Fix from_pretrained API with config and state_dict (#21542)
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@@ -2749,6 +2749,15 @@ class ModelUtilsTest(TestCasePlus):
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BertModel.from_pretrained(TINY_T5)
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self.assertTrue("You are using a model of type t5 to instantiate a model of type bert" in cl.out)
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def test_model_from_pretrained_no_checkpoint(self):
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config = BertConfig.from_pretrained("hf-internal-testing/tiny-random-bert")
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model = BertModel(config)
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state_dict = model.state_dict()
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new_model = BertModel.from_pretrained(pretrained_model_name_or_path=None, config=config, state_dict=state_dict)
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for p1, p2 in zip(model.parameters(), new_model.parameters()):
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self.assertTrue(torch.equal(p1, p2))
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@require_torch
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def test_model_from_config_torch_dtype(self):
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# test that the model can be instantiated with dtype of user's choice - as long as it's a
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