| import torch |
| |
| import math |
| from pathlib import PurePosixPath |
| |
| from torch.testing._internal.common_utils import \ |
| (TestCase, make_tensor, run_tests, slowTest) |
| from torch.testing._internal.common_device_type import \ |
| (instantiate_device_type_tests, onlyCUDA, onlyOnCPUAndCUDA, dtypes) |
| from torch.testing._internal import mypy_wrapper |
| from torch.testing._internal import print_test_stats |
| |
| # For testing TestCase methods and torch.testing functions |
| class TestTesting(TestCase): |
| # Ensure that assertEqual handles numpy arrays properly |
| @dtypes(*(torch.testing.get_all_dtypes(include_half=True, include_bfloat16=False, |
| include_bool=True, include_complex=True))) |
| def test_assertEqual_numpy(self, device, dtype): |
| S = 10 |
| test_sizes = [ |
| (), |
| (0,), |
| (S,), |
| (S, S), |
| (0, S), |
| (S, 0)] |
| for test_size in test_sizes: |
| a = make_tensor(test_size, device, dtype, low=-5, high=5) |
| a_n = a.cpu().numpy() |
| msg = f'size: {test_size}' |
| self.assertEqual(a_n, a, rtol=0, atol=0, msg=msg) |
| self.assertEqual(a, a_n, rtol=0, atol=0, msg=msg) |
| self.assertEqual(a_n, a_n, rtol=0, atol=0, msg=msg) |
| |
| # Tests that when rtol or atol (including self.precision) is set, then |
| # the other is zeroed. |
| # TODO: this is legacy behavior and should be updated after test |
| # precisions are reviewed to be consistent with torch.isclose. |
| @onlyOnCPUAndCUDA |
| def test__comparetensors_legacy(self, device): |
| a = torch.tensor((10000000.,)) |
| b = torch.tensor((10000002.,)) |
| |
| x = torch.tensor((1.,)) |
| y = torch.tensor((1. + 1e-5,)) |
| |
| # Helper for reusing the tensor values as scalars |
| def _scalar_helper(a, b, rtol=None, atol=None): |
| return self._compareScalars(a.item(), b.item(), rtol=rtol, atol=atol) |
| |
| for op in (self._compareTensors, _scalar_helper): |
| # Tests default |
| result, debug_msg = op(a, b) |
| self.assertTrue(result) |
| |
| # Tests setting atol |
| result, debug_msg = op(a, b, atol=2, rtol=0) |
| self.assertTrue(result) |
| |
| # Tests setting atol too small |
| result, debug_msg = op(a, b, atol=1, rtol=0) |
| self.assertFalse(result) |
| |
| # Tests setting rtol too small |
| result, debug_msg = op(x, y, atol=0, rtol=1.05e-5) |
| self.assertTrue(result) |
| |
| # Tests setting rtol too small |
| result, debug_msg = op(x, y, atol=0, rtol=1e-5) |
| self.assertFalse(result) |
| |
| @onlyOnCPUAndCUDA |
| def test__comparescalars_debug_msg(self, device): |
| # float x float |
| result, debug_msg = self._compareScalars(4., 7.) |
| expected_msg = ("Comparing 4.0 and 7.0 gives a difference of 3.0, " |
| "but the allowed difference with rtol=1.3e-06 and " |
| "atol=1e-05 is only 1.9100000000000003e-05!") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # complex x complex, real difference |
| result, debug_msg = self._compareScalars(complex(1, 3), complex(3, 1)) |
| expected_msg = ("Comparing the real part 1.0 and 3.0 gives a difference " |
| "of 2.0, but the allowed difference with rtol=1.3e-06 " |
| "and atol=1e-05 is only 1.39e-05!") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # complex x complex, imaginary difference |
| result, debug_msg = self._compareScalars(complex(1, 3), complex(1, 5.5)) |
| expected_msg = ("Comparing the imaginary part 3.0 and 5.5 gives a " |
| "difference of 2.5, but the allowed difference with " |
| "rtol=1.3e-06 and atol=1e-05 is only 1.715e-05!") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # complex x int |
| result, debug_msg = self._compareScalars(complex(1, -2), 1) |
| expected_msg = ("Comparing the imaginary part -2.0 and 0.0 gives a " |
| "difference of 2.0, but the allowed difference with " |
| "rtol=1.3e-06 and atol=1e-05 is only 1e-05!") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # NaN x NaN, equal_nan=False |
| result, debug_msg = self._compareScalars(float('nan'), float('nan'), equal_nan=False) |
| expected_msg = ("Found nan and nan while comparing and either one is " |
| "nan and the other isn't, or both are nan and equal_nan " |
| "is False") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks that compareTensors provides the correct debug info |
| @onlyOnCPUAndCUDA |
| def test__comparetensors_debug_msg(self, device): |
| # Acquires atol that will be used |
| atol = max(1e-05, self.precision) |
| |
| # Checks float tensor comparisons (2D tensor) |
