


import os
import sys

from . import rsa_key_generator as rkg

__lowerCamelCase   	=  128
__lowerCamelCase   	=  256



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase = DEFAULT_BLOCK_SIZE			):
     a_     :  Union[str, Any]				      =     message.encode("""ascii"""			)

     a_     :  Dict				      =     []
     for block_start in range(0	,	len(UpperCamelCase_			)	,	UpperCamelCase_			):
          a_     :  Union[str, Any]				      =     0
          for i in range(UpperCamelCase_	,	min(block_start + block_size	,	len(UpperCamelCase_			)			)			):
               block_int += message_bytes[i] * (BYTE_SIZE ** (i % block_size))
          block_ints.append(UpperCamelCase_			)
     return block_ints



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase = DEFAULT_BLOCK_SIZE			):
     a_     :  Any				      =     []
     for block_int in block_ints:
          a_     :  Any				      =     []
          for i in range(block_size - 1	,	-1	,	-1			):
               if len(UpperCamelCase_			) + i < message_length:
                    a_     :  int				      =     block_int // (BYTE_SIZE**i)
                    a_     :  Dict				      =     block_int % (BYTE_SIZE**i)
                    block_message.insert(0	,	chr(UpperCamelCase_			)			)
          message.extend(UpperCamelCase_			)
     return "".join(UpperCamelCase_			)



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase = DEFAULT_BLOCK_SIZE			):
     a_     :  Any				      =     []
     a_      ,      a_     :  Tuple				      =     key

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



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase = DEFAULT_BLOCK_SIZE	,	):
     a_     :  Optional[Any]				      =     []
     a_      ,      a_     :  str				      =     key
     for block in encrypted_blocks:
          decrypted_blocks.append(pow(UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_			)			)
     return get_text_from_blocks(UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_			)



def 			_a      (    __UpperCamelCase			):


     with open(UpperCamelCase_			) as fo:
          a_     :  Optional[int]				      =     fo.read()
     a_      ,      a_      ,      a_     :  str				      =     content.split(""","""			)
     return (int(UpperCamelCase_			), int(UpperCamelCase_			), int(UpperCamelCase_			))



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase	,	__UpperCamelCase = DEFAULT_BLOCK_SIZE	,	):
     a_      ,      a_      ,      a_     :  Optional[Any]				      =     read_key_file(UpperCamelCase_			)
     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	,	UpperCamelCase_			)			)

     a_     :  Any				      =     [str(UpperCamelCase_			) for i in encrypt_message(UpperCamelCase_	,	(n, e)	,	UpperCamelCase_			)]

     a_     :  int				      =     """,""".join(UpperCamelCase_			)
     a_     :  List[Any]				      =     F'''{len(UpperCamelCase_			)}_{block_size}_{encrypted_content}'''
     with open(UpperCamelCase_	,	"""w"""			) as fo:
          fo.write(UpperCamelCase_			)
     return encrypted_content



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase			):
     a_      ,      a_      ,      a_     :  Any				      =     read_key_file(UpperCamelCase_			)
     with open(UpperCamelCase_			) as fo:
          a_     :  Optional[int]				      =     fo.read()
     a_      ,      a_      ,      a_     :  Union[str, Any]				      =     content.split("""_"""			)
     a_     :  int				      =     int(UpperCamelCase_			)
     a_     :  Optional[Any]				      =     int(UpperCamelCase_			)

     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	,	UpperCamelCase_			)			)

     a_     :  str				      =     []
     for block in encrypted_message.split(""","""			):
          encrypted_blocks.append(int(UpperCamelCase_			)			)

     return decrypt_message(UpperCamelCase_	,	UpperCamelCase_	,	(n, d)	,	UpperCamelCase_			)



def 			_a      (    ):
     a_     :  Union[str, Any]				      =     """encrypted_file.txt"""
     a_     :  int				      =     input(r"""Encrypt\Decrypt [e\d]: """			)

     if response.lower().startswith("""e"""			):
          a_     :  Union[str, Any]				      =     """encrypt"""
     elif response.lower().startswith("""d"""			):
          a_     :  Dict				      =     """decrypt"""

     if mode == "encrypt":
          if not os.path.exists("""rsa_pubkey.txt"""			):
               rkg.make_key_files("""rsa"""	,	1_0_2_4			)

          a_     :  Dict				      =     input("""\nEnter message: """			)
          a_     :  Optional[Any]				      =     """rsa_pubkey.txt"""
          print(F'''Encrypting and writing to {filename}...'''			)
          a_     :  str				      =     encrypt_and_write_to_file(UpperCamelCase_	,	UpperCamelCase_	,	UpperCamelCase_			)

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

     elif mode == "decrypt":
          a_     :  Union[str, Any]				      =     """rsa_privkey.txt"""
          print(F'''Reading from {filename} and decrypting...'''			)
          a_     :  Any				      =     read_from_file_and_decrypt(UpperCamelCase_	,	UpperCamelCase_			)
          print("""writing decryption to rsa_decryption.txt..."""			)
          with open("""rsa_decryption.txt"""	,	"""w"""			) as dec:
               dec.write(UpperCamelCase_			)

          print("""\nDecryption:"""			)
          print(UpperCamelCase_			)


if __name__ == "__main__":
       main()






"""simple docstring"""





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_image_inputs


if is_torch_available():
   import torch

if is_vision_available():
   from PIL import Image

   from transformers import OwlViTImageProcessor




class    _lowerCAmelCase    (      unittest.TestCase  ):







