from collections.abc import Generator
from math import sin
def 					_snake_case	(  __snake_case						):
					if len(__snake_case						) != 32:
										raise ValueError('''Input must be of length 32'''						)

					_UpperCamelCase			     =     B''''''
					for i in [3, 2, 1, 0]:
										little_endian += string_aa[8 * i : 8 * i + 8]
					return little_endian
def 					_snake_case	(  __snake_case						):
					if i < 0:
										raise ValueError('''Input must be non-negative'''						)

					_UpperCamelCase			     =     format(__snake_case  ,     '''08x'''						)[-8:]
					_UpperCamelCase			     =     B''''''
					for i in [3, 2, 1, 0]:
										little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('''utf-8'''						)
					return little_endian_hex
def 					_snake_case	(  __snake_case						):
					_UpperCamelCase			     =     B''''''
					for char in message:
										bit_string += format(__snake_case  ,     '''08b'''						).encode('''utf-8'''						)
					_UpperCamelCase			     =     format(len(__snake_case						)  ,     '''064b'''						).encode('''utf-8'''						)

					# Pad bit_string to a multiple of 512 chars
					bit_string += b"1"
					while len(__snake_case						) % 512 != 448:
										bit_string += b"0"
					bit_string += to_little_endian(start_len[32:]						) + to_little_endian(start_len[:32]						)

					return bit_string
def 					_snake_case	(  __snake_case						):
					if len(__snake_case						) % 512 != 0:
										raise ValueError('''Input must have length that\'s a multiple of 512'''						)

					for pos in range(0  ,     len(__snake_case						)  ,     512						):
										_UpperCamelCase			     =     bit_string[pos : pos + 512]
										_UpperCamelCase			     =     []
										for i in range(0  ,     512  ,     32						):
															block_words.append(int(to_little_endian(block[i : i + 32]						)  ,     2						)						)
										yield block_words
def 					_snake_case	(  __snake_case						):
					if i < 0:
										raise ValueError('''Input must be non-negative'''						)

					_UpperCamelCase			     =     format(__snake_case  ,     '''032b'''						)
					_UpperCamelCase			     =     ''''''
					for c in i_str:
										new_str += "1" if c == "0" else "0"
					return int(__snake_case  ,     2						)
def 					_snake_case	(  __snake_case  ,     __snake_case						):
					return (a + b) % 2**32
def 					_snake_case	(  __snake_case  ,     __snake_case						):
					if i < 0:
										raise ValueError('''Input must be non-negative'''						)
					if shift < 0:
										raise ValueError('''Shift must be non-negative'''						)
					return ((i << shift) ^ (i >> (32 - shift))) % 2**32
def 					_snake_case	(  __snake_case						):
					_UpperCamelCase			     =     preprocess(__snake_case						)

					_UpperCamelCase			     =     [int(2**32 * abs(sin(i + 1						)						)						) for i in range(64						)]

					# Starting states
					_UpperCamelCase			     =     0x6745_2301
					_UpperCamelCase			     =     0xEFCD_AB89
					_UpperCamelCase			     =     0x98BA_DCFE
					_UpperCamelCase			     =     0x1032_5476

					_UpperCamelCase			     =     [
					    7,
					    12,
					    17,
					    22,
					    7,
					    12,
					    17,
					    22,
					    7,
					    12,
					    17,
					    22,
					    7,
					    12,
					    17,
					    22,
					    5,
					    9,
					    14,
					    20,
					    5,
					    9,
					    14,
					    20,
					    5,
					    9,
					    14,
					    20,
					    5,
					    9,
					    14,
					    20,
					    4,
					    11,
					    16,
					    23,
					    4,
					    11,
					    16,
					    23,
					    4,
					    11,
					    16,
					    23,
					    4,
					    11,
					    16,
					    23,
					    6,
					    10,
					    15,
					    21,
					    6,
					    10,
					    15,
					    21,
					    6,
					    10,
					    15,
					    21,
					    6,
					    10,
					    15,
					    21,
					]

					# Process bit string in chunks, each with 16 32-char words
					for block_words in get_block_words(__snake_case						):
										_UpperCamelCase			     =     aa
										_UpperCamelCase			     =     ba
										_UpperCamelCase			     =     ca
										_UpperCamelCase			     =     da

