



from collections.abc import Generator
from math import sin






def     a(      A       :    bytes       )		->       bytes:
					"""simple docstring"""





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

					a					     =   B""
					for i in [3, 2, 1, 0]:
										little_endian += string_aa[8 * i : 8 * i + 8]
					return little_endian






def     a(      A       :    int       )		->       bytes:
					"""simple docstring"""





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

					a					     =   format(A ,     "08x"       )[-8:]
					a					     =   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(      A       :    bytes       )		->       bytes:
					"""simple docstring"""





					a					     =   B""
					for char in message:
										bit_string += format(A ,     "08b"       ).encode("utf-8"       )
					a					     =   format(len(A       ) ,     "064b"       ).encode("utf-8"       )

					# Pad bit_string to a multiple of 512 chars
					bit_string += b"1"
					while len(A       ) % 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(      A       :    bytes       )		->       Generator[list[int], None, None]:
					"""simple docstring"""





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

					for pos in range(0 ,     len(A       ) ,     512       ):
										a					     =   bit_string[pos : pos + 512]
										a					     =   []
										for i in range(0 ,     512 ,     32       ):
															block_words.append(int(to_little_endian(block[i : i + 32]       ) ,     2       )       )
										yield block_words






def     a(      A       :    int       )		->       int:
					"""simple docstring"""





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

					a					     =   format(A ,     "032b"       )
					a					     =   ""
					for c in i_str:
										new_str += "1" if c == "0" else "0"
					return int(A ,     2       )






def     a(      A       :    int ,     A       :    int       )		->       int:
					"""simple docstring"""





					return (a + b) % 2**32






def     a(      A       :    int ,     A       :    int       )		->       int:
					"""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(      A       :    bytes       )		->       bytes:
					"""simple docstring"""





					a					     =   preprocess(A       )

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

					# Starting states
					a					     =   0x6745_2301
					a					     =   0xefcd_ab89
					a					     =   0x98ba_dcfe
					a					     =   0x1032_5476

					a					     =   [
					    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(A       ):
										a					     =   aa
										a					     =   ba
										a					     =   ca
										a					     =   da

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

										# Add hashed chunk to running total
										a					     =   sum_aa(A ,     A       )
										a					     =   sum_aa(A ,     A       )
										a					     =   sum_aa(A ,     A       )
										a					     =   sum_aa(A ,     A       )

					a					     =   reformat_hex(A       ) + reformat_hex(A       ) + reformat_hex(A       ) + reformat_hex(A       )
					return digest


if __name__ == "__main__":
				import doctest

				doctest.testmod()





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


_lowercase: str      			=		logging.get_logger(__name__)

_lowercase: 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 	_lowercase							(   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		,       lowerCamelCase_=50265		,       lowerCamelCase_=1024		,       lowerCamelCase_=12		,       lowerCamelCase_=16		,       lowerCamelCase_=4096		,       lowerCamelCase_="gelu"		,       lowerCamelCase_=512		,       lowerCamelCase_=0.1		,       lowerCamelCase_=0.0		,       lowerCamelCase_=0.0		,       lowerCamelCase_=2		,       lowerCamelCase_=0.02		,       lowerCamelCase_=0.0		,       lowerCamelCase_=True		,       lowerCamelCase_=False		,       lowerCamelCase_=True		,       lowerCamelCase_=True		,       lowerCamelCase_=1		,       lowerCamelCase_=0		,       lowerCamelCase_=2		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						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=lowerCamelCase_		,       bos_token_id=lowerCamelCase_		,       eos_token_id=lowerCamelCase_		,       decoder_start_token_id=lowerCamelCase_		,       **lowerCamelCase_		,       )
