
import os
import sys

from . import rsa_key_generator as rkg

lowercase						:      List[Any]							=							128
lowercase						:      Union[str, Any]							=							256







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__ = DEFAULT_BLOCK_SIZE       )				->					list[int]:
       lowercase							:  Dict 			=   message.encode("""ascii"""       )

       lowercase							:  Optional[int] 			=   []
       for block_start in range(0      ,			len(SCREAMING_SNAKE_CASE__       )      ,			SCREAMING_SNAKE_CASE__       ):
              lowercase							:  Optional[int] 			=   0
              for i in range(SCREAMING_SNAKE_CASE__      ,			min(block_start + block_size      ,			len(SCREAMING_SNAKE_CASE__       )       )       ):
                     block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
              block_ints.append(SCREAMING_SNAKE_CASE__       )
       return block_ints







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__ = DEFAULT_BLOCK_SIZE       )				->					str:
       lowercase							:  list[str] 			=   []
       for block_int in block_ints:
              lowercase							:  list[str] 			=   []
              for i in range(block_size - 1      ,			-1      ,			-1       ):
                     if len(SCREAMING_SNAKE_CASE__       ) + i < message_length:
                            lowercase							:  Optional[int] 			=   block_int // (BYTE_SIZE**i)
                            lowercase							:  Dict 			=   block_int % (BYTE_SIZE**i)
                            block_message.insert(0      ,			chr(SCREAMING_SNAKE_CASE__       )       )
              message.extend(SCREAMING_SNAKE_CASE__       )
       return "".join(SCREAMING_SNAKE_CASE__       )







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__ = DEFAULT_BLOCK_SIZE       )				->					list[int]:
       lowercase							:  Union[str, Any] 			=   []
       lowercase			,    lowercase							:  Union[str, Any] 			=   key

       for block in get_blocks_from_text(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       ):
              encrypted_blocks.append(pow(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )       )
       return encrypted_blocks







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__ = DEFAULT_BLOCK_SIZE      ,			)				->					str:
       lowercase							:  Optional[Any] 			=   []
       lowercase			,    lowercase							:  Union[str, Any] 			=   key
       for block in encrypted_blocks:
              decrypted_blocks.append(pow(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )       )
       return get_text_from_blocks(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )







def 		_snake_case(						SCREAMING_SNAKE_CASE__       )				->					tuple[int, int, int]:
       with open(SCREAMING_SNAKE_CASE__       ) as fo:
              lowercase							:  int 			=   fo.read()
       lowercase			,    lowercase			,    lowercase							:  int 			=   content.split(""","""       )
       return (int(SCREAMING_SNAKE_CASE__       ), int(SCREAMING_SNAKE_CASE__       ), int(SCREAMING_SNAKE_CASE__       ))







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__ = DEFAULT_BLOCK_SIZE      ,			)				->					str:
       lowercase			,    lowercase			,    lowercase							:  Union[str, Any] 			=   read_key_file(SCREAMING_SNAKE_CASE__       )
       if key_size < block_size * 8:
              sys.exit(
                  """ERROR: Block size is {} bits and key size is {} bits. The RSA cipher """
                  """requires the block size to be equal to or greater than the key size. """
                  """Either decrease the block size or use different keys.""".format(
                      block_size * 8      ,			SCREAMING_SNAKE_CASE__       )       )

       lowercase							:  int 			=   [str(SCREAMING_SNAKE_CASE__       ) for i in encrypt_message(SCREAMING_SNAKE_CASE__      ,			(n, e)      ,			SCREAMING_SNAKE_CASE__       )]

       lowercase							:  Any 			=   """,""".join(SCREAMING_SNAKE_CASE__       )
       lowercase							:  List[str] 			=   f"{len(SCREAMING_SNAKE_CASE__       )}_{block_size}_{encrypted_content}"
       with open(SCREAMING_SNAKE_CASE__      ,			"""w"""       ) as fo:
              fo.write(SCREAMING_SNAKE_CASE__       )
       return encrypted_content







