


import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin







class 						_snake_case    ( _snake_case		,       unittest.TestCase				):
 SCREAMING_SNAKE_CASE__ =			BlenderbotSmallTokenizer
 SCREAMING_SNAKE_CASE__ =			False




 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       super().setUp()

       a		:List[str]									=			['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
       a		:int									=			dict(zip(_lowerCamelCase   ,    range(len(_lowerCamelCase       )       )       )       )

       a		:List[str]									=			['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
       a		:Optional[int]									=			{'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

       a		:int									=			os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES['''vocab_file''']       )
       a		:Dict									=			os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES['''merges_file''']       )
       with open(self.vocab_file   ,    '''w'''   ,    encoding='''utf-8'''       ) as fp:
             fp.write(json.dumps(_lowerCamelCase       ) + '''\n'''       )
       with open(self.merges_file   ,    '''w'''   ,    encoding='''utf-8'''       ) as fp:
             fp.write('''\n'''.join(_lowerCamelCase       )       )




 def 			SCREAMING_SNAKE_CASE__							(						self   ,    **_lowerCamelCase       ):
       kwargs.update(self.special_tokens_map       )
       return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname   ,    **_lowerCamelCase       )




 def 			SCREAMING_SNAKE_CASE__							(						self   ,    _lowerCamelCase       ):
       a		:str									=			'''adapt act apte'''
       a		:int									=			'''adapt act apte'''
       return input_text, output_text




 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       a		:Dict									=			BlenderbotSmallTokenizer(self.vocab_file   ,    self.merges_file   ,    **self.special_tokens_map       )
       a		:int									=			'''adapt act apte'''
       a		:List[Any]									=			['''adapt''', '''act''', '''ap@@''', '''te''']
       a		:int									=			tokenizer.tokenize(_lowerCamelCase       )
       self.assertListEqual(_lowerCamelCase   ,    _lowerCamelCase       )

       a		:List[Any]									=			[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

       a		:str									=			[0, 1, 2, 3, 4, 5]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase       )   ,    _lowerCamelCase       )




 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       a		:List[Any]									=			BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
       assert tok('''sam'''       ).input_ids == [1384]
       a		:Tuple									=			'''I am a small frog.'''
       a		:Optional[int]									=			tok([src_text]   ,    padding=_lowerCamelCase   ,    truncation=_lowerCamelCase       )['''input_ids''']
       a		:List[Any]									=			tok.batch_decode(_lowerCamelCase   ,    skip_special_tokens=_lowerCamelCase   ,    clean_up_tokenization_spaces=_lowerCamelCase       )[0]
       assert src_text != decoded  # I wish it did!
       assert decoded == "i am a small frog ."




 def 			SCREAMING_SNAKE_CASE__							(						self       ):
       a		:Union[str, Any]									=			BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''       )
       a		:Optional[Any]									=			'''I am a small frog .'''
       a		:int									=			'''.'''
       a		:List[str]									=			tok(_lowerCamelCase       )['''input_ids''']
       a		:Union[str, Any]									=			tok(_lowerCamelCase       )['''input_ids''']

       assert encoded[-1] == encoded_dot[0]









import qiskit
def 							__lowerCamelCase		(					UpperCAmelCase_		:						int					,    UpperCAmelCase_		:						int		):




      """simple docstring"""





      a		:Tuple									=			qiskit.Aer.get_backend('''aer_simulator'''		)

      # Create a Quantum Circuit acting on the q register
      a		:str									=			qiskit.QuantumCircuit(UpperCAmelCase_					,    UpperCAmelCase_		)

      # Apply X (NOT) Gate to Qubits 0 & 1
      circuit.x(0		)
      circuit.x(1		)

      # Map the quantum measurement to the classical bits
      circuit.measure([0, 1]					,    [0, 1]		)

      # Execute the circuit on the qasm simulator
      a		:Optional[Any]									=			qiskit.execute(UpperCAmelCase_					,    UpperCAmelCase_					,    shots=1000		)

      # Return the histogram data of the results of the experiment.
      return job.result().get_counts(UpperCAmelCase_		)


if __name__ == "__main__":
     snake_case							:       Any										=	single_qubit_measure(2, 2)
     print(F"""Total count for various states are: {counts}""")





