

import json
import os
from collections import Counter

import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset


_UpperCAmelCase						:  Union[str, Any]									=			{1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3, 2), 7: (7, 1), 8: (4, 2), 9: (3, 3)}







class 					lowercase							(			nn.Module     ):




				def __init__(   self ,  snake_case			):
											super().__init__()
											snake_case_     							=       torchvision.models.resnetaaa(pretrained=snake_case			)
											snake_case_     							=       list(model.children()			)[:-2]
											snake_case_     							=       nn.Sequential(*snake_case			)
											snake_case_     							=       nn.AdaptiveAvgPoolad(POOLING_BREAKDOWN[args.num_image_embeds]			)




				def        a				(   self ,  snake_case			):
											# Bx3x224x224 -> Bx2048x7x7 -> Bx2048xN -> BxNx2048
											snake_case_     							=       self.pool(self.model(snake_case			)			)
											snake_case_     							=       torch.flatten(snake_case ,  start_dim=2			)
											snake_case_     							=       out.transpose(1 ,  2			).contiguous()
											return out  # BxNx2048







class 					lowercase							(			lowercase_     ):




				def __init__(   self ,  snake_case ,  snake_case ,  snake_case ,  snake_case ,  snake_case			):
											snake_case_     							=       [json.loads(snake_case			) for l in open(snake_case			)]
											snake_case_     							=       os.path.dirname(snake_case			)
											snake_case_     							=       tokenizer
											snake_case_     							=       labels
											snake_case_     							=       len(snake_case			)
											snake_case_     							=       max_seq_length

											snake_case_     							=       transforms




				def __len__(   self			):
											return len(self.data			)




				def __getitem__(   self ,  snake_case			):
											snake_case_     							=       torch.LongTensor(self.tokenizer.encode(self.data[index]['text'] ,  add_special_tokens=snake_case			)			)
											snake_case_							,       snake_case_							,       snake_case_     							=       sentence[0], sentence[1:-1], sentence[-1]
											snake_case_     							=       sentence[: self.max_seq_length]

											snake_case_     							=       torch.zeros(self.n_classes			)
											snake_case_     							=       1

											snake_case_     							=       Image.open(os.path.join(self.data_dir ,  self.data[index]['img']			)			).convert('RGB'			)
											snake_case_     							=       self.transforms(snake_case			)

											return {
											    "image_start_token": start_token,
											    "image_end_token": end_token,
											    "sentence": sentence,
											    "image": image,
											    "label": label,
											}




				def        a				(   self			):
											snake_case_     							=       Counter()
											for row in self.data:
																		label_freqs.update(row['label']			)
											return label_freqs





def    __lowerCamelCase      (					UpperCamelCase__ ):







							'''simple docstring'''






							snake_case_     							=       [len(row['sentence'] ) for row in batch]
							snake_case_							,       snake_case_     							=       len(UpperCamelCase__ ), max(UpperCamelCase__ )

							snake_case_     							=       torch.zeros(UpperCamelCase__  ,				UpperCamelCase__  ,				dtype=torch.long )
							snake_case_     							=       torch.zeros(UpperCamelCase__  ,				UpperCamelCase__  ,				dtype=torch.long )

							for i_batch, (input_row, length) in enumerate(zip(UpperCamelCase__  ,				UpperCamelCase__ ) ):
														snake_case_     							=       input_row['sentence']
														snake_case_     							=       1

							snake_case_     							=       torch.stack([row['image'] for row in batch] )
							snake_case_     							=       torch.stack([row['label'] for row in batch] )
							snake_case_     							=       torch.stack([row['image_start_token'] for row in batch] )
							snake_case_     							=       torch.stack([row['image_end_token'] for row in batch] )

							return text_tensor, mask_tensor, img_tensor, img_start_token, img_end_token, tgt_tensor





def    __lowerCamelCase      (					):







							'''simple docstring'''






							return [
							    "Crime",
							    "Drama",
							    "Thriller",
							    "Action",
							    "Comedy",
							    "Romance",
							    "Documentary",
							    "Short",
							    "Mystery",
							    "History",
							    "Family",
							    "Adventure",
							    "Fantasy",
							    "Sci-Fi",
							    "Western",
							    "Horror",
							    "Sport",
							    "War",
							    "Music",
							    "Musical",
							    "Animation",
							    "Biography",
							    "Film-Noir",
							]





def    __lowerCamelCase      (					):







							'''simple docstring'''






							return transforms.Compose(
							    [
							        transforms.Resize(256 ),
							        transforms.CenterCrop(224 ),
							        transforms.ToTensor(),
							        transforms.Normalize(
							            mean=[0.46_77_70_44, 0.44_53_14_29, 0.40_66_10_17]  ,				std=[0.12_22_19_94, 0.12_14_58_35, 0.14_38_04_69]  ,				),
							    ] )







import argparse
import struct
import unittest







class 					lowercase							:




				def __init__(   self ,  snake_case			):
											snake_case_     							=       data

											# Initialize hash values
											snake_case_     							=       [
											    0x6A09E667,
											    0xBB67AE85,
											    0x3C6EF372,
											    0xA54FF53A,
											    0x510E527F,
											    0x9B05688C,
											    0x1F83D9AB,
											    0x5BE0CD19,
											]

