8000 [Not to be merged] Update to compile and run test_torch with 3.13t by albanD · Pull Request #130689 · pytorch/pytorch · GitHub
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[Not to be merged] Update to compile and run test_torch with 3.13t #130689

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[Not to be merged] Update to compile and run test_torch with 3.13t #130689

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0eb8c55
Small updates
albanD Jul 13, 2024
45ed610
fix test_torch for 3.13
albanD Jul 13, 2024
005b98c
Fix requirements.txt back
albanD Jul 14, 2024
bb08736
Fix static `py::object` dangling pointer with `py::gil_safe_call_once…
XuehaiPan Jul 10, 2024
e4a652e
More pickler fix and updated dependency
albanD Jul 16, 2024
df98ed5
Remove test dependencies not supported in 3.13
albanD Jul 17, 2024
4939de8
no gil deps
albanD Jul 17, 2024
86016ed
minor cleanup
albanD Sep 23, 2024
98be449
Merge branch 'main' into update_313t
XuehaiPan Oct 8, 2024
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21 changes: 11 additions & 10 deletions .ci/docker/requirements-ci.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ optree==0.13.0
#test_pointwise_ops.py, test_dtensor_ops.py, test_torchinductor.py, test_fx.py,
#test_fake_tensor.py, test_mps.py

pillow==10.3.0
pillow==10.3.0 ; python_version <= "3.12"
#Description: Python Imaging Library fork
#Pinned versions: 10.3.0
#test that import:
Expand Down Expand Up @@ -223,7 +223,7 @@ pygments==2.15.0
#test that import:

scikit-image==0.19.3 ; python_version < "3.10"
scikit-image==0.22.0 ; python_version >= "3.10"
scikit-image==0.20.0 ; python_version >= "3.10" and python_version <= "3.12"
#Description: image processing routines
#Pinned versions:
#test that import: test_nn.py
Expand All @@ -235,6 +235,7 @@ scikit-image==0.22.0 ; python_version >= "3.10"

scipy==1.10.1 ; python_version <= "3.11"
scipy==1.12.0 ; python_version == "3.12"
scipy>1.14 ; python_version == "3.13"
# Pin SciPy because of failing distribution tests (see #60347)
#Description: scientific python
#Pinned versions: 1.10.1
Expand All @@ -247,7 +248,7 @@ scipy==1.12.0 ; python_version == "3.12"
#Pinned versions:
#test that import:

tb-nightly==2.13.0a20230426
tb-nightly==2.13.0a20230426 ; python_version <= "3.12"
#Description: TensorBoard
#Pinned versions:
#test that import:
Expand All @@ -263,7 +264,7 @@ typing-extensions
#Pinned versions:
#test that import:

unittest-xml-reporting<=3.2.0,>=2.0.0
unittest-xml-reporting<=3.2.0,>=2.0.0 ; python_version <= "3.12"
#Description: saves unit test results to xml
#Pinned versions:
#test that import:
Expand Down Expand Up @@ -303,37 +304,37 @@ z3-solver==4.12.2.0
#Pinned versions:
#test that import:

tensorboard==2.13.0
tensorboard==2.13.0 ; python_version <= "3.12"
#Description: Also included in .ci/docker/requirements-docs.txt
#Pinned versions:
#test that import: test_tensorboard

pywavelets==1.4.1 ; python_version < "3.12"
pywavelets==1.5.0 ; python_version >= "3.12"
pywavelets==1.5.0 ; python_version == "3.12"
#Description: This is a requirement of scikit-image, we need to pin
# it here because 1.5.0 conflicts with numpy 1.21.2 used in CI
#Pinned versions: 1.4.1
#test that import:

lxml==5.0.0
lxml==5.0.0 ; python_version <= "3.12"
#Description: This is a requirement of unittest-xml-reporting

# Python-3.9 binaries

PyGithub==2.3.0
PyGithub==2.3.0 ; python_version <= "3.12"

sympy==1.12.1 ; python_version == "3.8"
sympy==1.13.1 ; python_version >= "3.9"
#Description: Required by coremltools, also pinned in .github/requirements/pip-requirements-macOS.txt
#Pinned versions:
#test that import:

onnx==1.16.1
onnx==1.16.1 ; python_version <= "3.12"
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:

onnxscript==0.1.0.dev20240817
onnxscript==0.1.0.dev20240817 ; python_version <= "3.12"
#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
#Pinned versions:
#test that import:
Expand Down
13 changes: 9 additions & 4 deletions test/test_torch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2891,7 +2891,12 @@ def test_diff(self, device, dtype):

# if the given input arg is not a list, it returns a list of single element: [arg]
def _wrap_to_list(self, input_array):
return input_array if isinstance(input_array, list) else [input_array]
if isinstance(input_array, list):
return input_array
elif isinstance(input_array, tuple):
return list(input_array)
else:
return [input_array]

# To ensure inf, -inf, and nan values do not cause divergence between Numpy and PyTorch.
# There are two types of possible divergence:
Expand Down Expand Up @@ -3029,7 +3034,7 @@ def test_gradient_type_promotion(self, device):
# Result is given just as real number and all the imaginary parts to be equal to zero.
self.assertEqual(expected[i].imag, torch.zeros(actual[i].shape), exact_dtype=False)
else:
actual, expected = self._inf_nan_preprocess(list(actual), expected)
actual, expected = self._inf_nan_preprocess(list(actual), self._wrap_to_list(expected))
self.assertEqual(actual, expected, equal_nan=True, exact_dtype=False)

@onlyNativeDeviceTypes
Expand Down Expand Up @@ -7559,10 +7564,10 @@ def test_sobolengine_distribution(self, scramble=False):
torch.mean(sample, dim=0), torch.full((d,), 0.5), atol=2, rtol=2
)
torch.testing.assert_close(
5E5C np.percentile(sample, 25, axis=0), np.repeat(0.25, d), atol=2, rtol=2
np.percentile(sample, 25, axis=0), np.repeat(0.25, d), atol=2, rtol=2, check_dtype=False
)
torch.testing.assert_close(
np.percentile(sample, 75, axis=0), np.repeat(0.75, d), atol=2, rtol=2
np.percentile(sample, 75, axis=0), np.repeat(0.75, d), atol=2, rtol=2, check_dtype=False
)

@skipIfTorchDynamo("np.float64 restored as float32 after graph break.")
Expand Down
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