def 		_snake_case(						SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )				->					str:
       lowercase			,    lowercase			,    lowercase							:  str 			=   read_key_file(SCREAMING_SNAKE_CASE__       )
       with open(SCREAMING_SNAKE_CASE__       ) as fo:
              lowercase							:  Tuple 			=   fo.read()
       lowercase			,    lowercase			,    lowercase							:  List[Any] 			=   content.split("""_"""       )
       lowercase							:  Optional[Any] 			=   int(SCREAMING_SNAKE_CASE__       )
       lowercase							:  Optional[int] 			=   int(SCREAMING_SNAKE_CASE__       )

       if key_size < block_size * 8:
              sys.exit(
                  """ERROR: Block size is {} bits and key size is {} bits. The RSA cipher """
                  """requires the block size to be equal to or greater than the key size. """
                  """Did you specify the correct key file and encrypted file?""".format(
                      block_size * 8      ,			SCREAMING_SNAKE_CASE__       )       )

       lowercase							:  Union[str, Any] 			=   []
       for block in encrypted_message.split(""","""       ):
              encrypted_blocks.append(int(SCREAMING_SNAKE_CASE__       )       )

       return decrypt_message(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			(n, d)      ,			SCREAMING_SNAKE_CASE__       )







def 		_snake_case(						)				->					None:
       lowercase							:  Union[str, Any] 			=   """encrypted_file.txt"""
       lowercase							:  Any 			=   input(R"""Encrypt\Decrypt [e\d]: """       )

       if response.lower().startswith("""e"""       ):
              lowercase							:  str 			=   """encrypt"""
       elif response.lower().startswith("""d"""       ):
              lowercase							:  str 			=   """decrypt"""

       if mode == "encrypt":
              if not os.path.exists("""rsa_pubkey.txt"""       ):
                     rkg.make_key_files("""rsa"""      ,			1_024       )

              lowercase							:  List[str] 			=   input("""\nEnter message: """       )
              lowercase							:  Any 			=   """rsa_pubkey.txt"""
              print(f"Encrypting and writing to {filename}..."       )
              lowercase							:  Tuple 			=   encrypt_and_write_to_file(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )

              print("""\nEncrypted text:"""       )
              print(SCREAMING_SNAKE_CASE__       )

       elif mode == "decrypt":
              lowercase							:  str 			=   """rsa_privkey.txt"""
              print(f"Reading from {filename} and decrypting..."       )
              lowercase							:  Optional[int] 			=   read_from_file_and_decrypt(SCREAMING_SNAKE_CASE__      ,			SCREAMING_SNAKE_CASE__       )
              print("""writing decryption to rsa_decryption.txt..."""       )
              with open("""rsa_decryption.txt"""      ,			"""w"""       ) as dec:
                     dec.write(SCREAMING_SNAKE_CASE__       )

              print("""\nDecryption:"""       )
              print(SCREAMING_SNAKE_CASE__       )


if __name__ == "__main__":
  main()


import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs


if is_torch_available():
  import torch

if is_vision_available():
  from PIL import Image

  from transformers import VideoMAEImageProcessor

class __snake_case	(   unittest.TestCase  ):
    def __init__(						self	,snake_case	,snake_case=7	,snake_case=3	,snake_case=10	,snake_case=18	,snake_case=30	,snake_case=400	,snake_case=True	,snake_case=None	,snake_case=True	,snake_case=[0.5, 0.5, 0.5]	,snake_case=[0.5, 0.5, 0.5]	,snake_case=None	,):



           '''simple docstring'''







           lowercase							:  Dict 			=   size if size is not None else {"""shortest_edge""": 18}
           lowercase							:  Tuple 			=   crop_size if crop_size is not None else {"""height""": 18, """width""": 18}

           lowercase							:  Optional[int] 			=   parent
           lowercase							:  Any 			=   batch_size
           lowercase							:  int 			=   num_channels
           lowercase							:  Dict 			=   num_frames
           lowercase							:  Any 			=   image_size
           lowercase							:  str 			=   min_resolution
           lowercase							:  Any 			=   max_resolution
           lowercase							:  Tuple 			=   do_resize
           lowercase							:  Optional[Any] 			=   size
           lowercase							:  str 			=   do_normalize
           lowercase							:  Optional[Any] 			=   image_mean
           lowercase							:  Optional[Any] 			=   image_std
           lowercase							:  Union[str, Any] 			=   crop_size
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           return {
               "image_mean": self.image_mean,
               "image_std": self.image_std,
               "do_normalize": self.do_normalize,
               "do_resize": self.do_resize,
               "size": self.size,
               "crop_size": self.crop_size,
           }