| a = torch.tensor(((0, 6), (7, 9)), device=device, dtype=torch.float32) |
| b = torch.tensor(((0, 7), (7, 22)), device=device, dtype=torch.float32) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("With rtol=1.3e-06 and atol={0}, found 2 element(s) (out of 4) " |
| "whose difference(s) exceeded the margin of error (including 0 nan comparisons). " |
| "The greatest difference was 13.0 (9.0 vs. 22.0), " |
| "which occurred at index (1, 1).").format(atol) |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks float tensor comparisons (with extremal values) |
| a = torch.tensor((float('inf'), 5, float('inf')), device=device, dtype=torch.float32) |
| b = torch.tensor((float('inf'), float('nan'), float('-inf')), device=device, dtype=torch.float32) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("With rtol=1.3e-06 and atol={0}, found 2 element(s) (out of 3) " |
| "whose difference(s) exceeded the margin of error (including 1 nan comparisons). " |
| "The greatest difference was nan (5.0 vs. nan), " |
| "which occurred at index 1.").format(atol) |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks float tensor comparisons (with finite vs nan differences) |
| a = torch.tensor((20, -6), device=device, dtype=torch.float32) |
| b = torch.tensor((-1, float('nan')), device=device, dtype=torch.float32) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("With rtol=1.3e-06 and atol={0}, found 2 element(s) (out of 2) " |
| "whose difference(s) exceeded the margin of error (including 1 nan comparisons). " |
| "The greatest difference was nan (-6.0 vs. nan), " |
| "which occurred at index 1.").format(atol) |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks int tensor comparisons (1D tensor) |
| a = torch.tensor((1, 2, 3, 4), device=device) |
| b = torch.tensor((2, 5, 3, 4), device=device) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("Found 2 different element(s) (out of 4), " |
| "with the greatest difference of 3 (2 vs. 5) " |
| "occuring at index 1.") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks bool tensor comparisons (0D tensor) |
| a = torch.tensor((True), device=device) |
| b = torch.tensor((False), device=device) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("Found 1 different element(s) (out of 1), " |
| "with the greatest difference of 1 (1 vs. 0) " |
| "occuring at index 0.") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks complex tensor comparisons (real part) |
| a = torch.tensor((1 - 1j, 4 + 3j), device=device) |
| b = torch.tensor((1 - 1j, 1 + 3j), device=device) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("Real parts failed to compare as equal! " |
| "With rtol=1.3e-06 and atol={0}, " |
| "found 1 element(s) (out of 2) whose difference(s) exceeded the " |
| "margin of error (including 0 nan comparisons). The greatest difference was " |
| "3.0 (4.0 vs. 1.0), which occurred at index 1.").format(atol) |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks complex tensor comparisons (imaginary part) |
| a = torch.tensor((1 - 1j, 4 + 3j), device=device) |
| b = torch.tensor((1 - 1j, 4 - 21j), device=device) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("Imaginary parts failed to compare as equal! " |
| "With rtol=1.3e-06 and atol={0}, " |
| "found 1 element(s) (out of 2) whose difference(s) exceeded the " |
| "margin of error (including 0 nan comparisons). The greatest difference was " |
| "24.0 (3.0 vs. -21.0), which occurred at index 1.").format(atol) |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks size mismatch |
| a = torch.tensor((1, 2), device=device) |
| b = torch.tensor((3), device=device) |
| result, debug_msg = self._compareTensors(a, b) |
| expected_msg = ("Attempted to compare equality of tensors " |
| "with different sizes. Got sizes torch.Size([2]) and torch.Size([]).") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks dtype mismatch |
| a = torch.tensor((1, 2), device=device, dtype=torch.long) |
| b = torch.tensor((1, 2), device=device, dtype=torch.float32) |
| result, debug_msg = self._compareTensors(a, b, exact_dtype=True) |
| expected_msg = ("Attempted to compare equality of tensors " |
| "with different dtypes. Got dtypes torch.int64 and torch.float32.") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Checks device mismatch |
| if self.device_type == 'cuda': |
| a = torch.tensor((5), device='cpu') |
| b = torch.tensor((5), device=device) |
