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adding test_sparse_csr to run_test (#58666)
Summary: fixes https://github.com/pytorch/pytorch/issues/58632. Added several skips that relates to test assert and MKL. Will address them in separate PR. Pull Request resolved: https://github.com/pytorch/pytorch/pull/58666 Reviewed By: seemethere, janeyx99 Differential Revision: D28607966 Pulled By: walterddr fbshipit-source-id: 066d4afce2672e4026334528233e69f68da04965
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@ -81,6 +81,7 @@ TESTS = [
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'test_xnnpack_integration',
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'test_xnnpack_integration',
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'test_vulkan',
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'test_vulkan',
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'test_sparse',
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'test_sparse',
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'test_sparse_csr',
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'test_quantization',
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'test_quantization',
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'test_pruning_op',
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'test_pruning_op',
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'test_spectral_ops',
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'test_spectral_ops',
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@ -1,6 +1,8 @@
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import torch
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import torch
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import warnings
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import warnings
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from torch.testing._internal.common_utils import TestCase, run_tests, load_tests, coalescedonoff
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import unittest
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from torch.testing._internal.common_utils import \
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(IS_MACOS, IS_WINDOWS, TestCase, run_tests, load_tests, coalescedonoff)
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from torch.testing._internal.common_device_type import \
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from torch.testing._internal.common_device_type import \
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(instantiate_device_type_tests, dtypes, onlyCPU)
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(instantiate_device_type_tests, dtypes, onlyCPU)
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@ -81,7 +83,10 @@ class TestSparseCSR(TestCase):
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size, dtype=dtype, device=device)
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size, dtype=dtype, device=device)
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@onlyCPU
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@onlyCPU
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@unittest.skip("see: https://github.com/pytorch/pytorch/issues/58762")
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def test_sparse_csr_print(self, device):
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def test_sparse_csr_print(self, device):
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orig_maxDiff = self.maxDiff
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self.maxDiff = None
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shape_nnz = [
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shape_nnz = [
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((10, 10), 10),
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((10, 10), 10),
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((100, 10), 10),
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((100, 10), 10),
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@ -112,6 +117,7 @@ class TestSparseCSR(TestCase):
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printed.append('')
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printed.append('')
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printed.append('')
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printed.append('')
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self.assertExpected('\n'.join(printed))
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self.assertExpected('\n'.join(printed))
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self.maxDiff = orig_maxDiff
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@onlyCPU
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@onlyCPU
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def test_sparse_csr_from_dense(self, device):
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def test_sparse_csr_from_dense(self, device):
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@ -157,6 +163,7 @@ class TestSparseCSR(TestCase):
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@coalescedonoff
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@coalescedonoff
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@onlyCPU
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@onlyCPU
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@dtypes(torch.double)
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@dtypes(torch.double)
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@unittest.skipIf(IS_MACOS or IS_WINDOWS, "see: https://github.com/pytorch/pytorch/issues/58757")
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def test_coo_to_csr_convert(self, device, dtype, coalesced):
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def test_coo_to_csr_convert(self, device, dtype, coalesced):
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size = (5, 5)
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size = (5, 5)
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sparse_dim = 2
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sparse_dim = 2
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@ -186,6 +193,7 @@ class TestSparseCSR(TestCase):
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@onlyCPU
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@onlyCPU
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@dtypes(torch.float, torch.double)
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@dtypes(torch.float, torch.double)
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@unittest.skipIf(IS_MACOS or IS_WINDOWS, "see: https://github.com/pytorch/pytorch/issues/58757")
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def test_mkl_matvec_warnings(self, device, dtype):
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def test_mkl_matvec_warnings(self, device, dtype):
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if torch.has_mkl:
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if torch.has_mkl:
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for index_dtype in [torch.int32, torch.int64]:
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for index_dtype in [torch.int32, torch.int64]:
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@ -211,6 +219,7 @@ class TestSparseCSR(TestCase):
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@onlyCPU
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@onlyCPU
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@dtypes(torch.float, torch.double)
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@dtypes(torch.float, torch.double)
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@unittest.skipIf(IS_MACOS or IS_WINDOWS, "see: https://github.com/pytorch/pytorch/issues/58757")
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def test_csr_matvec(self, device, dtype):
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def test_csr_matvec(self, device, dtype):
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side = 100
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side = 100
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for index_dtype in [torch.int32, torch.int64]:
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for index_dtype in [torch.int32, torch.int64]:
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