




'''simple docstring'''







import unittest

from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow


if is_flax_available():
      import jax

      from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
      from transformers.models.bert.modeling_flax_bert import FlaxBertModel
      from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel







@require_flax
class 					_a (unittest.TestCase	):





     '''simple docstring'''



     @slow
     def 			snake_case_      (				self							)      ->				str:
          for model_name in ["bert-base-cased", "bert-large-uncased"]:
               with self.subTest(__a							):
                    snake_case			:      Optional[Any]        =			AutoConfig.from_pretrained(__a							)
                    self.assertIsNotNone(__a							)
                    self.assertIsInstance(__a							,__a							)

                    snake_case			:      Tuple        =			FlaxAutoModel.from_pretrained(__a							)
                    self.assertIsNotNone(__a							)
                    self.assertIsInstance(__a							,__a							)







     @slow
     def 			snake_case_      (				self							)      ->				Optional[Any]:
          for model_name in ["roberta-base", "roberta-large"]:
               with self.subTest(__a							):
                    snake_case			:      Tuple        =			AutoConfig.from_pretrained(__a							)
                    self.assertIsNotNone(__a							)
                    self.assertIsInstance(__a							,__a							)

                    snake_case			:      Optional[int]        =			FlaxAutoModel.from_pretrained(__a							)
                    self.assertIsNotNone(__a							)
                    self.assertIsInstance(__a							,__a							)







     @slow
     def 			snake_case_      (				self							)      ->				List[str]:
          for model_name in ["bert-base-cased", "bert-large-uncased"]:
               snake_case			:      Tuple        =			AutoTokenizer.from_pretrained(__a							)
               snake_case			:      Tuple        =			FlaxBertModel.from_pretrained(__a							)
               snake_case			:      Dict        =			tokenizer("""Do you support jax jitted function?"""							,return_tensors=TensorType.JAX							)

               @jax.jit
               def eval(**__a							):
                    return model(**__a							)

               eval(**__a							).block_until_ready()







     @slow
     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          for model_name in ["roberta-base", "roberta-large"]:
               snake_case			:      Union[str, Any]        =			AutoTokenizer.from_pretrained(__a							)
               snake_case			:      str        =			FlaxRobertaModel.from_pretrained(__a							)
               snake_case			:      Tuple        =			tokenizer("""Do you support jax jitted function?"""							,return_tensors=TensorType.JAX							)

               @jax.jit
               def eval(**__a							):
                    return model(**__a							)

               eval(**__a							).block_until_ready()







     def 			snake_case_      (				self							)      ->				Dict:
          with self.assertRaisesRegex(
              __a							,"""bert-base is not a local folder and is not a valid model identifier"""							):
               snake_case			:      Optional[int]        =			FlaxAutoModel.from_pretrained("""bert-base"""							)







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          with self.assertRaisesRegex(
              __a							,r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""							):
               snake_case			:      Union[str, Any]        =			FlaxAutoModel.from_pretrained(__a							,revision="""aaaaaa"""							)







     def 			snake_case_      (				self							)      ->				Union[str, Any]:
          with self.assertRaisesRegex(
              __a							,"""hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack"""							,):
               snake_case			:      int        =			FlaxAutoModel.from_pretrained("""hf-internal-testing/config-no-model"""							)







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          with self.assertRaisesRegex(__a							,"""Use `from_pt=True` to load this model"""							):
               snake_case			:      Any        =			FlaxAutoModel.from_pretrained("""hf-internal-testing/tiny-bert-pt-only"""							)









'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase      :   Optional[int]      =       {
    """configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase      :   int      =       [
          """PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """PegasusXForConditionalGeneration""",
          """PegasusXModel""",
          """PegasusXPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_pegasus_x import PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP, PegasusXConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_pegasus_x import (
                PEGASUS_X_PRETRAINED_MODEL_ARCHIVE_LIST,
                PegasusXForConditionalGeneration,
                PegasusXModel,
                PegasusXPreTrainedModel,
            )


else:
      import sys

      lowercase      :   Optional[Any]      =       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