 """simple docstring"""







 def __init__(     self				:     Union[str, Any],   UpperCAmelCase__				:     Dict,   UpperCAmelCase__				:     Optional[int]=7,   UpperCAmelCase__				:     List[str]=3,   UpperCAmelCase__				:     List[Any]=1_8,   UpperCAmelCase__				:     Any=3_0,   UpperCAmelCase__				:     str=4_0_0,   UpperCAmelCase__				:     Union[str, Any]=True,   UpperCAmelCase__				:     Dict=None,   UpperCAmelCase__				:     int=True,   UpperCAmelCase__				:     str=None,   UpperCAmelCase__				:     Dict=True,   UpperCAmelCase__				:     str=[0.48_145_466, 0.4_578_275, 0.40_821_073],   UpperCAmelCase__				:     Dict=[0.26_862_954, 0.26_130_258, 0.27_577_711],   UpperCAmelCase__				:     Any=True,   ):
    __lowercase								=		parent
    __lowercase								=		batch_size
    __lowercase								=		num_channels
    __lowercase								=		image_size
    __lowercase								=		min_resolution
    __lowercase								=		max_resolution
    __lowercase								=		do_resize
    __lowercase								=		size if size is not None else {"height": 1_8, "width": 1_8}
    __lowercase								=		do_center_crop
    __lowercase								=		crop_size if crop_size is not None else {"height": 1_8, "width": 1_8}
    __lowercase								=		do_normalize
    __lowercase								=		image_mean
    __lowercase								=		image_std
    __lowercase								=		do_convert_rgb



 def    _lowercase					(     self				:     List[str]      ):
    return {
        "do_resize": self.do_resize,
        "size": self.size,
        "do_center_crop": self.do_center_crop,
        "crop_size": self.crop_size,
        "do_normalize": self.do_normalize,
        "image_mean": self.image_mean,
        "image_std": self.image_std,
        "do_convert_rgb": self.do_convert_rgb,
    }







@require_torch
@require_vision
class    _lowerCAmelCase    (      lowercase	,unittest.TestCase  ):







 """simple docstring"""







 __UpperCAmelCase      :   List[str]  						=      OwlViTImageProcessor if is_vision_available() else None


 def    _lowercase					(     self				:     Dict      ):
    __lowercase								=		OwlViTImageProcessingTester(self      )


 @property
 def    _lowercase					(     self				:     int      ):
    return self.image_processor_tester.prepare_image_processor_dict()


 def    _lowercase					(     self				:     Tuple      ):
    __lowercase								=		self.image_processing_class(**self.image_processor_dict      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "do_resize"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "size"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "do_center_crop"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "center_crop"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "do_normalize"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "image_mean"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "image_std"      )      )
    self.assertTrue(hasattr(UpperCAmelCase__,   "do_convert_rgb"      )      )


 def    _lowercase					(     self				:     Dict      ):
    __lowercase								=		self.image_processing_class.from_dict(self.image_processor_dict      )
    self.assertEqual(image_processor.size,   {"height": 1_8, "width": 1_8}      )
    self.assertEqual(image_processor.crop_size,   {"height": 1_8, "width": 1_8}      )

    __lowercase								=		self.image_processing_class.from_dict(self.image_processor_dict,   size=4_2,   crop_size=8_4      )
    self.assertEqual(image_processor.size,   {"height": 4_2, "width": 4_2}      )
    self.assertEqual(image_processor.crop_size,   {"height": 8_4, "width": 8_4}      )


 def    _lowercase					(     self				:     Any      ):
    # Initialize image_processing
    __lowercase								=		self.image_processing_class(**self.image_processor_dict      )
    # create random PIL images
    __lowercase								=		prepare_image_inputs(self.image_processor_tester,   equal_resolution=UpperCAmelCase__      )

    for image in image_inputs:
       self.assertIsInstance(UpperCAmelCase__,   Image.Image      )

    # Test not batched input
    __lowercase								=		image_processing(image_inputs[0],   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            1,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )

    # Test batched
    __lowercase								=		image_processing(UpperCAmelCase__,   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            self.image_processor_tester.batch_size,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )


 def    _lowercase					(     self				:     Optional[Any]      ):
    # Initialize image_processing
    __lowercase								=		self.image_processing_class(**self.image_processor_dict      )
    # create random numpy tensors
    __lowercase								=		prepare_image_inputs(self.image_processor_tester,   equal_resolution=UpperCAmelCase__,   numpify=UpperCAmelCase__      )
    for image in image_inputs:
       self.assertIsInstance(UpperCAmelCase__,   np.ndarray      )

    # Test not batched input
    __lowercase								=		image_processing(image_inputs[0],   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            1,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )

    # Test batched
    __lowercase								=		image_processing(UpperCAmelCase__,   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            self.image_processor_tester.batch_size,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )



 def    _lowercase					(     self				:     List[str]      ):
    # Initialize image_processing
    __lowercase								=		self.image_processing_class(**self.image_processor_dict      )
    # create random PyTorch tensors
    __lowercase								=		prepare_image_inputs(self.image_processor_tester,   equal_resolution=UpperCAmelCase__,   torchify=UpperCAmelCase__      )
    for image in image_inputs:
       self.assertIsInstance(UpperCAmelCase__,   torch.Tensor      )

    # Test not batched input
    __lowercase								=		image_processing(image_inputs[0],   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            1,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )

    # Test batched
    __lowercase								=		image_processing(UpperCAmelCase__,   return_tensors="pt"      ).pixel_values
    self.assertEqual(
        encoded_images.shape,   (
            self.image_processor_tester.batch_size,
            self.image_processor_tester.num_channels,
            self.image_processor_tester.crop_size["height"],
            self.image_processor_tester.crop_size["width"],
        ),   )




