
from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


UpperCamelCase_   	=	logging.get_logger(__name__)

UpperCamelCase_   	=	{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCamelCase_   	=	{
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

UpperCamelCase_   	=	{
    "facebook/blenderbot_small-90M": 5_1_2,
}

class       a		(   __UpperCAmelCase					):
							lowercase_		:						Tuple   							=  VOCAB_FILES_NAMES
							lowercase_		:						Optional[int]   							=  PRETRAINED_VOCAB_FILES_MAP
							lowercase_		:						str   							=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_		:						str   							=  BlenderbotSmallTokenizer







							def __init__(						self  :  List[Any]      ,				snake_case__  :  Any=None      ,				snake_case__  :  Dict=None      ,				snake_case__  :  Optional[int]="<|endoftext|>"      ,				snake_case__  :  Optional[int]="<|endoftext|>"      ,				snake_case__  :  List[str]="<|endoftext|>"      ,				snake_case__  :  List[Any]=False      ,				snake_case__  :  int=True      ,				**snake_case__  :  Any      ,				):
								"""simple docstring"""







								super().__init__(
								    ByteLevelBPETokenizer(
								        vocab=snake_case__      ,				merges=snake_case__      ,				add_prefix_space=snake_case__      ,				trim_offsets=snake_case__      ,				)      ,				bos_token=snake_case__      ,				eos_token=snake_case__      ,				unk_token=snake_case__      ,				**snake_case__      ,				)
								__lowerCAmelCase         =							add_prefix_space







							def       UpperCAmelCase__					(						self  :  List[Any]      ,				snake_case__  :  Tuple      ,				snake_case__  :  Tuple=None ):
								"""simple docstring"""







								__lowerCAmelCase         =							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







							def       UpperCAmelCase__					(						self  :  str      ,				snake_case__  :  List[int]      ,				snake_case__  :  Optional[List[int]] = None ):
								"""simple docstring"""







								__lowerCAmelCase         =							[self.sep_token_id]
								__lowerCAmelCase         =							[self.cls_token_id]

								if token_ids_a is None:
									return len(cls + token_ids_a + sep ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]








import numpy as np
import qiskit






def 		_UpperCAmelCase   (	UpperCamelCase:     int = 8			,							UpperCamelCase:     int | None = None  ):






	"""simple docstring"""


	__lowerCAmelCase         =							np.random.default_rng(seed=UpperCamelCase  )

	# Roughly 25% of the qubits will contribute to the key.
	# So we take more than we need.
	__lowerCAmelCase         =							6 * key_len
	# Measurement basis for Alice's qubits.
	__lowerCAmelCase         =							rng.integers(2			,							size=UpperCamelCase  )
	# The set of states Alice will prepare.
	__lowerCAmelCase         =							rng.integers(2			,							size=UpperCamelCase  )
	# Measurement basis for Bob's qubits.
	__lowerCAmelCase         =							rng.integers(2			,							size=UpperCamelCase  )

	# Quantum Circuit to simulate BB84
	__lowerCAmelCase         =							qiskit.QuantumCircuit(UpperCamelCase			,							name="BB84"  )

	# Alice prepares her qubits according to rules above.
	for index, _ in enumerate(UpperCamelCase  ):
		if alice_state[index] == 1:
			bbaa_circ.x(UpperCamelCase  )
		if alice_basis[index] == 1:
			bbaa_circ.h(UpperCamelCase  )
	bbaa_circ.barrier()

	# Bob measures the received qubits according to rules above.
	for index, _ in enumerate(UpperCamelCase  ):
		if bob_basis[index] == 1:
			bbaa_circ.h(UpperCamelCase  )

	bbaa_circ.barrier()
	bbaa_circ.measure_all()

	# Simulate the quantum circuit.
	__lowerCAmelCase         =							qiskit.Aer.get_backend("aer_simulator"  )
	# We only need to run one shot because the key is unique.
	# Multiple shots will produce the same key.
	__lowerCAmelCase         =							qiskit.execute(UpperCamelCase			,							UpperCamelCase			,							shots=1			,							seed_simulator=UpperCamelCase  )
	# Returns the result of measurement.
	__lowerCAmelCase         =							job.result().get_counts(UpperCamelCase  ).most_frequent()

	# Extracting the generated key from the simulation results.
	# Only keep measurement results where Alice and Bob chose the same basis.
	__lowerCAmelCase         =							"".join(
	    [
	        result_bit
	        for alice_basis_bit, bob_basis_bit, result_bit in zip(
	            UpperCamelCase			,							UpperCamelCase			,							UpperCamelCase  )
	        if alice_basis_bit == bob_basis_bit
	    ]  )

	# Get final key. Pad with 0 if too short, otherwise truncate.
	__lowerCAmelCase         =							gen_key[:key_len] if len(UpperCamelCase  ) >= key_len else gen_key.ljust(UpperCamelCase			,							"0"  )
	return key


if __name__ == "__main__":
					print(f'''The generated key is : {bbaa(8, seed=0)}''')
					from doctest import testmod

					testmod()