| result, debug_msg = self._compareTensors(a, b, exact_device=True) |
| expected_msg = ("Attempted to compare equality of tensors " |
| "on different devices! Got devices cpu and cuda:0.") |
| self.assertEqual(debug_msg, expected_msg) |
| |
| # Helper for testing _compareTensors and _compareScalars |
| # Works on single element tensors |
| def _comparetensors_helper(self, tests, device, dtype, equal_nan, exact_dtype=True, atol=1e-08, rtol=1e-05): |
| for test in tests: |
| a = torch.tensor((test[0],), device=device, dtype=dtype) |
| b = torch.tensor((test[1],), device=device, dtype=dtype) |
| |
| # Tensor x Tensor comparison |
| compare_result, debug_msg = self._compareTensors(a, b, rtol=rtol, atol=atol, |
| equal_nan=equal_nan, |
| exact_dtype=exact_dtype) |
| self.assertEqual(compare_result, test[2]) |
| |
| # Scalar x Scalar comparison |
| compare_result, debug_msg = self._compareScalars(a.item(), b.item(), |
| rtol=rtol, atol=atol, |
| equal_nan=equal_nan) |
| self.assertEqual(compare_result, test[2]) |
| |
| def _isclose_helper(self, tests, device, dtype, equal_nan, atol=1e-08, rtol=1e-05): |
| for test in tests: |
| a = torch.tensor((test[0],), device=device, dtype=dtype) |
| b = torch.tensor((test[1],), device=device, dtype=dtype) |
| |
| actual = torch.isclose(a, b, equal_nan=equal_nan, atol=atol, rtol=rtol) |
| expected = test[2] |
| self.assertEqual(actual.item(), expected) |
| |
| # torch.close is not implemented for bool tensors |
| # see https://github.com/pytorch/pytorch/issues/33048 |
| def test_isclose_comparetensors_bool(self, device): |
| tests = ( |
| (True, True, True), |
| (False, False, True), |
| (True, False, False), |
| (False, True, False), |
| ) |
| |
| with self.assertRaises(RuntimeError): |
| self._isclose_helper(tests, device, torch.bool, False) |
| |
| self._comparetensors_helper(tests, device, torch.bool, False) |
| |
| @dtypes(torch.uint8, |
| torch.int8, torch.int16, torch.int32, torch.int64) |
| def test_isclose_comparetensors_integer(self, device, dtype): |
| tests = ( |
| (0, 0, True), |
| (0, 1, False), |
| (1, 0, False), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False) |
| |
| # atol and rtol tests |
| tests = [ |
| (0, 1, True), |
| (1, 0, False), |
| (1, 3, True), |
| ] |
| |
| self._isclose_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| self._comparetensors_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| |
| if dtype is torch.uint8: |
| tests = [ |
| (-1, 1, False), |
| (1, -1, False) |
| ] |
| else: |
| tests = [ |
| (-1, 1, True), |
| (1, -1, True) |
| ] |
| |
| self._isclose_helper(tests, device, dtype, False, atol=1.5, rtol=.5) |
| self._comparetensors_helper(tests, device, dtype, False, atol=1.5, rtol=.5) |
| |
| @onlyOnCPUAndCUDA |
| @dtypes(torch.float16, torch.float32, torch.float64) |
| def test_isclose_comparetensors_float(self, device, dtype): |
| tests = ( |
| (0, 0, True), |
| (0, -1, False), |
| (float('inf'), float('inf'), True), |
| (-float('inf'), float('inf'), False), |
| (float('inf'), float('nan'), False), |
| (float('nan'), float('nan'), False), |
| (0, float('nan'), False), |
| (1, 1, True), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False) |
| self._comparetensors_helper(tests, device, dtype, False) |
| |
| # atol and rtol tests |
| eps = 1e-2 if dtype is torch.half else 1e-6 |
| tests = ( |
| (0, 1, True), |
| (0, 1 + eps, False), |
| (1, 0, False), |
| (1, 3, True), |
| (1 - eps, 3, False), |
| (-.25, .5, True), |
| (-.25 - eps, .5, False), |
| (.25, -.5, True), |
| (.25 + eps, -.5, False), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| self._comparetensors_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| |
| # equal_nan = True tests |
| tests = ( |
| (0, float('nan'), False), |
| (float('inf'), float('nan'), False), |
| (float('nan'), float('nan'), True), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, True) |
| |
| self._comparetensors_helper(tests, device, dtype, True) |
| |
| # torch.close with equal_nan=True is not implemented for complex inputs |
| # see https://github.com/numpy/numpy/issues/15959 |
| # Note: compareTensor will compare the real and imaginary parts of a |
| # complex tensors separately, unlike isclose. |
| @dtypes(torch.complex64, torch.complex128) |
| def test_isclose_comparetensors_complex(self, device, dtype): |
| tests = ( |
| (complex(1, 1), complex(1, 1 + 1e-8), True), |
| (complex(0, 1), complex(1, 1), False), |
