






from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_tf_available():
       import tensorflow as tf


a						:			Tuple     	=					logging.get_logger(__name__)
@dataclass
class        a       (					lowercase__  ):



      """simple docstring"""


      a    :					List[str]							=      [
          'no_inference',
          'no_cuda',
          'no_tpu',
          'no_speed',
          'no_memory',
          'no_env_print',
          'no_multi_process',
      ]
      def __init__( self   :     Union[str, Any]						, **__lowercase   :     List[Any]   )				-> Dict:
        for deprecated_arg in self.deprecated_args:
          if deprecated_arg in kwargs:
            __UpperCAmelCase				:      Any	 =    deprecated_arg[3:]
            __UpperCAmelCase				:      List[Any]	 =    not kwargs.pop(__lowercase   )
            logger.warning(
                f"""{deprecated_arg} is depreciated. Please use --no-{positive_arg} or"""
                f""" {positive_arg}={kwargs[positive_arg]}"""   )
        __UpperCAmelCase				:      Tuple	 =    kwargs.pop("""tpu_name"""						, self.tpu_name   )
        __UpperCAmelCase				:      str	 =    kwargs.pop("""device_idx"""						, self.device_idx   )
        __UpperCAmelCase				:      Tuple	 =    kwargs.pop("""eager_mode"""						, self.eager_mode   )
        __UpperCAmelCase				:      Optional[Any]	 =    kwargs.pop("""use_xla"""						, self.use_xla   )
        super().__init__(**__lowercase   )

      a    :					str							=      field(
          default=lowercase__				,			metadata={'help': 'Name of TPU'}				,			)
      a    :					int							=      field(
          default=0				,			metadata={'help': 'CPU / GPU device index. Defaults to 0.'}				,			)
      a    :					bool							=      field(default=lowercase__				,			metadata={'help': 'Benchmark models in eager model.'}  )
      a    :					bool							=      field(
          default=lowercase__				,			metadata={
              'help': 'Benchmark models using XLA JIT compilation. Note that `eager_model` has to be set to `False`.'
          }				,			)
      @cached_property
      def       UpperCAmelCase ( self   :     int   )				-> Tuple["tf.distribute.cluster_resolver.TPUClusterResolver"]:
        requires_backends(self						, ["""tf"""]   )
        __UpperCAmelCase				:      List[str]	 =    None
        if self.tpu:
          try:
            if self.tpu_name:
              __UpperCAmelCase				:      int	 =    tf.distribute.cluster_resolver.TPUClusterResolver(self.tpu_name   )
            else:
              __UpperCAmelCase				:      Optional[int]	 =    tf.distribute.cluster_resolver.TPUClusterResolver()
          except ValueError:
            __UpperCAmelCase				:      Any	 =    None
        return tpu
      @cached_property
      def       UpperCAmelCase ( self   :     List[str]   )				-> Tuple["tf.distribute.Strategy", "tf.distribute.cluster_resolver.TPUClusterResolver"]:
        requires_backends(self						, ["""tf"""]   )
        if self.is_tpu:
          tf.config.experimental_connect_to_cluster(self._setup_tpu   )
          tf.tpu.experimental.initialize_tpu_system(self._setup_tpu   )

          __UpperCAmelCase				:      Tuple	 =    tf.distribute.TPUStrategy(self._setup_tpu   )
        else:
          # currently no multi gpu is allowed
          if self.is_gpu:
            # TODO: Currently only single GPU is supported
            tf.config.set_visible_devices(self.gpu_list[self.device_idx]						, """GPU"""   )
            __UpperCAmelCase				:      Tuple	 =    tf.distribute.OneDeviceStrategy(device=f"""/gpu:{self.device_idx}"""   )
          else:
            tf.config.set_visible_devices([]						, """GPU"""   )  # disable GPU
            __UpperCAmelCase				:      int	 =    tf.distribute.OneDeviceStrategy(device=f"""/cpu:{self.device_idx}"""   )