@require_torch
@require_vision
class __snake_case	(   lowerCAmelCase      ,			unittest.TestCase  ):
    _a	:		Optional[Any]=       VideoMAEImageProcessor if is_vision_available() else None
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  Any 			=   VideoMAEImageProcessingTester(self   )
    @property
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           return self.image_processor_tester.prepare_image_processor_dict()
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  Any 			=   self.image_processing_class(**self.image_processor_dict   )
           self.assertTrue(hasattr(snake_case	,"""image_mean"""   )   )
           self.assertTrue(hasattr(snake_case	,"""image_std"""   )   )
           self.assertTrue(hasattr(snake_case	,"""do_normalize"""   )   )
           self.assertTrue(hasattr(snake_case	,"""do_resize"""   )   )
           self.assertTrue(hasattr(snake_case	,"""do_center_crop"""   )   )
           self.assertTrue(hasattr(snake_case	,"""size"""   )   )
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  List[str] 			=   self.image_processing_class.from_dict(self.image_processor_dict   )
           self.assertEqual(image_processor.size	,{"""shortest_edge""": 18}   )
           self.assertEqual(image_processor.crop_size	,{"""height""": 18, """width""": 18}   )

           lowercase							:  Any 			=   self.image_processing_class.from_dict(self.image_processor_dict	,size=42	,crop_size=84   )
           self.assertEqual(image_processor.size	,{"""shortest_edge""": 42}   )
           self.assertEqual(image_processor.crop_size	,{"""height""": 84, """width""": 84}   )
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           pass
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  Tuple 			=   self.image_processing_class(**self.image_processor_dict   )
           # create random PIL videos
           lowercase							:  Optional[int] 			=   prepare_video_inputs(self.image_processor_tester	,equal_resolution=snake_case   )
           for video in video_inputs:
                  self.assertIsInstance(snake_case	,snake_case   )
                  self.assertIsInstance(video[0]	,Image.Image   )

           # Test not batched input
           lowercase							:  Optional[Any] 			=   image_processing(video_inputs[0]	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   1,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)

           # Test batched
           lowercase							:  Union[str, Any] 			=   image_processing(snake_case	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   self.image_processor_tester.batch_size,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  Dict 			=   self.image_processing_class(**self.image_processor_dict   )
           # create random numpy tensors
           lowercase							:  Optional[Any] 			=   prepare_video_inputs(self.image_processor_tester	,equal_resolution=snake_case	,numpify=snake_case   )
           for video in video_inputs:
                  self.assertIsInstance(snake_case	,snake_case   )
                  self.assertIsInstance(video[0]	,np.ndarray   )

           # Test not batched input
           lowercase							:  int 			=   image_processing(video_inputs[0]	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   1,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)

           # Test batched
           lowercase							:  Optional[int] 			=   image_processing(snake_case	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   self.image_processor_tester.batch_size,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)
    def    _SCREAMING_SNAKE_CASE (						self   ):



           '''simple docstring'''







           lowercase							:  Dict 			=   self.image_processing_class(**self.image_processor_dict   )
           # create random PyTorch tensors
           lowercase							:  List[str] 			=   prepare_video_inputs(self.image_processor_tester	,equal_resolution=snake_case	,torchify=snake_case   )
           for video in video_inputs:
                  self.assertIsInstance(snake_case	,snake_case   )
                  self.assertIsInstance(video[0]	,torch.Tensor   )

           # Test not batched input
           lowercase							:  Optional[Any] 			=   image_processing(video_inputs[0]	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   1,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)

           # Test batched
           lowercase							:  Union[str, Any] 			=   image_processing(snake_case	,return_tensors="""pt"""   ).pixel_values
           self.assertEqual(
               encoded_videos.shape	,(
                   self.image_processor_tester.batch_size,
                   self.image_processor_tester.num_frames,
                   self.image_processor_tester.num_channels,
                   self.image_processor_tester.crop_size["""height"""],
                   self.image_processor_tester.crop_size["""width"""],
               )	,)