| (complex(1, 1), complex(1, 0), False), |
| (complex(1, 1), complex(1, float('nan')), False), |
| (complex(1, float('nan')), complex(1, float('nan')), False), |
| (complex(1, 1), complex(1, float('inf')), False), |
| (complex(float('inf'), 1), complex(1, float('inf')), False), |
| (complex(-float('inf'), 1), complex(1, float('inf')), False), |
| (complex(-float('inf'), 1), complex(float('inf'), 1), False), |
| (complex(float('inf'), 1), complex(float('inf'), 1), True), |
| (complex(float('inf'), 1), complex(float('inf'), 1 + 1e-4), False), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False) |
| self._comparetensors_helper(tests, device, dtype, False) |
| |
| # atol and rtol tests |
| |
| # atol and rtol tests |
| eps = 1e-6 |
| tests = ( |
| # Complex versions of float tests (real part) |
| (complex(0, 0), complex(1, 0), True), |
| (complex(0, 0), complex(1 + eps, 0), False), |
| (complex(1, 0), complex(0, 0), False), |
| (complex(1, 0), complex(3, 0), True), |
| (complex(1 - eps, 0), complex(3, 0), False), |
| (complex(-.25, 0), complex(.5, 0), True), |
| (complex(-.25 - eps, 0), complex(.5, 0), False), |
| (complex(.25, 0), complex(-.5, 0), True), |
| (complex(.25 + eps, 0), complex(-.5, 0), False), |
| # Complex versions of float tests (imaginary part) |
| (complex(0, 0), complex(0, 1), True), |
| (complex(0, 0), complex(0, 1 + eps), False), |
| (complex(0, 1), complex(0, 0), False), |
| (complex(0, 1), complex(0, 3), True), |
| (complex(0, 1 - eps), complex(0, 3), False), |
| (complex(0, -.25), complex(0, .5), True), |
| (complex(0, -.25 - eps), complex(0, .5), False), |
| (complex(0, .25), complex(0, -.5), True), |
| (complex(0, .25 + eps), complex(0, -.5), False), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| self._comparetensors_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| |
| # atol and rtol tests for isclose |
| tests = ( |
| # Complex-specific tests |
| (complex(1, -1), complex(-1, 1), False), |
| (complex(1, -1), complex(2, -2), True), |
| (complex(-math.sqrt(2), math.sqrt(2)), |
| complex(-math.sqrt(.5), math.sqrt(.5)), True), |
| (complex(-math.sqrt(2), math.sqrt(2)), |
| complex(-math.sqrt(.501), math.sqrt(.499)), False), |
| (complex(2, 4), complex(1., 8.8523607), True), |
| (complex(2, 4), complex(1., 8.8523607 + eps), False), |
| (complex(1, 99), complex(4, 100), True), |
| ) |
| |
| self._isclose_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| |
| # atol and rtol tests for compareTensors |
| tests = ( |
| (complex(1, -1), complex(-1, 1), False), |
| (complex(1, -1), complex(2, -2), True), |
| (complex(1, 99), complex(4, 100), False), |
| ) |
| |
| self._comparetensors_helper(tests, device, dtype, False, atol=.5, rtol=.5) |
| |
| # equal_nan = True tests |
| tests = ( |
| (complex(1, 1), complex(1, float('nan')), False), |
| (complex(float('nan'), 1), complex(1, float('nan')), False), |
| (complex(float('nan'), 1), complex(float('nan'), 1), True), |
| ) |
| |
| with self.assertRaises(RuntimeError): |
| self._isclose_helper(tests, device, dtype, True) |
| |
| self._comparetensors_helper(tests, device, dtype, True) |
| |
| # Tests that isclose with rtol or atol values less than zero throws a |
| # RuntimeError |
| @dtypes(torch.bool, torch.uint8, |
| torch.int8, torch.int16, torch.int32, torch.int64, |
| torch.float16, torch.float32, torch.float64) |
| def test_isclose_atol_rtol_greater_than_zero(self, device, dtype): |
| t = torch.tensor((1,), device=device, dtype=dtype) |
| |
| with self.assertRaises(RuntimeError): |
| torch.isclose(t, t, atol=-1, rtol=1) |
| with self.assertRaises(RuntimeError): |
| torch.isclose(t, t, atol=1, rtol=-1) |
| with self.assertRaises(RuntimeError): |
| torch.isclose(t, t, atol=-1, rtol=-1) |
| |
| @dtypes(torch.bool, torch.long, torch.float, torch.cfloat) |
| def test_make_tensor(self, device, dtype): |
| def check(size, low, high, requires_grad, discontiguous): |
| t = make_tensor(size, device, dtype, low=low, high=high, |
| requires_grad=requires_grad, discontiguous=discontiguous) |
| |
| self.assertEqual(t.shape, size) |
| self.assertEqual(t.device, torch.device(device)) |
| self.assertEqual(t.dtype, dtype) |
| |
| low = -9 if low is None else low |
| high = 9 if high is None else high |
| |
| if t.numel() > 0 and dtype in [torch.long, torch.float]: |
| self.assertTrue(t.le(high).logical_and(t.ge(low)).all().item()) |
| |
| if dtype in [torch.float, torch.cfloat]: |
