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Enable tests in test_pytorch_onnx_onnxruntime #37868

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Enable tests in test_pytorch_onnx_onnxruntime #37868

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3500599
enable tests for einsum, softmaxcrossentropy, nllloss
KsenijaS May 5, 2020
3f5129b
Merge https://github.com/pytorch/pytorch into nllloss_tests
KsenijaS May 8, 2020
b22076d
Merge https://github.com/pytorch/pytorch into nllloss_tests
KsenijaS May 15, 2020
2d3276f
enable more tests
KsenijaS May 15, 2020
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15 changes: 1 addition & 14 deletions test/onnx/test_pytorch_onnx_onnxruntime.py
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Expand Up @@ -771,7 +771,6 @@ def forward(self, x):
x = torch.randn(3, 4, 5, 6, 7)
self.run_test(NegSlice(), x)

@unittest.skip('https://github.com/pytorch/pytorch/issues/10984')
def test_slice_neg_large_negone(self):
class NegSlice(torch.nn.Module):
def forward(self, x):
Expand Down Expand Up @@ -822,7 +821,6 @@ def forward(self, x):
'output_1': [0, 1, 2]})

@skipIfUnsupportedMinOpsetVersion(9)
@unittest.skip("relies on not constant folding size calls, but other tests rely on constant folding")
def test_arange_dynamic(self):
class ArangeModel(torch.nn.Module):
def forward(self, input):
Expand Down Expand Up @@ -1312,7 +1310,6 @@ def test_interpolate_downsample(self):
self._interpolate_tests(False)

@skipIfUnsupportedMinOpsetVersion(11)
@unittest.skip("Interpolate script NYI")
def test_interpolate_no_shape(self):
class MyModel(torch.jit.ScriptModule):
@torch.jit.script_method
Expand Down Expand Up @@ -1524,7 +1521,7 @@ def forward(self, x, k):
k = torch.tensor(3)
self.run_test(MyModuleDynamic(), [x, k])

@skipIfUnsupportedOpsetVersion([7, 12])
@skipIfUnsupportedOpsetVersion([7])
def test_normalize(self):
class Model(torch.nn.Module):
def forward(self, x):
Expand Down Expand Up @@ -2424,7 +2421,6 @@ def forward(self, x):
x = torch.randn(3, 4, 5, requires_grad=True)
self.run_test(MaskedSelectModel(), x)

@unittest.skip("Enable this once depthToSpace attr 'mode' is supported in ORT")
@skipIfUnsupportedMinOpsetVersion(9)
def test_pixel_shuffle(self):
class PixelShuffle(torch.nn.Module):
Expand Down Expand Up @@ -2815,7 +2811,6 @@ def forward(self, input):
self.run_test(DimModel(), empty_input)
self.run_test(DimModel(), multi_dim_input)

@unittest.skip("Enable this once einsum supported in ORT")
@skipIfUnsupportedMinOpsetVersion(12)
def test_einsum(self):
class EinsumModelBatchDiagonal(torch.nn.Module):
Expand Down Expand Up @@ -2852,7 +2847,6 @@ def forward(self, *tensor_list):
x = torch.randn(3, 4)
self.run_test(EinsumModelTranspose(), input=(x,))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_crossentropyloss(self):
x = torch.randn(3, 5)
Expand Down Expand Up @@ -3004,7 +2998,6 @@ def forward(self, input):
x = torch.randn(1, 2, 3, requires_grad=True)
self.run_test(EmptyBranchModel(), x)

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3022,7 +3015,6 @@ def forward(self, input, target):
target = torch.empty(N, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_none(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3041,7 +3033,6 @@ def forward(self, input, target):
target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_mean(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3060,7 +3051,6 @@ def forward(self, input, target):
target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_sum(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3079,7 +3069,6 @@ def forward(self, input, target):
target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_mean_weights(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3098,7 +3087,6 @@ def forward(self, input, target):
target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_mean_ignore_index(self):
class NLLModel(torch.nn.Module):
Expand All @@ -3117,7 +3105,6 @@ def forward(self, input, target):
target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
self.run_test(NLLModel(), (input, target))

@unittest.skip("Enable this once ORT version is updated")
@skipIfUnsupportedMinOpsetVersion(12)
def test_nllloss_2d_mean_ignore_index_weights(self):
class NLLModel(torch.nn.Module):
Expand Down