



from collections.abc import Generator
from math import sin






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if len(_lowerCamelCase  ) != 32:
														raise ValueError("Input must be of length 32"  )

							_lowerCAmelCase     :							Optional[Any]    =    b""
							for i in [3, 2, 1, 0]:
														little_endian += string_aa[8 * i : 8 * i + 8]
							return little_endian






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if i < 0:
														raise ValueError("Input must be non-negative"  )

							_lowerCAmelCase     :							Dict    =    format(_lowerCamelCase				, "08x"  )[-8:]
							_lowerCAmelCase     :							int    =    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 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Tuple    =    b""
							for char in message:
														bit_string += format(_lowerCamelCase				, "08b"  ).encode("utf-8"  )
							_lowerCAmelCase     :							Tuple    =    format(len(_lowerCamelCase  )				, "064b"  ).encode("utf-8"  )

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

							return bit_string






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if len(_lowerCamelCase  ) % 512 != 0:
														raise ValueError("Input must have length that's a multiple of 512"  )

							for pos in range(0				, len(_lowerCamelCase  )				, 512  ):
														_lowerCAmelCase     :							List[str]    =    bit_string[pos : pos + 512]
														_lowerCAmelCase     :							Optional[Any]    =    []
														for i in range(0				, 512				, 32  ):
																					block_words.append(int(to_little_endian(block[i : i + 32]  )				, 2  )  )
														yield block_words






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							if i < 0:
														raise ValueError("Input must be non-negative"  )

							_lowerCAmelCase     :							str    =    format(_lowerCamelCase				, "032b"  )
							_lowerCAmelCase     :							Optional[Any]    =    ""
							for c in i_str:
														new_str += "1" if c == "0" else "0"
							return int(_lowerCamelCase				, 2  )






def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							return (a + b) % 2**32






def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							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 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Dict    =    preprocess(_lowerCamelCase  )

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

							# Starting states
							_lowerCAmelCase     :							int    =    0X67_45_23_01
							_lowerCAmelCase     :							Optional[Any]    =    0XEF_CD_AB_89
							_lowerCAmelCase     :							Union[str, Any]    =    0X98_BA_DC_FE
							_lowerCAmelCase     :							Dict    =    0X10_32_54_76

							_lowerCAmelCase     :							int    =    [
							    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(_lowerCamelCase  ):
														_lowerCAmelCase     :							Dict    =    aa
														_lowerCAmelCase     :							Union[str, Any]    =    ba
														_lowerCAmelCase     :							Dict    =    ca
														_lowerCAmelCase     :							Tuple    =    da

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

														# Add hashed chunk to running total
														_lowerCAmelCase     :							List[str]    =    sum_aa(_lowerCamelCase				, _lowerCamelCase  )
														_lowerCAmelCase     :							Any    =    sum_aa(_lowerCamelCase				, _lowerCamelCase  )
														_lowerCAmelCase     :							Any    =    sum_aa(_lowerCamelCase				, _lowerCamelCase  )
														_lowerCAmelCase     :							str    =    sum_aa(_lowerCamelCase				, _lowerCamelCase  )

							_lowerCAmelCase     :							Union[str, Any]    =    reformat_hex(_lowerCamelCase  ) + reformat_hex(_lowerCamelCase  ) + reformat_hex(_lowerCamelCase  ) + reformat_hex(_lowerCamelCase  )
							return digest


if __name__ == "__main__":
						import doctest

						doctest.testmod()







'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

lowerCAmelCase_					:    List[str]      	=			{
    'microsoft/trocr-base-handwritten': (
        'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}
class 				__SCREAMING_SNAKE_CASE  (lowerCamelCase_      ):






				"""simple docstring"""







				__a            ='trocr'
				__a            =['past_key_values']
				__a            ={
				    'num_attention_heads': 'decoder_attention_heads',
				    'hidden_size': 'd_model',
				    'num_hidden_layers': 'decoder_layers',
				}




				def __init__(  self     :					Optional[int]					,				__a     :					Any=5_02_65					,				__a     :					Optional[int]=10_24					,				__a     :					List[Any]=12					,				__a     :					str=16					,				__a     :					int=40_96					,				__a     :					Optional[Any]="gelu"					,				__a     :					Union[str, Any]=5_12					,				__a     :					Dict=0.1					,				__a     :					List[str]=0.0					,				__a     :					Union[str, Any]=0.0					,				__a     :					Any=2					,				__a     :					Union[str, Any]=0.02					,				__a     :					Any=0.0					,				__a     :					List[str]=True					,				__a     :					Optional[Any]=False					,				__a     :					Union[str, Any]=True					,				__a     :					Optional[Any]=True					,				__a     :					Any=1					,				__a     :					List[Any]=0					,				__a     :					Any=2					,				**__a     :					Optional[Any]					,				):
								_a								= vocab_size
								_a								= d_model
								_a								= decoder_layers
								_a								= decoder_attention_heads
								_a								= decoder_ffn_dim
								_a								= activation_function
								_a								= max_position_embeddings
								_a								= dropout
								_a								= attention_dropout
								_a								= activation_dropout
								_a								= init_std
								_a								= decoder_layerdrop
								_a								= use_cache
								_a								= scale_embedding
								_a								= use_learned_position_embeddings
								_a								= layernorm_embedding

								super().__init__(
								    pad_token_id=__a					,				bos_token_id=__a					,				eos_token_id=__a					,				decoder_start_token_id=__a					,				**__a					,				)