| self.assertEqual(t.requires_grad, requires_grad) |
| else: |
| self.assertFalse(t.requires_grad) |
| |
| if t.numel() > 1: |
| self.assertEqual(t.is_contiguous(), not discontiguous) |
| else: |
| self.assertTrue(t.is_contiguous()) |
| |
| for size in (tuple(), (0,), (1,), (1, 1), (2,), (2, 3), (8, 16, 32)): |
| check(size, None, None, False, False) |
| check(size, 2, 4, True, True) |
| |
| def test_assert_messages(self, device): |
| self.assertIsNone(self._get_assert_msg(msg=None)) |
| self.assertEqual("\nno_debug_msg", self._get_assert_msg("no_debug_msg")) |
| self.assertEqual("no_user_msg", self._get_assert_msg(msg=None, debug_msg="no_user_msg")) |
| self.assertEqual("debug_msg\nuser_msg", self._get_assert_msg(msg="user_msg", debug_msg="debug_msg")) |
| |
| # The following tests (test_cuda_assert_*) are added to ensure test suite terminates early |
| # when CUDA assert was thrown. Because all subsequent test will fail if that happens. |
| # These tests are slow because it spawn another process to run test suite. |
| # See: https://github.com/pytorch/pytorch/issues/49019 |
| @onlyCUDA |
| @slowTest |
| def test_cuda_assert_should_stop_common_utils_test_suite(self, device): |
| # test to ensure common_utils.py override has early termination for CUDA. |
| stderr = TestCase.runWithPytorchAPIUsageStderr("""\ |
| #!/usr/bin/env python |
| |
| import torch |
| from torch.testing._internal.common_utils import (TestCase, run_tests, slowTest) |
| |
| class TestThatContainsCUDAAssertFailure(TestCase): |
| |
| @slowTest |
| def test_throw_unrecoverable_cuda_exception(self): |
| x = torch.rand(10, device='cuda') |
| # cause unrecoverable CUDA exception, recoverable on CPU |
| y = x[torch.tensor([25])].cpu() |
| |
| @slowTest |
| def test_trivial_passing_test_case_on_cpu_cuda(self): |
| x1 = torch.tensor([0., 1.], device='cuda') |
| x2 = torch.tensor([0., 1.], device='cpu') |
| self.assertEqual(x1, x2) |
| |
| if __name__ == '__main__': |
| run_tests() |
| """) |
| # should capture CUDA error |
| self.assertIn('CUDA error: device-side assert triggered', stderr) |
| # should run only 1 test because it throws unrecoverable error. |
| self.assertIn('Ran 1 test', stderr) |
| |
| |
| @onlyCUDA |
| @slowTest |
| def test_cuda_assert_should_stop_common_device_type_test_suite(self, device): |
| # test to ensure common_device_type.py override has early termination for CUDA. |
| stderr = TestCase.runWithPytorchAPIUsageStderr("""\ |
| #!/usr/bin/env python |
| |
| import torch |
| from torch.testing._internal.common_utils import (TestCase, run_tests, slowTest) |
| from torch.testing._internal.common_device_type import instantiate_device_type_tests |
| |
| class TestThatContainsCUDAAssertFailure(TestCase): |
| |
| @slowTest |
| def test_throw_unrecoverable_cuda_exception(self, device): |
| x = torch.rand(10, device=device) |
| # cause unrecoverable CUDA exception, recoverable on CPU |
| y = x[torch.tensor([25])].cpu() |
| |
| @slowTest |
| def test_trivial_passing_test_case_on_cpu_cuda(self, device): |
| x1 = torch.tensor([0., 1.], device=device) |
| x2 = torch.tensor([0., 1.], device='cpu') |
| self.assertEqual(x1, x2) |
| |
| instantiate_device_type_tests( |
| TestThatContainsCUDAAssertFailure, |
| globals(), |
| only_for='cuda' |
| ) |
| |
| if __name__ == '__main__': |
| run_tests() |
| """) |
| # should capture CUDA error |
| self.assertIn('CUDA error: device-side assert triggered', stderr) |
| # should run only 1 test because it throws unrecoverable error. |
| self.assertIn('Ran 1 test', stderr) |
| |
| |
| @onlyCUDA |
| @slowTest |
| def test_cuda_assert_should_not_stop_common_distributed_test_suite(self, device): |
| # test to ensure common_distributed.py override should not early terminate CUDA. |
| stderr = TestCase.runWithPytorchAPIUsageStderr("""\ |
| #!/usr/bin/env python |
| |
| import torch |
| from torch.testing._internal.common_utils import (run_tests, slowTest) |
| from torch.testing._internal.common_device_type import instantiate_device_type_tests |
| from torch.testing._internal.common_distributed import MultiProcessTestCase |
| |
| class TestThatContainsCUDAAssertFailure(MultiProcessTestCase): |
| |
| @slowTest |
| def test_throw_unrecoverable_cuda_exception(self, device): |
| x = torch.rand(10, device=device) |
| # cause unrecoverable CUDA exception, recoverable on CPU |
| y = x[torch.tensor([25])].cpu() |
| |
| @slowTest |
