


from __future__ import annotations

import unittest

from transformers import DebertaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
     import tensorflow as tf

     from transformers import (
         TFDebertaForMaskedLM,
         TFDebertaForQuestionAnswering,
         TFDebertaForSequenceClassification,
         TFDebertaForTokenClassification,
         TFDebertaModel,
     )







class 	_snake_case						:




 def __init__(	self      ,						_lowerCamelCase      ,						_lowerCamelCase=13      ,						_lowerCamelCase=7      ,						_lowerCamelCase=True      ,						_lowerCamelCase=True      ,						_lowerCamelCase=True      ,						_lowerCamelCase=True      ,						_lowerCamelCase=99      ,						_lowerCamelCase=32      ,						_lowerCamelCase=2      ,						_lowerCamelCase=4      ,						_lowerCamelCase=37      ,						_lowerCamelCase="gelu"      ,						_lowerCamelCase=0.1      ,						_lowerCamelCase=0.1      ,						_lowerCamelCase=512      ,						_lowerCamelCase=16      ,						_lowerCamelCase=2      ,						_lowerCamelCase=0.02      ,						_lowerCamelCase=3      ,						_lowerCamelCase=4      ,						_lowerCamelCase=None      ,						):
       a		:str											= parent
       a		:int											= 13
       a		:str											= 7
       a		:int											= True
       a		:Tuple											= True
       a		:str											= True
       a		:Optional[int]											= True
       a		:Tuple											= 99
       a		:Dict											= 32
       a		:Dict											= 2
       a		:str											= 4
       a		:List[Any]											= 37
       a		:Any											= '''gelu'''
       a		:List[Any]											= 0.1
       a		:Tuple											= 0.1
       a		:Union[str, Any]											= 512
       a		:List[str]											= 16
       a		:str											= False
       a		:int											= -1
       a		:int											= True
       a		:Optional[int]											= 2
       a		:Any											= 0.02
       a		:int											= 3
       a		:Tuple											= 4
       a		:Union[str, Any]											= None




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:List[str]											= ids_tensor([self.batch_size, self.seq_length]      ,						self.vocab_size					)

       a		:Optional[Any]											= None
       if self.use_input_mask:
             a		:Union[str, Any]											= random_attention_mask([self.batch_size, self.seq_length]					)

       a		:Optional[int]											= None
       if self.use_token_type_ids:
             a		:List[str]											= ids_tensor([self.batch_size, self.seq_length]      ,						self.type_vocab_size					)

       a		:List[Any]											= None
       a		:List[Any]											= None
       a		:Any											= None
       if self.use_labels:
             a		:Dict											= ids_tensor([self.batch_size]      ,						self.type_sequence_label_size					)
             a		:Optional[Any]											= ids_tensor([self.batch_size, self.seq_length]      ,						self.num_labels					)

       a		:List[Any]											= DebertaConfig(
           vocab_size=self.vocab_size      ,						hidden_size=self.hidden_size      ,						num_hidden_layers=self.num_hidden_layers      ,						num_attention_heads=self.num_attention_heads      ,						intermediate_size=self.intermediate_size      ,						hidden_act=self.hidden_act      ,						hidden_dropout_prob=self.hidden_dropout_prob      ,						attention_probs_dropout_prob=self.attention_probs_dropout_prob      ,						max_position_embeddings=self.max_position_embeddings      ,						type_vocab_size=self.type_vocab_size      ,						relative_attention=self.relative_attention      ,						max_relative_positions=self.max_relative_positions      ,						position_biased_input=self.position_biased_input      ,						initializer_range=self.initializer_range      ,						return_dict=_lowerCamelCase      ,						)

       return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels




 def  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					):
       a		:Optional[int]											= TFDebertaModel(config=_lowerCamelCase					)
       a		:Tuple											= {'''input_ids''': input_ids, '''attention_mask''': input_mask, '''token_type_ids''': token_type_ids}

       a		:Optional[int]											= [input_ids, input_mask]
       a		:List[Any]											= model(_lowerCamelCase					)

       a		:List[Any]											= model(_lowerCamelCase					)

       self.parent.assertEqual(result.last_hidden_state.shape      ,						(self.batch_size, self.seq_length, self.hidden_size)					)




 def  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					):
       a		:List[Any]											= TFDebertaForMaskedLM(config=_lowerCamelCase					)
       a		:Tuple											= {
           '''input_ids''': input_ids,
           '''attention_mask''': input_mask,
           '''token_type_ids''': token_type_ids,
       }
       a		:Union[str, Any]											= model(_lowerCamelCase					)
       self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.seq_length, self.vocab_size)					)




 def  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					):
       a		:int											= self.num_labels
       a		:Dict											= TFDebertaForSequenceClassification(config=_lowerCamelCase					)
       a		:Tuple											= {
           '''input_ids''': input_ids,
           '''attention_mask''': input_mask,
           '''token_type_ids''': token_type_ids,
       }

