use torch.testing.assertclose instead to get more details about error in cis (#35659)
* use torch.testing.assertclose instead to get more details about error in cis * fix * style * test_all * revert for I bert * fixes and updates * more image processing fixes * more image processors * fix mamba and co * style * less strick * ok I won't be strict * skip and be done * up
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@@ -525,7 +525,7 @@ class WavLMModelIntegrationTest(unittest.TestCase):
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EXPECTED_HIDDEN_STATES_SLICE = torch.tensor(
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[[[0.0577, 0.1161], [0.0579, 0.1165]], [[0.0199, 0.1237], [0.0059, 0.0605]]]
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)
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self.assertTrue(torch.allclose(hidden_states_slice, EXPECTED_HIDDEN_STATES_SLICE, atol=5e-2))
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torch.testing.assert_close(hidden_states_slice, EXPECTED_HIDDEN_STATES_SLICE, rtol=5e-2, atol=5e-2)
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def test_inference_large(self):
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model = WavLMModel.from_pretrained("microsoft/wavlm-large").to(torch_device)
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@@ -549,7 +549,7 @@ class WavLMModelIntegrationTest(unittest.TestCase):
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[[[0.2122, 0.0500], [0.2118, 0.0563]], [[0.1353, 0.1818], [0.2453, 0.0595]]]
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)
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self.assertTrue(torch.allclose(hidden_states_slice, EXPECTED_HIDDEN_STATES_SLICE, rtol=5e-2))
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torch.testing.assert_close(hidden_states_slice, EXPECTED_HIDDEN_STATES_SLICE, rtol=5e-2)
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def test_inference_diarization(self):
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model = WavLMForAudioFrameClassification.from_pretrained("microsoft/wavlm-base-plus-sd").to(torch_device)
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@@ -576,7 +576,7 @@ class WavLMModelIntegrationTest(unittest.TestCase):
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)
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self.assertEqual(labels[0, :, 0].sum(), 258)
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self.assertEqual(labels[0, :, 1].sum(), 647)
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self.assertTrue(torch.allclose(outputs.logits[:, :4], expected_logits, atol=1e-2))
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torch.testing.assert_close(outputs.logits[:, :4], expected_logits, rtol=1e-2, atol=1e-2)
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def test_inference_speaker_verification(self):
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model = WavLMForXVector.from_pretrained("microsoft/wavlm-base-plus-sv").to(torch_device)
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