| def test_trivial_passing_test_case_on_cpu_cuda(self, device): |
| x1 = torch.tensor([0., 1.], device=device) |
| x2 = torch.tensor([0., 1.], device='cpu') |
| self.assertEqual(x1, x2) |
| |
| instantiate_device_type_tests( |
| TestThatContainsCUDAAssertFailure, |
| globals(), |
| only_for='cuda' |
| ) |
| |
| if __name__ == '__main__': |
| run_tests() |
| """) |
| # we are currently disabling CUDA early termination for distributed tests. |
| self.assertIn('Ran 2 test', stderr) |
| |
| |
| instantiate_device_type_tests(TestTesting, globals()) |
| |
| |
| class TestMypyWrapper(TestCase): |
| def test_glob(self): |
| # can match individual files |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='test/test_torch.py', |
| filename=PurePosixPath('test/test_torch.py'), |
| )) |
| self.assertFalse(mypy_wrapper.glob( |
| pattern='test/test_torch.py', |
| filename=PurePosixPath('test/test_testing.py'), |
| )) |
| |
| # dir matters |
| self.assertFalse(mypy_wrapper.glob( |
| pattern='tools/codegen/utils.py', |
| filename=PurePosixPath('torch/nn/modules.py'), |
| )) |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='setup.py', |
| filename=PurePosixPath('setup.py'), |
| )) |
| self.assertFalse(mypy_wrapper.glob( |
| pattern='setup.py', |
| filename=PurePosixPath('foo/setup.py'), |
| )) |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='foo/setup.py', |
| filename=PurePosixPath('foo/setup.py'), |
| )) |
| |
| # can match dirs |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='torch', |
| filename=PurePosixPath('torch/random.py'), |
| )) |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='torch', |
| filename=PurePosixPath('torch/nn/cpp.py'), |
| )) |
| self.assertFalse(mypy_wrapper.glob( |
| pattern='torch', |
| filename=PurePosixPath('tools/fast_nvcc/fast_nvcc.py'), |
| )) |
| |
| # can match wildcards |
| self.assertTrue(mypy_wrapper.glob( |
| pattern='tools/autograd/*.py', |
| filename=PurePosixPath('tools/autograd/gen_autograd.py'), |
| )) |
| self.assertFalse(mypy_wrapper.glob( |
| pattern='tools/autograd/*.py', |
| filename=PurePosixPath('tools/autograd/deprecated.yaml'), |
| )) |
| |
| |
| def fakehash(char): |
| return char * 40 |
| |
| |
| def makecase(name, seconds, *, errored=False, failed=False, skipped=False): |
| return { |
| 'name': name, |
| 'seconds': seconds, |
| 'errored': errored, |
| 'failed': failed, |
| 'skipped': skipped, |
| } |
| |
| |
| def makereport(tests): |
| suites = { |
| suite_name: { |
| 'total_seconds': sum(case['seconds'] for case in cases), |
| 'cases': cases, |
| } |
| for suite_name, cases in tests.items() |
| } |
| return { |
| 'total_seconds': sum(s['total_seconds'] for s in suites.values()), |
| 'suites': suites, |
| } |
| |
| |
| class TestPrintTestStats(TestCase): |
| maxDiff = None |
| |
| def test_analysis(self): |
| head_report = makereport({ |
| # input ordering of the suites is ignored |
| 'Grault': [ |
| # not printed: status same and time similar |
| makecase('test_grault0', 4.78, failed=True), |
| # status same, but time increased a lot |
| makecase('test_grault2', 1.473, errored=True), |
| ], |
| # individual tests times changed, not overall suite |
| 'Qux': [ |
| # input ordering of the test cases is ignored |
| makecase('test_qux1', 0.001, skipped=True), |
| makecase('test_qux6', 0.002, skipped=True), |
| # time in bounds, but status changed |
| makecase('test_qux4', 7.158, failed=True), |
| # not printed because it's the same as before |
| makecase('test_qux7', 0.003, skipped=True), |
| makecase('test_qux5', 11.968), |
| makecase('test_qux3', 23.496), |
| ], |
| # new test suite |
| 'Bar': [ |
| makecase('test_bar2', 3.742, failed=True), |
| makecase('test_bar1', 50.447), |
| ], |
| # overall suite time changed but no individual tests |
| 'Norf': [ |
| makecase('test_norf1', 3), |
| makecase('test_norf2', 3), |
| makecase('test_norf3', 3), |
| makecase('test_norf4', 3), |
| ], |
| # suite doesn't show up if it doesn't change enough |
| 'Foo': [ |
| makecase('test_foo1', 42), |
| makecase('test_foo2', 56), |
| ], |
| }) |
| |
| base_reports = { |
| # bbbb has no reports, so base is cccc instead |
| fakehash('b'): [], |
| fakehash('c'): [ |
| makereport({ |
| 'Baz': [ |
| makecase('test_baz2', 13.605), |
| # no recent suites have & skip this test |
| makecase('test_baz1', 0.004, skipped=True), |
| ], |
| 'Foo': [ |
| makecase('test_foo1', 43), |
| # test added since dddd |
