






"""simple docstring"""






import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List

from ..utils import logging


UpperCAmelCase_   : str   			= logging.get_logger(__name__)



def 					_A			(__a=None    ,				__a=None							) ->       int:
    """simple docstring"""






    return field(default_factory=lambda: default    ,				metadata=__a							)





@dataclass
class 							lowerCAmelCase__				:






      '''simple docstring'''

      __UpperCamelCase	 =  list_field(
          default=[]				,		metadata={
              "help": (
                  "Model checkpoints to be provided to the AutoModel classes. Leave blank to benchmark the base version"
                  " of all available models"
              )
          }				,		)

      __UpperCamelCase	 =  list_field(
          default=[8]				,		metadata={"help": "List of batch sizes for which memory and time performance will be evaluated"} )

      __UpperCamelCase	 =  list_field(
          default=[8, 3_2, 1_2_8, 5_1_2]				,		metadata={"help": "List of sequence lengths for which memory and time performance will be evaluated"}				,		)

      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={"help": "Whether to benchmark inference of model. Inference can be disabled via --no-inference."}				,		)
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={"help": "Whether to run on available cuda devices. Cuda can be disabled via --no-cuda."}				,		)
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={"help": "Whether to run on available tpu devices. TPU can be disabled via --no-tpu."} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Use FP16 to accelerate inference."} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Benchmark training of model"} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Verbose memory tracing"} )
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={"help": "Whether to perform speed measurements. Speed measurements can be disabled via --no-speed."}				,		)
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={
              "help": "Whether to perform memory measurements. Memory measurements can be disabled via --no-memory"
          }				,		)
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Trace memory line by line"} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Save result to a CSV file"} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Save all print statements in a log file"} )
      __UpperCamelCase	 =  field(default=UpperCAmelCase__				,		metadata={"help": "Whether to print environment information"} )
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={
              "help": (
                  "Whether to use multiprocessing for memory and speed measurement. It is highly recommended to use"
                  " multiprocessing for accurate CPU and GPU memory measurements. This option should only be disabled"
                  " for debugging / testing and on TPU."
              )
          }				,		)
      __UpperCamelCase	 =  field(
          default=f'''inference_time_{round(time() )}.csv'''				,		metadata={"help": "CSV filename used if saving time results to csv."}				,		)
      __UpperCamelCase	 =  field(
          default=f'''inference_memory_{round(time() )}.csv'''				,		metadata={"help": "CSV filename used if saving memory results to csv."}				,		)
      __UpperCamelCase	 =  field(
          default=f'''train_time_{round(time() )}.csv'''				,		metadata={"help": "CSV filename used if saving time results to csv for training."}				,		)
      __UpperCamelCase	 =  field(
          default=f'''train_memory_{round(time() )}.csv'''				,		metadata={"help": "CSV filename used if saving memory results to csv for training."}				,		)
      __UpperCamelCase	 =  field(
          default=f'''env_info_{round(time() )}.csv'''				,		metadata={"help": "CSV filename used if saving environment information."}				,		)
      __UpperCamelCase	 =  field(
          default=f'''log_{round(time() )}.csv'''				,		metadata={"help": "Log filename used if print statements are saved in log."}				,		)
      __UpperCamelCase	 =  field(default=3				,		metadata={"help": "Times an experiment will be run."} )
      __UpperCamelCase	 =  field(
          default=UpperCAmelCase__				,		metadata={
              "help": (
                  "Instead of loading the model as defined in `config.architectures` if exists, just load the pretrain"
                  " model weights."
              )
          }				,		)
      def _SCREAMING_SNAKE_CASE (						self     :  Tuple):




          '''simple docstring'''


          warnings.warn(
              F'The class {self.__class__} is deprecated. Hugging Face Benchmarking utils'
              ''' are deprecated in general and it is advised to use external Benchmarking libraries '''
              ''' to benchmark Transformer models.'''						,	lowercase_						,	)
      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          return json.dumps(dataclasses.asdict(self)						,	indent=2)
      @property
      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''simple docstring'''


          if len(self.models) <= 0:
              raise ValueError(
                  '''Please make sure you provide at least one model name / model identifier, *e.g.* `--models'''
                  ''' bert-base-cased` or `args.models = [\'bert-base-cased\'].''')
          return self.models



      @property
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[int]):




          '''simple docstring'''


          if not self.multi_process:
              return False
          elif self.is_tpu:
              logger.info('''Multiprocessing is currently not possible on TPU.''')
              return False
          else:
              return True










"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


UpperCAmelCase_   : Optional[Any]   			= logging.get_logger(__name__)




class 							lowerCAmelCase__				(			UpperCAmelCase__ ):






      '''simple docstring'''

      def __init__(						self     :  List[str]						,	*lowercase_     :  Dict						,	**lowercase_     :  Union[str, Any]):




          '''simple docstring'''


          warnings.warn(
              '''The class DeiTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
              ''' use DeiTImageProcessor instead.'''						,	lowercase_						,	)
          super().__init__(*lowercase_						,	**lowercase_)