										# Hash current chunk
										for i in range(64						):
															if i <= 15:
																				# f = (b & c) | (not_32(b) & d)     # Alternate definition for f
																				_UpperCamelCase			     =     d ^ (b & (c ^ d))
																				_UpperCamelCase			     =     i
															elif i <= 31:
																				# f = (d & b) | (not_32(d) & c)     # Alternate definition for f
																				_UpperCamelCase			     =     c ^ (d & (b ^ c))
																				_UpperCamelCase			     =     (5 * i + 1) % 16
															elif i <= 47:
																				_UpperCamelCase			     =     b ^ c ^ d
																				_UpperCamelCase			     =     (3 * i + 5) % 16
															else:
																				_UpperCamelCase			     =     c ^ (b | not_aa(__snake_case						))
																				_UpperCamelCase			     =     (7 * i) % 16
															_UpperCamelCase			     =     (f + a + added_consts[i] + block_words[g]) % 2**32
															_UpperCamelCase			     =     d
															_UpperCamelCase			     =     c
															_UpperCamelCase			     =     b
															_UpperCamelCase			     =     sum_aa(__snake_case  ,     left_rotate_aa(__snake_case  ,     shift_amounts[i]						)						)

										# Add hashed chunk to running total
										_UpperCamelCase			     =     sum_aa(__snake_case  ,     __snake_case						)
										_UpperCamelCase			     =     sum_aa(__snake_case  ,     __snake_case						)
										_UpperCamelCase			     =     sum_aa(__snake_case  ,     __snake_case						)
										_UpperCamelCase			     =     sum_aa(__snake_case  ,     __snake_case						)

					_UpperCamelCase			     =     reformat_hex(__snake_case						) + reformat_hex(__snake_case						) + reformat_hex(__snake_case						) + reformat_hex(__snake_case						)
					return digest


if __name__ == "__main__":
					import doctest

					doctest.testmod()

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

from ..utils import logging


_lowerCAmelCase       =		logging.get_logger(__name__)
def 					_snake_case	(  __snake_case=None  ,     __snake_case=None						):
					return field(default_factory=lambda: default  ,     metadata=__snake_case						)







@dataclass
class     lowerCAmelCase_     :
							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, 32, 128, 512],  metadata={"help": "List of sequence lengths for which memory and time performance will be evaluated"},  )

							UpperCAmelCase				   =     field(
							    default=__lowercase,  metadata={"help": "Whether to benchmark inference of model. Inference can be disabled via --no-inference."},  )
							UpperCAmelCase				   =     field(
							    default=__lowercase,  metadata={"help": "Whether to run on available cuda devices. Cuda can be disabled via --no-cuda."},  )
							UpperCAmelCase				   =     field(
							    default=__lowercase,  metadata={"help": "Whether to run on available tpu devices. TPU can be disabled via --no-tpu."} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Use FP16 to accelerate inference."} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Benchmark training of model"} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Verbose memory tracing"} )
							UpperCAmelCase				   =     field(
							    default=__lowercase,  metadata={"help": "Whether to perform speed measurements. Speed measurements can be disabled via --no-speed."},  )
							UpperCAmelCase				   =     field(
							    default=__lowercase,  metadata={
							        "help": "Whether to perform memory measurements. Memory measurements can be disabled via --no-memory"
							    },  )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Trace memory line by line"} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Save result to a CSV file"} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Save all print statements in a log file"} )
							UpperCAmelCase				   =     field(default=__lowercase,  metadata={"help": "Whether to print environment information"} )
							UpperCAmelCase				   =     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."
							        )
							    },  )
							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=__lowercase,  metadata={
							        "help": (
							            "Instead of loading the model as defined in `config.architectures` if exists, just load the pretrain"
							            " model weights."
							        )
							    },  )







							def  UpperCamelCase_						(   self      :     Union[str, Any]		):
												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.''' ,			_A ,			)







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







							@property
							def  UpperCamelCase_						(   self      :     List[Any]		):
												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      :     Optional[int]		):
												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
