





from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def 							UpperCAmelCase_  (						):
   lowercase_      :str         =			HfArgumentParser(lowercase_			)
   lowercase_      :Tuple         =			parser.parse_args_into_dataclasses()[0]
   lowercase_      :List[Any]         =			TensorFlowBenchmark(args=lowercase_			)
   try:
      lowercase_      :Optional[Any]         =			parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      lowercase_      :Union[str, Any]         =			"Arg --no_{0} is no longer used, please use --no-{0} instead."
      lowercase_      :Any         =			" ".join(str(lowercase_			).split(" "			)[:-1]			)
      lowercase_      :List[Any]         =			""
      lowercase_      :int         =			eval(str(lowercase_			).split(" "			)[-1]			)
      lowercase_      :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:
         lowercase_      :Tuple         =			full_error_msg + begin_error_msg + str(lowercase_			)
      raise ValueError(lowercase_			)
   benchmark.run()


if __name__ == "__main__":
 main()









'''simple docstring'''


# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase :					Dict 							={
    '''configuration_xmod''': [
        '''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XmodConfig''',
        '''XmodOnnxConfig''',
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Union[str, Any] 							=[
     '''XMOD_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''XmodForCausalLM''',
     '''XmodForMaskedLM''',
     '''XmodForMultipleChoice''',
     '''XmodForQuestionAnswering''',
     '''XmodForSequenceClassification''',
     '''XmodForTokenClassification''',
     '''XmodModel''',
     '''XmodPreTrainedModel''',
 ]

if TYPE_CHECKING:
 from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_xmod import (
      XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
      XmodForCausalLM,
      XmodForMaskedLM,
      XmodForMultipleChoice,
      XmodForQuestionAnswering,
      XmodForSequenceClassification,
      XmodForTokenClassification,
      XmodModel,
      XmodPreTrainedModel,
  )

else:
 import sys

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


