
'''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						):





     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[Any]:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   int					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   List[str]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				int:






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             with self.subTest(SCREAMING_SNAKE_CASE	):
                 A       :   Any					=						AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

                 A       :   Any					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE	)
                 self.assertIsNotNone(SCREAMING_SNAKE_CASE	)
                 self.assertIsInstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         for model_name in ["bert-base-cased", "bert-large-uncased"]:
             A       :   Optional[int]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   List[str]					=						FlaxBertModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Optional[Any]					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

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

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[str]:






         """simple docstring"""






         for model_name in ["roberta-base", "roberta-large"]:
             A       :   List[str]					=						AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   Union[str, Any]					=						FlaxRobertaModel.from_pretrained(SCREAMING_SNAKE_CASE	)
             A       :   int					=						tokenizer('''Do you support jax jitted function?'''						,			return_tensors=TensorType.JAX	)

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

             eval(**SCREAMING_SNAKE_CASE	).block_until_ready()





     def 				__lowerCAmelCase							(							self	) ->				List[str]:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''bert-base is not a local folder and is not a valid model identifier'''	):
             A       :   List[Any]					=						FlaxAutoModel.from_pretrained('''bert-base'''	)





     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''	):
             A       :   Optional[int]					=						FlaxAutoModel.from_pretrained(SCREAMING_SNAKE_CASE						,			revision='''aaaaaa'''	)





     def 				__lowerCAmelCase							(							self	) ->				str:






         """simple docstring"""






         with self.assertRaisesRegex(
             SCREAMING_SNAKE_CASE						,			'''hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack'''						,			):
             A       :   List[str]					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/config-no-model'''	)





     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         with self.assertRaisesRegex(SCREAMING_SNAKE_CASE						,			'''Use `from_pt=True` to load this model'''	):
             A       :   Any					=						FlaxAutoModel.from_pretrained('''hf-internal-testing/tiny-bert-pt-only'''	)








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_snake_case             =     {
    '''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''VisionEncoderDecoderOnnxConfig''']
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''VisionEncoderDecoderModel''']

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''TFVisionEncoderDecoderModel''']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case             =     ['''FlaxVisionEncoderDecoderModel''']

if TYPE_CHECKING:
   from .configuration_vision_encoder_decoder import VisionEncoderDecoderConfig, VisionEncoderDecoderOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_vision_encoder_decoder import VisionEncoderDecoderModel

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_vision_encoder_decoder import TFVisionEncoderDecoderModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_vision_encoder_decoder import FlaxVisionEncoderDecoderModel

else:
   import sys

   _snake_case             =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