       a		:Optional[int]											= model(_lowerCamelCase					)
       self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.num_labels)					)




 def  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					):
       a		:Union[str, Any]											= self.num_labels
       a		:Dict											= TFDebertaForTokenClassification(config=_lowerCamelCase					)
       a		:List[str]											= {
           '''input_ids''': input_ids,
           '''attention_mask''': input_mask,
           '''token_type_ids''': token_type_ids,
       }
       a		:List[str]											= model(_lowerCamelCase					)
       self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.seq_length, self.num_labels)					)




 def  SCREAMING_SNAKE_CASE__       (	self      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					):
       a		:List[Any]											= TFDebertaForQuestionAnswering(config=_lowerCamelCase					)
       a		:Tuple											= {
           '''input_ids''': input_ids,
           '''attention_mask''': input_mask,
           '''token_type_ids''': token_type_ids,
       }

       a		:Optional[Any]											= model(_lowerCamelCase					)
       self.parent.assertEqual(result.start_logits.shape      ,						(self.batch_size, self.seq_length)					)
       self.parent.assertEqual(result.end_logits.shape      ,						(self.batch_size, self.seq_length)					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Optional[int]											= self.prepare_config_and_inputs()
       (
           a       
       )		:List[str]											= config_and_inputs
       a		:Optional[int]											= {'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': input_mask}
       return config, inputs_dict







@require_tf
class 	_snake_case						(   _snake_case		,					_snake_case		,					unittest.TestCase							):
 SCREAMING_SNAKE_CASE__   = (
     (
         TFDebertaModel,
         TFDebertaForMaskedLM,
         TFDebertaForQuestionAnswering,
         TFDebertaForSequenceClassification,
         TFDebertaForTokenClassification,
     )
     if is_tf_available()
     else ()
 )
 SCREAMING_SNAKE_CASE__   = (
     {
         'feature-extraction': TFDebertaModel,
         'fill-mask': TFDebertaForMaskedLM,
         'question-answering': TFDebertaForQuestionAnswering,
         'text-classification': TFDebertaForSequenceClassification,
         'token-classification': TFDebertaForTokenClassification,
         'zero-shot': TFDebertaForSequenceClassification,
     }
     if is_tf_available()
     else {}
 )

 SCREAMING_SNAKE_CASE__   = False
 SCREAMING_SNAKE_CASE__   = False




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Dict											= TFDebertaModelTester(self					)
       a		:Union[str, Any]											= ConfigTester(self      ,						config_class=_lowerCamelCase      ,						hidden_size=37					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       self.config_tester.run_common_tests()




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:List[str]											= self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_model(*_lowerCamelCase					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Optional[int]											= self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_masked_lm(*_lowerCamelCase					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Dict											= self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_question_answering(*_lowerCamelCase					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Any											= self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_sequence_classification(*_lowerCamelCase					)




 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Optional[Any]											= self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_for_token_classification(*_lowerCamelCase					)




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Dict											= TFDebertaModel.from_pretrained('''kamalkraj/deberta-base'''					)
       self.assertIsNotNone(_lowerCamelCase					)







@require_tf
class 	_snake_case						(   unittest.TestCase							):




 @unittest.skip(reason='''Model not available yet'''					)
 def  SCREAMING_SNAKE_CASE__       (	self					):
       pass




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Any											= TFDebertaModel.from_pretrained('''kamalkraj/deberta-base'''					)
       a		:Tuple											= tf.constant([[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]]					)
       a		:Any											= tf.constant([[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]					)
       a		:List[str]											= model(_lowerCamelCase      ,						attention_mask=_lowerCamelCase					)[0]

       a		:Tuple											= tf.constant(
           [
               [
                   [-0.5985_5896, -0.8055_2566, -0.846_2135],
                   [1.448_4025, -0.9348_3794, -0.8059_3085],
                   [0.312_2741, 0.0031_6059, -1.413_1377],
               ]
           ]					)
       tf.debugging.assert_near(output[:, 1:4, 1:4]      ,						_lowerCamelCase      ,						atol=1e-4					)









import os
import sys

from . import rsa_key_generator as rkg

snake_case       :					int        =  1_28
snake_case       :					Any        =  2_56
def        __lowerCamelCase		(				UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	int = DEFAULT_BLOCK_SIZE		):




      """simple docstring"""





      a		:Union[str, Any]											= message.encode('''ascii'''		)

      a		:List[Any]											= []
      for block_start in range(0				,						len(UpperCAmelCase_		)				,						UpperCAmelCase_		):
            a		:List[str]											= 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        __lowerCamelCase		(				UpperCAmelCase_		:	list[int]				,						UpperCAmelCase_		:	int				,						UpperCAmelCase_		:	int = DEFAULT_BLOCK_SIZE		):




