



'''simple docstring'''





from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
    center_crop,
    get_resize_output_image_size,
    normalize,
    rescale,
    resize,
    to_channel_dimension_format,
)
from ...image_utils import (
    IMAGENET_STANDARD_MEAN,
    IMAGENET_STANDARD_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
  import PIL


lowercase_		       =  logging.get_logger(__name__)






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       Any          =       ['pixel_values']



 def __init__(self ,   A = True ,   A = None ,   A = None ,   A = PILImageResampling.BILINEAR ,   A = True ,   A = 1 / 255 ,   A = True ,   A = None ,   A = None ,   **A ,   )    ->     None:


      """simple docstring"""



      super().__init__(**A       )
      _a      =  size if size is not None else {'''shortest_edge''': 384}
      _a      =  get_size_dict(A ,   default_to_square=A       )

      _a      =  do_resize
      _a      =  size
      # Default value set here for backwards compatibility where the value in config is None
      _a      =  crop_pct if crop_pct is not None else 224 / 256
      _a      =  resample
      _a      =  do_rescale
      _a      =  rescale_factor
      _a      =  do_normalize
      _a      =  image_mean if image_mean is not None else IMAGENET_STANDARD_MEAN
      _a      =  image_std if image_std is not None else IMAGENET_STANDARD_STD



 def 					a__  (self ,   A ,   A ,   A ,   A = PILImageResampling.BICUBIC ,   A = None ,   **A ,   )    ->     np.ndarray:


      """simple docstring"""



      _a      =  get_size_dict(A ,   default_to_square=A       )
      if "shortest_edge" not in size:
           raise ValueError(f'''Size dictionary must contain \'shortest_edge\' key. Got {size.keys()}'''       )
      _a      =  size['''shortest_edge''']

      if shortest_edge < 384:
           # maintain same ratio, resizing shortest edge to shortest_edge/crop_pct
           _a      =  int(shortest_edge / crop_pct       )
           _a      =  get_resize_output_image_size(A ,   size=A ,   default_to_square=A       )
           _a      =  resize(image=A ,   size=A ,   resample=A ,   data_format=A ,   **A       )
           # then crop to (shortest_edge, shortest_edge)
           return center_crop(image=A ,   size=(shortest_edge, shortest_edge) ,   data_format=A ,   **A       )
      else:
           # warping (no cropping) when evaluated at 384 or larger
           return resize(
               A ,   size=(shortest_edge, shortest_edge) ,   resample=A ,   data_format=A ,   **A       )



 def 					a__  (self ,   A ,   A ,   A = None ,   **A ,   )    ->     int:


      """simple docstring"""



      return rescale(A ,   scale=A ,   data_format=A ,   **A       )



 def 					a__  (self ,   A ,   A ,   A ,   A = None ,   **A ,   )    ->     np.ndarray:


      """simple docstring"""



      return normalize(A ,   mean=A ,   std=A ,   data_format=A ,   **A       )



 def 					a__  (self ,   A ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = None ,   A = ChannelDimension.FIRST ,   **A ,   )    ->     PIL.Image.Image:


      """simple docstring"""



      _a      =  do_resize if do_resize is not None else self.do_resize
      _a      =  crop_pct if crop_pct is not None else self.crop_pct
      _a      =  resample if resample is not None else self.resample
      _a      =  do_rescale if do_rescale is not None else self.do_rescale
      _a      =  rescale_factor if rescale_factor is not None else self.rescale_factor
      _a      =  do_normalize if do_normalize is not None else self.do_normalize
      _a      =  image_mean if image_mean is not None else self.image_mean
      _a      =  image_std if image_std is not None else self.image_std

      _a      =  size if size is not None else self.size
      _a      =  get_size_dict(A ,   default_to_square=A       )

      _a      =  make_list_of_images(A       )

      if not valid_images(A       ):
           raise ValueError(
               '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
               '''torch.Tensor, tf.Tensor or jax.ndarray.'''       )

      if do_resize and size is None or resample is None:
           raise ValueError('''Size and resample must be specified if do_resize is True.'''       )

      if do_resize and size["shortest_edge"] < 384 and crop_pct is None:
           raise ValueError('''crop_pct must be specified if size < 384.'''       )

      if do_rescale and rescale_factor is None:
           raise ValueError('''Rescale factor must be specified if do_rescale is True.'''       )

      if do_normalize and (image_mean is None or image_std is None):
           raise ValueError('''Image mean and std must be specified if do_normalize is True.'''       )

      # All transformations expect numpy arrays.
      _a      =  [to_numpy_array(A       ) for image in images]

      if do_resize:
           _a      =  [self.resize(image=A ,   size=A ,   crop_pct=A ,   resample=A       ) for image in images]

      if do_rescale:
           _a      =  [self.rescale(image=A ,   scale=A       ) for image in images]

      if do_normalize:
           _a      =  [self.normalize(image=A ,   mean=A ,   std=A       ) for image in images]

      _a      =  [to_channel_dimension_format(A ,   A       ) for image in images]

      _a      =  {'''pixel_values''': images}
      return BatchFeature(data=A ,   tensor_type=A       )








'''simple docstring'''





from collections.abc import Generator
from math import sin




def lowerCAmelCase  (__A):



     """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 lowerCAmelCase  (__A):



     """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 lowerCAmelCase  (__A):



     """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 lowerCAmelCase  (__A):



     """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 lowerCAmelCase  (__A):



     """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 lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     return (a + b) % 2**32




def lowerCAmelCase  (__A  ,	__A):



     """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 lowerCAmelCase  (__A):



     """simple docstring"""



     _a      =  preprocess(__A)

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

     # Starting states
     _a      =  0x67_452_301
     _a      =  0xEF_CDA_B89
     _a      =  0x98_BAD_CFE
     _a      =  0x10_325_476

     _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()



