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Fix generation config for empty state dict (#21630)
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@ -2648,7 +2648,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
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_from_pipeline=from_pipeline,
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**kwargs,
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)
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except OSError:
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except (OSError, TypeError):
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logger.info(
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"Generation config file not found, using a generation config created from the model config."
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)
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@ -325,6 +325,18 @@ class ModelTesterMixin:
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else:
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check_save_load(first, second)
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def test_from_pretrained_no_checkpoint(self):
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config, _ = self.model_tester.prepare_config_and_inputs_for_common()
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for model_class in self.all_model_classes:
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model = model_class(config)
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state_dict = model.state_dict()
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new_model = model_class.from_pretrained(
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pretrained_model_name_or_path=None, config=config, state_dict=state_dict
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)
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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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def test_save_load_keys_to_ignore_on_save(self):
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config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
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@ -2776,15 +2788,6 @@ 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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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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# float dtype. To make it happen config.torch_dtype needs to be set before instantiating the
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