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Update XNNPACK (#73467)

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Summary:
To https://github.com/google/XNNPACK/commit/ae108ef49aa5623b896fc93d4298c49d1750d9b

Revert https://github.com/pytorch/pytorch/pull/73476 and skip `TestXNNPACKOps.test_linear`, `TestXNNPACKSerDes.test_linear` and `TestXNNPACKSerDes.test_combined_model`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/73467

Reviewed By: digantdesai

Differential Revision: D34493139

Pulled By: malfet

fbshipit-source-id: 684e28c70644c42d2a73bc8146dca2e3e0ba3747
(cherry picked from commit 2ecfbe4c594d81f6cbcbcc1b871b3525920ee74a)
This commit is contained in:
Nikita Shulga
2022-02-27 21:35:29 -08:00
committed by PyTorch MergeBot
parent 3c932c345b
commit a22d079abd
2 changed files with 5 additions and 6 deletions
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9
test/test_xnnpack_integration.py
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@ -14,14 +14,14 @@ from hypothesis import strategies as st
import io
import itertools
from torch.testing._internal.common_utils import (TEST_WITH_TSAN, TEST_WITH_ROCM)
from torch.testing._internal.common_utils import TEST_WITH_TSAN
@unittest.skipUnless(torch.backends.xnnpack.enabled,
" XNNPACK must be enabled for these tests."
" Please build with USE_XNNPACK=1.")
@unittest.skipIf(TEST_WITH_TSAN, "TSAN fails with XNNPACK. Does not seem to have a good reason for failures.")
@unittest.skipIf(TEST_WITH_ROCM, "HACK, not sure why these fail on ROCM.")
class TestXNNPACKOps(TestCase):
@unittest.skip("Fails on some platforms, see https://github.com/pytorch/pytorch/issues/73488")
@given(batch_size=st.integers(0, 3),
data_shape=hu.array_shapes(1, 3, 2, 64),
weight_output_dim=st.integers(2, 64),
@ -182,8 +182,8 @@ class TestXNNPACKOps(TestCase):
" XNNPACK must be enabled for these tests."
" Please build with USE_XNNPACK=1.")
@unittest.skipIf(TEST_WITH_TSAN, "TSAN fails with XNNPACK. Does not seem to have a good reason for failures.")
@unittest.skipIf(TEST_WITH_ROCM, "HACK, not sure why these fail on ROCM.")
class TestXNNPACKSerDes(TestCase):
@unittest.skip("Fails on some platforms, see https://github.com/pytorch/pytorch/issues/73488")
@given(batch_size=st.integers(0, 3),
data_shape=hu.array_shapes(1, 3, 2, 64),
weight_output_dim=st.integers(2, 64),
@ -438,6 +438,7 @@ class TestXNNPACKSerDes(TestCase):
xnnpack_result = deserialized_conv2d_clamp_prepacked(input_data)
torch.testing.assert_close(ref_result, xnnpack_result, rtol=1e-2, atol=1e-3)
@unittest.skip("Fails on some platforms, see https://github.com/pytorch/pytorch/issues/73488")
@given(batch_size=st.integers(0, 3),
input_channels_per_group=st.integers(1, 32),
height=st.integers(5, 64),
@ -574,7 +575,6 @@ class TestXNNPACKSerDes(TestCase):
" XNNPACK must be enabled for these tests."
" Please build with USE_XNNPACK=1.")
@unittest.skipIf(TEST_WITH_TSAN, "TSAN fails with XNNPACK. Does not seem to have a good reason for failures.")
@unittest.skipIf(TEST_WITH_ROCM, "HACK, not sure why these fail on ROCM.")
class TestXNNPACKRewritePass(TestCase):
@staticmethod
def validate_transformed_module(
@ -936,7 +936,6 @@ class TestXNNPACKRewritePass(TestCase):
" XNNPACK must be enabled for these tests."
" Please build with USE_XNNPACK=1.")
@unittest.skipIf(TEST_WITH_TSAN, "TSAN is not fork-safe since we're forking in a multi-threaded environment")
@unittest.skipIf(TEST_WITH_ROCM, "HACK, not sure why these fail on ROCM.")
class TestXNNPACKConv1dTransformPass(TestCase):
@staticmethod
def validate_transform_conv1d_to_conv2d(

2
third_party/XNNPACK vendored

Submodule third_party/XNNPACK updated: 79cd5f9e18...ae108ef49a