


from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch





@require_torch
@require_tf
class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    def 					_lowerCamelCase (	self				:   Optional[Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Dict						=   SMALL_MODEL_IDENTIFIER
       UpperCAmelCase_							:      Union[str, Any]						=   '''pt'''
       UpperCAmelCase_							:      List[Any]						=   '''tf'''





    def 					_lowerCamelCase (	self				:   Optional[int]       ,   __snake_case				:   int	):





       '''simple docstring'''
       UpperCAmelCase_							:      Union[str, Any]						=   AutoModel.from_pretrained(self.test_model	)
       model_pt.save_pretrained(__snake_case	)





    def 					_lowerCamelCase (	self				:   List[str]       ,   __snake_case				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      int						=   TFAutoModel.from_pretrained(self.test_model       ,   from_pt=__snake_case	)
       model_tf.save_pretrained(__snake_case	)





    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      int						=   '''mock_framework'''

       # Framework provided - return whatever the user provides
       UpperCAmelCase_							:      Union[str, Any]						=   FeaturesManager.determine_framework(self.test_model       ,   __snake_case	)
       self.assertEqual(__snake_case       ,   __snake_case	)

       # Local checkpoint and framework provided - return provided framework
       # PyTorch checkpoint
       with TemporaryDirectory() as local_pt_ckpt:
          self._setup_pt_ckpt(__snake_case	)
          UpperCAmelCase_							:      Optional[Any]						=   FeaturesManager.determine_framework(__snake_case       ,   __snake_case	)
          self.assertEqual(__snake_case       ,   __snake_case	)

       # TensorFlow checkpoint
       with TemporaryDirectory() as local_tf_ckpt:
          self._setup_tf_ckpt(__snake_case	)
          UpperCAmelCase_							:      Union[str, Any]						=   FeaturesManager.determine_framework(__snake_case       ,   __snake_case	)
          self.assertEqual(__snake_case       ,   __snake_case	)





    def 					_lowerCamelCase (	self				:   List[Any]	):





       '''simple docstring'''
       # PyTorch checkpoint
       with TemporaryDirectory() as local_pt_ckpt:
          self._setup_pt_ckpt(__snake_case	)
          UpperCAmelCase_							:      Tuple						=   FeaturesManager.determine_framework(__snake_case	)
          self.assertEqual(__snake_case       ,   self.framework_pt	)

       # TensorFlow checkpoint
       with TemporaryDirectory() as local_tf_ckpt:
          self._setup_tf_ckpt(__snake_case	)
          UpperCAmelCase_							:      int						=   FeaturesManager.determine_framework(__snake_case	)
          self.assertEqual(__snake_case       ,   self.framework_tf	)

       # Invalid local checkpoint
       with TemporaryDirectory() as local_invalid_ckpt:
          with self.assertRaises(__snake_case	):
             UpperCAmelCase_							:      Optional[Any]						=   FeaturesManager.determine_framework(__snake_case	)





    def 					_lowerCamelCase (	self				:   Any	):





       '''simple docstring'''
       UpperCAmelCase_							:      str						=   MagicMock(return_value=__snake_case	)
       with patch('''transformers.onnx.features.is_tf_available'''       ,   __snake_case	):
          UpperCAmelCase_							:      Optional[Any]						=   FeaturesManager.determine_framework(self.test_model	)
          self.assertEqual(__snake_case       ,   self.framework_pt	)

       # PyTorch not in environment -> use TensorFlow
       UpperCAmelCase_							:      Dict						=   MagicMock(return_value=__snake_case	)
       with patch('''transformers.onnx.features.is_torch_available'''       ,   __snake_case	):
          UpperCAmelCase_							:      Tuple						=   FeaturesManager.determine_framework(self.test_model	)
          self.assertEqual(__snake_case       ,   self.framework_tf	)

       # Both in environment -> use PyTorch
       UpperCAmelCase_							:      int						=   MagicMock(return_value=__snake_case	)
       UpperCAmelCase_							:      Tuple						=   MagicMock(return_value=__snake_case	)
       with patch('''transformers.onnx.features.is_tf_available'''       ,   __snake_case	), patch(
           '''transformers.onnx.features.is_torch_available'''       ,   __snake_case	):
          UpperCAmelCase_							:      List[Any]						=   FeaturesManager.determine_framework(self.test_model	)
          self.assertEqual(__snake_case       ,   self.framework_pt	)

       # Both not in environment -> raise error
       UpperCAmelCase_							:      Dict						=   MagicMock(return_value=__snake_case	)
       UpperCAmelCase_							:      int						=   MagicMock(return_value=__snake_case	)
       with patch('''transformers.onnx.features.is_tf_available'''       ,   __snake_case	), patch(
           '''transformers.onnx.features.is_torch_available'''       ,   __snake_case	):
          with self.assertRaises(__snake_case	):
             UpperCAmelCase_							:      str						=   FeaturesManager.determine_framework(self.test_model	)



from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def      snake_case_						( ):
   UpperCAmelCase_							:      str						=   HfArgumentParser(__lowercase       )
   UpperCAmelCase_							:      Optional[Any]						=   parser.parse_args_into_dataclasses()[0]
   UpperCAmelCase_							:      Optional[int]						=   TensorFlowBenchmark(args=__lowercase       )
   try:
      UpperCAmelCase_							:      List[Any]						=   parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      UpperCAmelCase_							:      List[Any]						=   '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
      UpperCAmelCase_							:      List[str]						=   ''' '''.join(str(__lowercase       ).split(''' '''       )[:-1]       )
      UpperCAmelCase_							:      Optional[int]						=   ''''''
      UpperCAmelCase_							:      Dict						=   eval(str(__lowercase       ).split(''' '''       )[-1]       )
      UpperCAmelCase_							:      int						=   []
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]       )
         else:
            wrong_args.append(__lowercase       )
      if len(__lowercase       ) > 0:
         UpperCAmelCase_							:      Tuple						=   full_error_msg + begin_error_msg + str(__lowercase       )
      raise ValueError(__lowercase       )
   benchmark.run()


if __name__ == "__main__":
       main()