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 4e3c6bf49dc..7f19b923559 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -193,11 +193,10 @@ def _check_functional_torch_compile_smoke(functional, input, *args, **kwargs):
return
functional_compiled = torch.compile(functional)
- functional_compiled(input.as_subclass(torch.Tensor), *args, **kwargs)
+ functional_compiled(input, *args, **kwargs)
- explanation = torch._dynamo.explain(functional_compiled)(input.as_subclass(torch.Tensor), *args, **kwargs)
- # TODO: Set expected values to 1, 0 once fixed the graph break related to function registration
- assert explanation.graph_count in (1, 2)
+ explanation = torch._dynamo.explain(functional_compiled)(input, *args, **kwargs)
+ # TODO: Set expected value to 0 once fixed the graph break related to function registration
assert explanation.graph_break_count in (0, 1)
@@ -1162,22 +1161,7 @@ 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
- # /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
- )
+ check_functional(F.affine, make_input(), **self._MINIMAL_AFFINE_KWARGS)
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -1601,12 +1585,7 @@ 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
- # 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
- )
+ check_functional(F.rotate, make_input(), **self._MINIMAL_AFFINE_KWARGS)
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -2671,38 +2650,8 @@ 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_torch_compile_smoke=check_torch_compile_smoke,
- )
+ check_functional(F.elastic, input, displacement=self._make_displacement(input))
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -2815,23 +2764,7 @@ 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
- # 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,
- )
+ check_functional(F.crop, make_input(self.INPUT_SIZE), **self.MINIMAL_CROP_KWARGS)
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -3468,18 +3401,7 @@ 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):
- # 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,
- )
+ check_functional(F.convert_bounding_box_format, make_bounding_boxes(format=old_format), new_format=new_format)
@pytest.mark.parametrize(("old_format", "new_format"), old_new_formats)
@pytest.mark.parametrize("format_type", ["enum", "str"])
@@ -3753,18 +3675,7 @@ 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
- # 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)
+ check_functional(F.pad, make_input(), padding=[1])
@pytest.mark.parametrize(
("kernel", "input_type"),
@@ -4415,13 +4326,7 @@ def test_kernel(self, format, dtype, device):
@pytest.mark.parametrize("format", list(tv_tensors.BoundingBoxFormat))
def test_functional(self, 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)
+ check_functional(F.clamp_bounding_boxes, make_bounding_boxes(format=format))
def test_errors(self):
input_tv_tensor = make_bounding_boxes()
diff --git a/torchvision/tv_tensors/__init__.py b/torchvision/tv_tensors/__init__.py
index d55e10e8620..2e58d9d4c6a 100644
--- a/torchvision/tv_tensors/__init__.py
+++ b/torchvision/tv_tensors/__init__.py
@@ -8,6 +8,10 @@
from ._video import Video
+# TODO: Fix this. We skip this method as it leads to
+# RecursionError: maximum recursion depth exceeded while calling a Python object
+# Keeping it here, leads to graph breaks between multiple functional ops instead of having a single graph
+@torch.compiler.disable
def wrap(wrappee, *, like, **kwargs):
"""[BETA] Convert a :class:`torch.Tensor` (``wrappee``) into the same :class:`~torchvision.tv_tensors.TVTensor` subclass as ``like``.
From 3c959d904bb41e8bad059d3c11b1260b7b576a48 Mon Sep 17 00:00:00 2001
From: vfdev-5 <vfdev.5@gmail.com>
Date: Fri, 10 Nov 2023 04:41:50 -0600
Subject: [PATCH 8/8] Revert "Removed temporary fixes"
This reverts commit 7f91053e219946189acb38c987e36c1bdfcb607c.
---
test/test_transforms_v2.py | 10 ++++++++--
1 file changed, 8 insertions(+), 2 deletions(-)
diff --git a/test/test_transforms_v2.py b/test/test_transforms_v2.py
index 7f19b923559..9cba49440d1 100644
--- a/test/test_transforms_v2.py
+++ b/test/test_transforms_v2.py
@@ -220,7 +220,13 @@ def check_functional(functional, input, *args, check_scripted_smoke=True, check_
# Skip check on Windows as torch.compile does not work on Win32
if check_torch_compile_smoke and sys.platform != "win32":
- _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
+ # Temporary fix to catch deprectation warning
+ # This can be removed once https://github.com/pytorch/pytorch/pull/113023 is merged:
+ import warnings
+
+ with warnings.catch_warnings():
+ warnings.filterwarnings("ignore", category=DeprecationWarning)
+ _check_functional_torch_compile_smoke(functional, input, *args, **kwargs)
def check_functional_kernel_signature_match(functional, *, kernel, input_type):
@@ -4130,7 +4136,7 @@ def test_kernel_video(self):
@pytest.mark.parametrize("make_input", [make_image_tensor, make_image_pil, make_image, make_video])
def test_functional(self, make_input):
- check_functional(F.equalize, make_input())
+ check_functional(F.equalize, make_input(), check_torch_compile_smoke=False)
@pytest.mark.parametrize(
("kernel", "input_type"),