






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

from ..utils import logging


SCREAMING_SNAKE_CASE__		:							int 				=				logging.get_logger(__name__)





def  _lowerCamelCase						(						__lowerCamelCase=None ,							__lowerCamelCase=None       ) ->			List[str]:

     '''simple docstring'''
     return field(default_factory=lambda: default ,							metadata=__lowerCamelCase       )







@dataclass
class 				UpperCAmelCase_  :
     __lowerCamelCase      				=  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'
             )
         }							,      )

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

     __lowerCamelCase      				=  list_field(
         default=[8, 32, 128, 512]							,      metadata={'help': 'List of sequence lengths for which memory and time performance will be evaluated'}							,      )

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




     def   __UpperCAmelCase  (				self		):
          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."""	,						_lowerCAmelCase	,						)




     def   __UpperCAmelCase  (				self		):
          return json.dumps(dataclasses.asdict(self		)	,						indent=2		)




     @property
     def   __UpperCAmelCase  (				self		):
          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   __UpperCAmelCase  (				self		):
          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










from timeit import timeit


def     lowercase	(    a ):



		'''simple docstring'''




		if number < 0:
				raise ValueError("the value of input must not be negative" )
		SCREAMING_SNAKE_CASE_				:Optional[int]				     =						0
		while number:
				number &= number - 1
				result += 1
		return result


def     lowercase	(    a ):



		'''simple docstring'''




		if number < 0:
				raise ValueError("the value of input must not be negative" )
		SCREAMING_SNAKE_CASE_				:List[Any]				     =						0
		while number:
				if number % 2 == 1:
						result += 1
				number >>= 1
		return result


def     lowercase	(    ):



		'''simple docstring'''




		def do_benchmark(a ) -> None:
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						"import __main__ as z"
				print(F"Benchmark when {number = }:" )
				print(F"{get_set_bits_count_using_modulo_operator(a ) = }" )
				SCREAMING_SNAKE_CASE_				:List[Any]				     =						timeit("z.get_set_bits_count_using_modulo_operator(25)"     , setup=a )
				print(F"timeit() runs in {timing} seconds" )
				print(F"{get_set_bits_count_using_brian_kernighans_algorithm(a ) = }" )
				SCREAMING_SNAKE_CASE_				:str				     =						timeit(
				    "z.get_set_bits_count_using_brian_kernighans_algorithm(25)"     , setup=a     , )
				print(F"timeit() runs in {timing} seconds" )

		for number in (25, 37, 58, 0):
				do_benchmark(a )
				print()


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()