      """simple docstring"""





      a		:list[str]											= []
      for block_int in block_ints:
            a		:list[str]											= []
            for i in range(block_size - 1				,						-1				,						-1		):
                  if len(UpperCAmelCase_		) + i < message_length:
                        a		:List[str]											= block_int // (BYTE_SIZE**i)
                        a		:List[str]											= block_int % (BYTE_SIZE**i)
                        block_message.insert(0				,						chr(UpperCAmelCase_		)		)
            message.extend(UpperCAmelCase_		)
      return "".join(UpperCAmelCase_		)
def        __lowerCamelCase		(				UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	tuple[int, int]				,						UpperCAmelCase_		:	int = DEFAULT_BLOCK_SIZE		):




      """simple docstring"""





      a		:Tuple											= []
      a							,       a		:Any											= key

      for block in get_blocks_from_text(UpperCAmelCase_				,						UpperCAmelCase_		):
            encrypted_blocks.append(pow(UpperCAmelCase_				,						UpperCAmelCase_				,						UpperCAmelCase_		)		)
      return encrypted_blocks
def        __lowerCamelCase		(				UpperCAmelCase_		:	list[int]				,						UpperCAmelCase_		:	int				,						UpperCAmelCase_		:	tuple[int, int]				,						UpperCAmelCase_		:	int = DEFAULT_BLOCK_SIZE				,						):




      """simple docstring"""





      a		:Optional[Any]											= []
      a							,       a		:int											= key
      for block in encrypted_blocks:
            decrypted_blocks.append(pow(UpperCAmelCase_				,						UpperCAmelCase_				,						UpperCAmelCase_		)		)
      return get_text_from_blocks(UpperCAmelCase_				,						UpperCAmelCase_				,						UpperCAmelCase_		)
def        __lowerCamelCase		(				UpperCAmelCase_		:	str		):




      """simple docstring"""





      with open(UpperCAmelCase_		) as fo:
            a		:Dict											= fo.read()
      a							,       a							,       a		:Tuple											= content.split(''','''		)
      return (int(UpperCAmelCase_		), int(UpperCAmelCase_		), int(UpperCAmelCase_		))
def        __lowerCamelCase		(				UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	int = DEFAULT_BLOCK_SIZE				,						):




      """simple docstring"""





      a							,       a							,       a		:List[str]											= 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		:int											= [str(UpperCAmelCase_		) for i in encrypt_message(UpperCAmelCase_				,						(n, e)				,						UpperCAmelCase_		)]

      a		:str											= ''','''.join(UpperCAmelCase_		)
      a		:Optional[Any]											= F'''{len(UpperCAmelCase_		)}_{block_size}_{encrypted_content}'''
      with open(UpperCAmelCase_				,						'''w'''		) as fo:
            fo.write(UpperCAmelCase_		)
      return encrypted_content
def        __lowerCamelCase		(				UpperCAmelCase_		:	str				,						UpperCAmelCase_		:	str		):




      """simple docstring"""





      a							,       a							,       a		:List[Any]											= read_key_file(UpperCAmelCase_		)
      with open(UpperCAmelCase_		) as fo:
            a		:int											= fo.read()
      a							,       a							,       a		:List[str]											= content.split('''_'''		)
      a		:List[str]											= int(UpperCAmelCase_		)
      a		:List[str]											= 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		:Dict											= []
      for block in encrypted_message.split(''','''		):
            encrypted_blocks.append(int(UpperCAmelCase_		)		)

      return decrypt_message(UpperCAmelCase_				,						UpperCAmelCase_				,						(n, d)				,						UpperCAmelCase_		)
def        __lowerCamelCase		(				):




      """simple docstring"""





      a		:Union[str, Any]											= '''encrypted_file.txt'''
      a		:List[Any]											= input(R'''Encrypt\Decrypt [e\d]: '''		)

      if response.lower().startswith('''e'''		):
            a		:int											= '''encrypt'''
      elif response.lower().startswith('''d'''		):
            a		:Optional[Any]											= '''decrypt'''

      if mode == "encrypt":
            if not os.path.exists('''rsa_pubkey.txt'''		):
                  rkg.make_key_files('''rsa'''				,						1024		)

            a		:List[str]											= input('''\nEnter message: '''		)
            a		:str											= '''rsa_pubkey.txt'''
            print(F'''Encrypting and writing to {filename}...'''		)
            a		:Optional[int]											= encrypt_and_write_to_file(UpperCAmelCase_				,						UpperCAmelCase_				,						UpperCAmelCase_		)

            print('''\nEncrypted text:'''		)
            print(UpperCAmelCase_		)

      elif mode == "decrypt":
            a		:str											= '''rsa_privkey.txt'''
            print(F'''Reading from {filename} and decrypting...'''		)
            a		:Optional[int]											= 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()





