remove nan in head masking test
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@@ -194,6 +194,9 @@ class CommonTestCases:
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hidden_states = outputs[-2]
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# Remove Nan
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for t in attentions:
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self.assertLess(torch.sum(torch.isnan(t)), t.numel() / 4) # Check we don't have more than 25% nans (arbitrary)
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attentions = [t.masked_fill(torch.isnan(t), 0.0) for t in attentions] # remove them (the test is less complete)
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self.assertIsNotNone(multihead_outputs)
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self.assertEqual(len(multihead_outputs), self.model_tester.num_hidden_layers)
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