Fix DeBERTa integration tests (#7729)
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@ -491,7 +491,7 @@ class DisentangledSelfAttention(torch.nn.Module):
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self.in_proj = torch.nn.Linear(config.hidden_size, self.all_head_size * 3, bias=False)
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self.q_bias = torch.nn.Parameter(torch.zeros((self.all_head_size), dtype=torch.float))
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self.v_bias = torch.nn.Parameter(torch.zeros((self.all_head_size), dtype=torch.float))
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self.pos_att_type = config.pos_att_type
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self.pos_att_type = config.pos_att_type if config.pos_att_type is not None else []
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self.relative_attention = getattr(config, "relative_attention", False)
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self.talking_head = getattr(config, "talking_head", False)
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@ -247,7 +247,6 @@ class DebertaModelIntegrationTest(unittest.TestCase):
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np.random.seed(0)
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torch.manual_seed(0)
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torch.cuda.manual_seed_all(0)
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DebertaModel.base_model_prefix = "bert"
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model = DebertaModel.from_pretrained("microsoft/deberta-base")
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input_ids = torch.tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
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@ -257,17 +256,3 @@ class DebertaModelIntegrationTest(unittest.TestCase):
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[[[-0.0218, -0.6641, -0.3665], [-0.3907, -0.4716, -0.6640], [0.7461, 1.2570, -0.9063]]]
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)
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self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-4), f"{output[:, :3, :3]}")
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@slow
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def test_inference_classification_head(self):
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random.seed(0)
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np.random.seed(0)
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torch.manual_seed(0)
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torch.cuda.manual_seed_all(0)
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model = DebertaForSequenceClassification.from_pretrained("microsoft/deberta-base")
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input_ids = torch.tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
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output = model(input_ids)[0]
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expected_shape = torch.Size((1, 2))
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self.assertEqual(output.shape, expected_shape)
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expected_tensor = torch.tensor([[0.0884, -0.1047]])
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self.assertTrue(torch.allclose(output, expected_tensor, atol=1e-4), f"{output}")
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