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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@@ -359,7 +359,7 @@ class GPTNeoXModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMi
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# Dynamic scaling does not change the RoPE embeddings until it receives an input longer than the original
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# maximum sequence length, so the outputs for the short input should match.
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if scaling_type == "dynamic":
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self.assertTrue(torch.allclose(original_short_output, scaled_short_output, atol=1e-5))
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torch.testing.assert_close(original_short_output, scaled_short_output, rtol=1e-5, atol=1e-5)
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else:
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self.assertFalse(torch.allclose(original_short_output, scaled_short_output, atol=1e-5))
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@@ -472,4 +472,4 @@ class GPTNeoXLanguageGenerationTest(unittest.TestCase):
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# alternative: tokenizer('<|im_start|>system\nA chat between')
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input_ids = torch.as_tensor(input_ids)[None].to(torch_device)
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outputs = model(input_ids)["logits"][:, -1][0, :30]
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self.assertTrue(torch.allclose(EXPECTED_LOGITS, outputs, atol=1e-5))
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torch.testing.assert_close(EXPECTED_LOGITS, outputs, rtol=1e-5, atol=1e-5)
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