        return strategy
      @property
      def       UpperCAmelCase ( self   :     Optional[Any]   )				-> bool:
        requires_backends(self						, ["""tf"""]   )
        return self._setup_tpu is not None
      @property
      def       UpperCAmelCase ( self   :     Dict   )				-> "tf.distribute.Strategy":
        requires_backends(self						, ["""tf"""]   )
        return self._setup_strategy
      @property
      def       UpperCAmelCase ( self   :     Any   )				-> int:
        requires_backends(self						, ["""tf"""]   )
        return tf.config.list_physical_devices("""GPU"""   )
      @property
      def       UpperCAmelCase ( self   :     List[Any]   )				-> int:
        requires_backends(self						, ["""tf"""]   )
        if self.cuda:
          return len(self.gpu_list   )
        return 0




      @property
      def       UpperCAmelCase ( self   :     str   )				-> bool:
        return self.n_gpu > 0










from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class     lowerCamelCase_					(   lowerCamelCase			):
				a__       							=	''''''
				a__       							=	'''hf-legacy'''  # "hf://"" is reserved for hffs







				def __init__(    self							,       __lowerCAmelCase = None							,       __lowerCAmelCase = None							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								super().__init__(self							,       **__lowerCAmelCase  )
								__magic_name__		:List[Any]   =   repo_info
								__magic_name__		:Dict   =   token
								__magic_name__		:Optional[Any]   =   None







				def       A						(    self  ):
								"""simple docstring"""
								if self.dir_cache is None:
												__magic_name__		:Any   =   {}
												for hf_file in self.repo_info.siblings:
																# TODO(QL): add sizes
																__magic_name__		:Optional[int]   =   {
																    '''name''': hf_file.rfilename,
																    '''size''': None,
																    '''type''': '''file''',
																}
																self.dir_cache.update(
																    {
																        str(__lowerCAmelCase  ): {'''name''': str(__lowerCAmelCase  ), '''size''': None, '''type''': '''directory'''}
																        for d in list(PurePosixPath(hf_file.rfilename  ).parents  )[:-1]
																    }  )







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase = "rb"							,       **__lowerCAmelCase							,       ):
								"""simple docstring"""
								if not isinstance(self.repo_info							,       __lowerCAmelCase  ):
												raise NotImplementedError(F'''Open is only implemented for dataset repositories, but got {self.repo_info}'''  )
								__magic_name__		:Union[str, Any]   =   hf_hub_url(self.repo_info.id							,       __lowerCAmelCase							,       revision=self.repo_info.sha  )
								return fsspec.open(
								    __lowerCAmelCase							,       mode=__lowerCAmelCase							,       headers=get_authentication_headers_for_url(__lowerCAmelCase							,       use_auth_token=self.token  )							,       client_kwargs={'''trust_env''': True}							,       ).open()







				def       A						(    self							,       __lowerCAmelCase							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								self._get_dirs()
								__magic_name__		:str   =   self._strip_protocol(__lowerCAmelCase  )
								if path in self.dir_cache:
												return self.dir_cache[path]
								else:
												raise FileNotFoundError(__lowerCAmelCase  )







				def       A						(    self							,       __lowerCAmelCase							,       __lowerCAmelCase=False							,       **__lowerCAmelCase  ):
								"""simple docstring"""
								self._get_dirs()
								__magic_name__		:Union[str, Any]   =   PurePosixPath(path.strip('''/'''  )  )
								__magic_name__		:Dict   =   {}
								for p, f in self.dir_cache.items():
												__magic_name__		:int   =   PurePosixPath(p.strip('''/'''  )  )
												__magic_name__		:Tuple   =   p.parent
												if root == path:
																__magic_name__		:Optional[Any]   =   f
								__magic_name__		:List[Any]   =   list(paths.values()  )
								if detail:
												return out
								else:
												return sorted(f['''name'''] for f in out  )






