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neginraoofneginraoof
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Update test_pytorch_onnx_onnxruntime.py
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‎test/onnx/test_pytorch_onnx_onnxruntime.py‎

Lines changed: 6 additions & 0 deletions
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@@ -3001,6 +3001,7 @@ def forward(self, input, target):
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target = torch.empty(N, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_none(self):
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class NLLModel(torch.nn.Module):
@@ -3019,6 +3020,7 @@ def forward(self, input, target):
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target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_mean(self):
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class NLLModel(torch.nn.Module):
@@ -3037,6 +3039,7 @@ def forward(self, input, target):
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target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_sum(self):
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class NLLModel(torch.nn.Module):
@@ -3055,6 +3058,7 @@ def forward(self, input, target):
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target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_mean_weights(self):
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class NLLModel(torch.nn.Module):
@@ -3073,6 +3077,7 @@ def forward(self, input, target):
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target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_mean_ignore_index(self):
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class NLLModel(torch.nn.Module):
@@ -3091,6 +3096,7 @@ def forward(self, input, target):
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target = torch.empty(N, 8, 8, dtype=torch.long).random_(0, C)
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self.run_test(NLLModel(), (input, target))
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@unittest.skip("Enable this once ORT version is updated")
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@skipIfUnsupportedMinOpsetVersion(12)
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def test_nllloss_2d_mean_ignore_index_weights(self):
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class NLLModel(torch.nn.Module):

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