											# Initialize round constants
											snake_case_     							=       [
											    0x428A2F98,
											    0x71374491,
											    0xB5C0FBCF,
											    0xE9B5DBA5,
											    0x3956C25B,
											    0x59F111F1,
											    0x923F82A4,
											    0xAB1C5ED5,
											    0xD807AA98,
											    0x12835B01,
											    0x243185BE,
											    0x550C7DC3,
											    0x72BE5D74,
											    0x80DEB1FE,
											    0x9BDC06A7,
											    0xC19BF174,
											    0xE49B69C1,
											    0xEFBE4786,
											    0x0FC19DC6,
											    0x240CA1CC,
											    0x2DE92C6F,
											    0x4A7484AA,
											    0x5CB0A9DC,
											    0x76F988DA,
											    0x983E5152,
											    0xA831C66D,
											    0xB00327C8,
											    0xBF597FC7,
											    0xC6E00BF3,
											    0xD5A79147,
											    0x06CA6351,
											    0x14292967,
											    0x27B70A85,
											    0x2E1B2138,
											    0x4D2C6DFC,
											    0x53380D13,
											    0x650A7354,
											    0x766A0ABB,
											    0x81C2C92E,
											    0x92722C85,
											    0xA2BFE8A1,
											    0xA81A664B,
											    0xC24B8B70,
											    0xC76C51A3,
											    0xD192E819,
											    0xD6990624,
											    0xF40E3585,
											    0x106AA070,
											    0x19A4C116,
											    0x1E376C08,
											    0x2748774C,
											    0x34B0BCB5,
											    0x391C0CB3,
											    0x4ED8AA4A,
											    0x5B9CCA4F,
											    0x682E6FF3,
											    0x748F82EE,
											    0x78A5636F,
											    0x84C87814,
											    0x8CC70208,
											    0x90BEFFFA,
											    0xA4506CEB,
											    0xBEF9A3F7,
											    0xC67178F2,
											]

											snake_case_     							=       self.preprocessing(self.data			)
											self.final_hash()




				@staticmethod
				def        a				(   snake_case			):
											snake_case_     							=       b'\x80' + (b'\x00' * (63 - (len(snake_case			) + 8) % 64))
											snake_case_     							=       struct.pack('>Q' ,  (len(snake_case			) * 8)			)
											return data + padding + big_endian_integer




				def        a				(   self			):
											# Convert into blocks of 64 bytes
											snake_case_     							=       [
											    self.preprocessed_data[x : x + 64]
											    for x in range(0 ,  len(self.preprocessed_data			) ,  64			)
											]

											for block in self.blocks:
																		# Convert the given block into a list of 4 byte integers
																		snake_case_     							=       list(struct.unpack('>16L' ,  snake_case			)			)
																		# add 48 0-ed integers
																		words += [0] * 48

																		snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_     							=       self.hashes

																		for index in range(0 ,  64			):
																									if index > 15:
																																# modify the zero-ed indexes at the end of the array
																																snake_case_     							=       (
																																    self.ror(words[index - 15] ,  7			)
																																    ^ self.ror(words[index - 15] ,  18			)
																																    ^ (words[index - 15] >> 3)
																																)
																																snake_case_     							=       (
																																    self.ror(words[index - 2] ,  17			)
																																    ^ self.ror(words[index - 2] ,  19			)
																																    ^ (words[index - 2] >> 10)
																																)

																																snake_case_     							=       (
																																    words[index - 16] + sa + words[index - 7] + sa
																																) % 0x100000000

																									# Compression
																									snake_case_     							=       self.ror(snake_case ,  6			) ^ self.ror(snake_case ,  11			) ^ self.ror(snake_case ,  25			)
																									snake_case_     							=       (e & f) ^ ((~e & 0xFFFFFFFF) & g)
																									snake_case_     							=       (
																									    h + sa + ch + self.round_constants[index] + words[index]
																									) % 0x100000000
																									snake_case_     							=       self.ror(snake_case ,  2			) ^ self.ror(snake_case ,  13			) ^ self.ror(snake_case ,  22			)
																									snake_case_     							=       (a & b) ^ (a & c) ^ (b & c)
																									snake_case_     							=       (sa + maj) % 0x100000000

																									snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_							,       snake_case_     							=       (
																									    g,
																									    f,
																									    e,
																									    ((d + tempa) % 0x100000000),
																									    c,
																									    b,
																									    a,
																									    ((tempa + tempa) % 0x100000000),
																									)

																		snake_case_     							=       [a, b, c, d, e, f, g, h]

																		# Modify final values
																		snake_case_     							=       [
																		    ((element + mutated_hash_values[index]) % 0x100000000)
																		    for index, element in enumerate(self.hashes			)
																		]

											snake_case_     							=       ''.join([hex(snake_case			)[2:].zfill(8			) for value in self.hashes]			)




				def        a				(   self ,  snake_case ,  snake_case			):
											return 0xFFFFFFFF & (value << (32 - rotations)) | (value >> rotations)







class 					lowercase							(			unittest.TestCase     ):




				def        a				(   self			):
											import hashlib

											snake_case_     							=       bytes('Test String' ,  'utf-8'			)
											self.assertEqual(SHAaaa(snake_case			).hash ,  hashlib.shaaaa(snake_case			).hexdigest()			)





def    __lowerCamelCase      (					):







							'''simple docstring'''






							import doctest

							doctest.testmod()

							snake_case_     							=       argparse.ArgumentParser()
							parser.add_argument(
							    '-s'  ,				'--string'  ,				dest='input_string'  ,				default='Hello World!! Welcome to Cryptography'  ,				help='Hash the string'  ,				)
							parser.add_argument(
							    '-f'  ,				'--file'  ,				dest='input_file'  ,				help='Hash contents of a file' )

							snake_case_     							=       parser.parse_args()

							snake_case_     							=       args.input_string

							# hash input should be a bytestring
							if args.input_file:
														with open(args.input_file  ,				'rb' ) as f:
																					snake_case_     							=       f.read()
							else:
														snake_case_     							=       bytes(UpperCamelCase__  ,				'utf-8' )

							print(SHAaaa(UpperCamelCase__ ).hash )


if __name__ == "__main__":
					main()




