


'''simple docstring'''

from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments

def 							__magic_name__(  ):
						__lowerCAmelCase											= HfArgumentParser(a_)
						__lowerCAmelCase											= parser.parse_args_into_dataclasses()[0]
						__lowerCAmelCase											= TensorFlowBenchmark(args=a_)
						try:
												__lowerCAmelCase											= parser.parse_args_into_dataclasses()[0]
						except ValueError as e:
												__lowerCAmelCase											= '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
												__lowerCAmelCase											= ''' '''.join(str(a_).split(''' ''')[:-1])
												__lowerCAmelCase											= ''''''
												__lowerCAmelCase											= eval(str(a_).split(''' ''')[-1])
												__lowerCAmelCase											= []
												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(a_)
												if len(a_) > 0:
																		__lowerCAmelCase											= full_error_msg + begin_error_msg + str(a_)
												raise ValueError(a_)
						benchmark.run()


if __name__ == "__main__":
	main()








"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase_								=		{
    "configuration_blip_2": [
        "BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "Blip2Config",
        "Blip2QFormerConfig",
        "Blip2VisionConfig",
    ],
    "processing_blip_2": ["Blip2Processor"],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowerCamelCase_								=		[
      "BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST",
      "Blip2Model",
      "Blip2QFormerModel",
      "Blip2PreTrainedModel",
      "Blip2ForConditionalGeneration",
      "Blip2VisionModel",
  ]

if TYPE_CHECKING:
  from .configuration_blip_a import (
      BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BlipaConfig,
      BlipaQFormerConfig,
      BlipaVisionConfig,
  )
  from .processing_blip_a import BlipaProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_blip_a import (
        BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
        BlipaForConditionalGeneration,
        BlipaModel,
        BlipaPreTrainedModel,
        BlipaQFormerModel,
        BlipaVisionModel,
    )

else:
  import sys

  lowerCamelCase_								=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)