| makecase('test_foo2', 57), |
| ], |
| 'Grault': [ |
| makecase('test_grault0', 4.88, failed=True), |
| makecase('test_grault1', 11.967, failed=True), |
| makecase('test_grault2', 0.395, errored=True), |
| makecase('test_grault3', 30.460), |
| ], |
| 'Norf': [ |
| makecase('test_norf1', 2), |
| makecase('test_norf2', 2), |
| makecase('test_norf3', 2), |
| makecase('test_norf4', 2), |
| ], |
| 'Qux': [ |
| makecase('test_qux3', 4.978, errored=True), |
| makecase('test_qux7', 0.002, skipped=True), |
| makecase('test_qux2', 5.618), |
| makecase('test_qux4', 7.766, errored=True), |
| makecase('test_qux6', 23.589, failed=True), |
| ], |
| }), |
| ], |
| fakehash('d'): [ |
| makereport({ |
| 'Foo': [ |
| makecase('test_foo1', 40), |
| # removed in cccc |
| makecase('test_foo3', 17), |
| ], |
| 'Baz': [ |
| # not skipped, so not included in stdev |
| makecase('test_baz1', 3.14), |
| ], |
| 'Qux': [ |
| makecase('test_qux7', 0.004, skipped=True), |
| makecase('test_qux2', 6.02), |
| makecase('test_qux4', 20.932), |
| ], |
| 'Norf': [ |
| makecase('test_norf1', 3), |
| makecase('test_norf2', 3), |
| makecase('test_norf3', 3), |
| makecase('test_norf4', 3), |
| ], |
| 'Grault': [ |
| makecase('test_grault0', 5, failed=True), |
| makecase('test_grault1', 14.325, failed=True), |
| makecase('test_grault2', 0.31, errored=True), |
| ], |
| }), |
| ], |
| fakehash('e'): [], |
| fakehash('f'): [ |
| makereport({ |
| 'Foo': [ |
| makecase('test_foo3', 24), |
| makecase('test_foo1', 43), |
| ], |
| 'Baz': [ |
| makecase('test_baz2', 16.857), |
| ], |
| 'Qux': [ |
| makecase('test_qux2', 6.422), |
| makecase('test_qux4', 6.382, errored=True), |
| ], |
| 'Norf': [ |
| makecase('test_norf1', 0.9), |
| makecase('test_norf3', 0.9), |
| makecase('test_norf2', 0.9), |
| makecase('test_norf4', 0.9), |
| ], |
| 'Grault': [ |
| makecase('test_grault0', 4.7, failed=True), |
| makecase('test_grault1', 13.146, failed=True), |
| makecase('test_grault2', 0.48, errored=True), |
| ], |
| }), |
| ], |
| } |
| |
| simpler_head = print_test_stats.simplify(head_report) |
| simpler_base = {} |
| for commit, reports in base_reports.items(): |
| simpler_base[commit] = [print_test_stats.simplify(r) for r in reports] |
| analysis = print_test_stats.analyze( |
| head_report=simpler_head, |
| base_reports=simpler_base, |
| ) |
| |
| self.assertEqual( |
| '''\ |
| |
| - class Baz: |
| - # was 15.23s ± 2.30s |
| - |
| - def test_baz1: ... |
| - # was 0.004s (skipped) |
| - |
| - def test_baz2: ... |
| - # was 15.231s ± 2.300s |
| |
| |
| class Grault: |
| # was 48.86s ± 1.19s |
| # now 6.25s |
| |
| - def test_grault1: ... |
| - # was 13.146s ± 1.179s (failed) |
| |
| - def test_grault3: ... |
| - # was 30.460s |
| |
| |
| class Qux: |
| # was 41.66s ± 1.06s |
| # now 42.63s |
| |
| - def test_qux2: ... |
| - # was 6.020s ± 0.402s |
| |
| ! def test_qux3: ... |
| ! # was 4.978s (errored) |
| ! # now 23.496s |
| |
| ! def test_qux4: ... |
| ! # was 7.074s ± 0.979s (errored) |
| ! # now 7.158s (failed) |
| |
| ! def test_qux6: ... |
| ! # was 23.589s (failed) |
| ! # now 0.002s (skipped) |
| |
| + def test_qux1: ... |
| + # now 0.001s (skipped) |
| |
| + def test_qux5: ... |
| + # now 11.968s |
| |
| |
| + class Bar: |
| + # now 54.19s |
| + |
| + def test_bar1: ... |
| + # now 50.447s |
| + |
| + def test_bar2: ... |
| + # now 3.742s (failed) |
| |
| ''', |
| print_test_stats.anomalies(analysis), |
| ) |
| |
| def test_graph(self): |
| # HEAD is on master |
| self.assertEqual( |
| '''\ |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| * aaaaaaaaaa (HEAD) total time 502.99s |
| * bbbbbbbbbb (base) 1 report, total time 47.84s |
| * cccccccccc 1 report, total time 332.50s |
| * dddddddddd 0 reports |
| | |
| : |
| ''', |
| print_test_stats.graph( |
| head_sha=fakehash('a'), |
| head_seconds=502.99, |
| base_seconds={ |
| fakehash('b'): [47.84], |
| fakehash('c'): [332.50], |
| fakehash('d'): [], |
| }, |
| on_master=True, |
| ) |
| ) |
| |
| self.assertEqual( |
| '''\ |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 9988.77s |
| |/ |
| * bbbbbbbbbb (base) 121 reports, total time 7654.32s ± 55.55s |
| * cccccccccc 20 reports, total time 5555.55s ± 253.19s |
| * dddddddddd 1 report, total time 1234.56s |
| | |
| : |
| ''', |
| print_test_stats.graph( |
| head_sha=fakehash('a'), |
| head_seconds=9988.77, |
| base_seconds={ |
| fakehash('b'): [7598.77] * 60 + [7654.32] + [7709.87] * 60, |
