
"""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_       :    Any						      =			logging.get_logger(__name__)
def 				A_  (__a=None					, __a=None					):

					'''simple docstring'''





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




@dataclass
class __lowerCAmelCase					:




			"""simple docstring"""







			snake_case						   =					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"
			        )
			    }  ,					)

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

			snake_case						   =					list_field(
			    default=[8, 32, 1_28, 5_12]  ,					metadata={"help": "List of sequence lengths for which memory and time performance will be evaluated"}  ,					)

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




			def   lowerCamelCase__  (					self    :       Dict						)   ->			List[str]:







								"""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."							, __UpperCamelCase							, )




			def   lowerCamelCase__  (					self    :       str						)   ->			Optional[int]:







								"""simple docstring"""
								return json.dumps(dataclasses.asdict(self						)							, indent=2						)




			@property
			def   lowerCamelCase__  (					self    :       Optional[Any]						)   ->			List[Any]:







								"""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   lowerCamelCase__  (					self    :       Tuple						)   ->			str:







								"""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






def   __lowerCAmelCase    (				UpperCAmelCase__					:   int							)	->     int:

							if not isinstance(UpperCAmelCase__      ,					UpperCAmelCase__							):
														raise ValueError("""multiplicative_persistence() only accepts integral values"""							)
							if num < 0:
														raise ValueError("""multiplicative_persistence() does not accept negative values"""							)

							lowerCamelCase_					=       0
							lowerCamelCase_					=       str(UpperCAmelCase__							)

							while len(UpperCAmelCase__							) != 1:
														lowerCamelCase_					=       [int(UpperCAmelCase__							) for i in num_string]

														lowerCamelCase_					=       1
														for i in range(0      ,					len(UpperCAmelCase__							)							):
																					total *= numbers[i]

														lowerCamelCase_					=       str(UpperCAmelCase__							)

														steps += 1
							return steps



def   __lowerCAmelCase    (				UpperCAmelCase__					:   int							)	->     int:

							if not isinstance(UpperCAmelCase__      ,					UpperCAmelCase__							):
														raise ValueError("""additive_persistence() only accepts integral values"""							)
							if num < 0:
														raise ValueError("""additive_persistence() does not accept negative values"""							)

							lowerCamelCase_					=       0
							lowerCamelCase_					=       str(UpperCAmelCase__							)

							while len(UpperCAmelCase__							) != 1:
														lowerCamelCase_					=       [int(UpperCAmelCase__							) for i in num_string]

														lowerCamelCase_					=       0
														for i in range(0      ,					len(UpperCAmelCase__							)							):
																					total += numbers[i]

														lowerCamelCase_					=       str(UpperCAmelCase__							)

														steps += 1
							return steps


if __name__ == "__main__":
		import doctest

		doctest.testmod()