| fakehash('c'): [5308.77] * 10 + [5802.33] * 10, |
| fakehash('d'): [1234.56], |
| }, |
| on_master=False, |
| ) |
| ) |
| |
| self.assertEqual( |
| '''\ |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 25.52s |
| | | |
| | : (5 commits) |
| |/ |
| * bbbbbbbbbb 0 reports |
| * cccccccccc 0 reports |
| * dddddddddd (base) 15 reports, total time 58.92s ± 25.82s |
| | |
| : |
| ''', |
| print_test_stats.graph( |
| head_sha=fakehash('a'), |
| head_seconds=25.52, |
| base_seconds={ |
| fakehash('b'): [], |
| fakehash('c'): [], |
| fakehash('d'): [52.25] * 14 + [152.26], |
| }, |
| on_master=False, |
| ancestry_path=5, |
| ) |
| ) |
| |
| self.assertEqual( |
| '''\ |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 0.08s |
| |/| |
| | : (1 commit) |
| | |
| * bbbbbbbbbb 0 reports |
| * cccccccccc (base) 1 report, total time 0.09s |
| * dddddddddd 3 reports, total time 0.10s ± 0.05s |
| | |
| : |
| ''', |
| print_test_stats.graph( |
| head_sha=fakehash('a'), |
| head_seconds=0.08, |
| base_seconds={ |
| fakehash('b'): [], |
| fakehash('c'): [0.09], |
| fakehash('d'): [0.05, 0.10, 0.15], |
| }, |
| on_master=False, |
| other_ancestors=1, |
| ) |
| ) |
| |
| self.assertEqual( |
| '''\ |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 5.98s |
| | | |
| | : (1 commit) |
| |/| |
| | : (7 commits) |
| | |
| * bbbbbbbbbb (base) 2 reports, total time 6.02s ± 1.71s |
| * cccccccccc 0 reports |
| * dddddddddd 10 reports, total time 5.84s ± 0.92s |
| | |
| : |
| ''', |
| print_test_stats.graph( |
| head_sha=fakehash('a'), |
| head_seconds=5.98, |
| base_seconds={ |
| fakehash('b'): [4.81, 7.23], |
| fakehash('c'): [], |
| fakehash('d'): [4.97] * 5 + [6.71] * 5, |
| }, |
| on_master=False, |
| ancestry_path=1, |
| other_ancestors=7, |
| ) |
| ) |
| |
| def test_regression_info(self): |
| self.assertEqual( |
| '''\ |
| ----- Historic stats comparison result ------ |
| |
| job: foo_job |
| commit: aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa |
| |
| |
| class Foo: |
| # was 42.50s ± 2.12s |
| # now 3.02s |
| |
| - def test_bar: ... |
| - # was 1.000s |
| |
| ! def test_foo: ... |
| ! # was 41.500s ± 2.121s |
| ! # now 0.020s (skipped) |
| |
| + def test_baz: ... |
| + # now 3.000s |
| |
| |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 3.02s |
| |/ |
| * bbbbbbbbbb (base) 1 report, total time 41.00s |
| * cccccccccc 1 report, total time 43.00s |
| | |
| : |
| |
| Removed (across 1 suite) 1 test, totaling - 1.00s |
| Modified (across 1 suite) 1 test, totaling - 41.48s ± 2.12s |
| Added (across 1 suite) 1 test, totaling + 3.00s |
| ''', |
| print_test_stats.regression_info( |
| head_sha=fakehash('a'), |
| head_report=makereport({ |
| 'Foo': [ |
| makecase('test_foo', 0.02, skipped=True), |
| makecase('test_baz', 3), |
| ]}), |
| base_reports={ |
| fakehash('b'): [ |
| makereport({ |
| 'Foo': [ |
| makecase('test_foo', 40), |
| makecase('test_bar', 1), |
| ], |
| }), |
| ], |
| fakehash('c'): [ |
| makereport({ |
| 'Foo': [ |
| makecase('test_foo', 43), |
| ], |
| }), |
| ], |
| }, |
| job_name='foo_job', |
| on_master=False, |
| ancestry_path=0, |
| other_ancestors=0, |
| ) |
| ) |
| |
| def test_regression_info_new_job(self): |
| self.assertEqual( |
| '''\ |
| ----- Historic stats comparison result ------ |
| |
| job: foo_job |
| commit: aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa |
| |
| |
| + class Foo: |
| + # now 3.02s |
| + |
| + def test_baz: ... |
| + # now 3.000s |
| + |
| + def test_foo: ... |
| + # now 0.020s (skipped) |
| |
| |
| Commit graph (base is most recent master ancestor with at least one S3 report): |
| |
| : (master) |
| | |
| | * aaaaaaaaaa (HEAD) total time 3.02s |
| | | |
| | : (3 commits) |
| |/| |
| | : (2 commits) |
| | |
| * bbbbbbbbbb 0 reports |
| * cccccccccc 0 reports |
| | |
| : |
| |
| Removed (across 0 suites) 0 tests, totaling 0.00s |
| Modified (across 0 suites) 0 tests, totaling 0.00s |
| Added (across 1 suite) 2 tests, totaling + 3.02s |
| ''', |
| print_test_stats.regression_info( |
| head_sha=fakehash('a'), |
| head_report=makereport({ |
| 'Foo': [ |
| makecase('test_foo', 0.02, skipped=True), |
| makecase('test_baz', 3), |
| ]}), |
| base_reports={ |
| fakehash('b'): [], |
| fakehash('c'): [], |
| }, |
| job_name='foo_job', |
| on_master=False, |
| ancestry_path=3, |
| other_ancestors=2, |
| ) |
| ) |
| |
| |
| if __name__ == '__main__': |
| run_tests() |
