






"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_layoutlm import LayoutLMTokenizer


lowercase_								=	logging.get_logger(__name__)

lowercase_								=	{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

lowercase_								=	{
    'vocab_file': {
        'microsoft/layoutlm-base-uncased': (
            'https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/vocab.txt'
        ),
        'microsoft/layoutlm-large-uncased': (
            'https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'microsoft/layoutlm-base-uncased': (
            'https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/tokenizer.json'
        ),
        'microsoft/layoutlm-large-uncased': (
            'https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/tokenizer.json'
        ),
    },
}

lowercase_								=	{
    'microsoft/layoutlm-base-uncased': 512,
    'microsoft/layoutlm-large-uncased': 512,
}

lowercase_								=	{
    'microsoft/layoutlm-base-uncased': {'do_lower_case': True},
    'microsoft/layoutlm-large-uncased': {'do_lower_case': True},
}


class    snake_case						(				_lowerCAmelCase		):


   '''simple docstring'''

   A_		:      str							=					VOCAB_FILES_NAMES
   A_		:      Any							=					PRETRAINED_VOCAB_FILES_MAP
   A_		:      Union[str, Any]							=					PRETRAINED_INIT_CONFIGURATION
   A_		:      List[Any]							=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A_		:      Optional[int]							=					LayoutLMTokenizer


   def __init__(      self					:	Optional[Any],			_lowerCamelCase					:	List[Any]=None,			_lowerCamelCase					:	Dict=None,			_lowerCamelCase					:	Tuple=True,			_lowerCamelCase					:	List[Any]="[UNK]",			_lowerCamelCase					:	Dict="[SEP]",			_lowerCamelCase					:	Dict="[PAD]",			_lowerCamelCase					:	int="[CLS]",			_lowerCamelCase					:	Union[str, Any]="[MASK]",			_lowerCamelCase					:	List[Any]=True,			_lowerCamelCase					:	Optional[int]=None,			**_lowerCamelCase					:	str,			):

     '''simple docstring'''
     super().__init__(
         SCREAMING_SNAKE_CASE_,			tokenizer_file=SCREAMING_SNAKE_CASE_,			do_lower_case=SCREAMING_SNAKE_CASE_,			unk_token=SCREAMING_SNAKE_CASE_,			sep_token=SCREAMING_SNAKE_CASE_,			pad_token=SCREAMING_SNAKE_CASE_,			cls_token=SCREAMING_SNAKE_CASE_,			mask_token=SCREAMING_SNAKE_CASE_,			tokenize_chinese_chars=SCREAMING_SNAKE_CASE_,			strip_accents=SCREAMING_SNAKE_CASE_,			**SCREAMING_SNAKE_CASE_,			)

     __A		     =					json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
     if (
         normalizer_state.get('''lowercase''',			SCREAMING_SNAKE_CASE_    ) != do_lower_case
         or normalizer_state.get('''strip_accents''',			SCREAMING_SNAKE_CASE_    ) != strip_accents
         or normalizer_state.get('''handle_chinese_chars''',			SCREAMING_SNAKE_CASE_    ) != tokenize_chinese_chars
     ):
       __A		     =					getattr(SCREAMING_SNAKE_CASE_,			normalizer_state.pop('''type'''    )    )
       __A		     =					do_lower_case
       __A		     =					strip_accents
       __A		     =					tokenize_chinese_chars
       __A		     =					normalizer_class(**SCREAMING_SNAKE_CASE_    )

     __A		     =					do_lower_case


   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	int,			_lowerCamelCase					:	Optional[int]=None    ):

     '''simple docstring'''
     __A		     =					[self.cls_token_id] + token_ids_a + [self.sep_token_id]

     if token_ids_a:
       output += token_ids_a + [self.sep_token_id]

     return output


   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	List[int],			_lowerCamelCase					:	Optional[List[int]] = None    ):

     '''simple docstring'''
     __A		     =					[self.sep_token_id]
     __A		     =					[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    ) * [0] + len(token_ids_a + sep    ) * [1]






   def 							_SCREAMING_SNAKE_CASE							(      self					:	str,			_lowerCamelCase					:	str,			_lowerCamelCase					:	Optional[str] = None    ):

     '''simple docstring'''
     __A		     =					self._tokenizer.model.save(SCREAMING_SNAKE_CASE_,			name=SCREAMING_SNAKE_CASE_    )
     return tuple(SCREAMING_SNAKE_CASE_    )






'''simple docstring'''





import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute

def   A			(							A_				:       float = np.pi / 2     ,				A_				:       float = np.pi / 2     ,				A_				:       float = np.pi / 2							):
						snake_case							:  List[Any]			=     QuantumRegister(3     ,				'''qr'''							)  # Define the number of quantum bits
						snake_case							:  List[Any]			=     ClassicalRegister(1     ,				'''cr'''							)  # Define the number of classical bits

						snake_case							:  Dict			=     QuantumCircuit(A_     ,				A_							)  # Define the quantum circuit.

						# Build the circuit
						quantum_circuit.u(A_     ,				A_     ,				A_     ,				0							)  # Quantum State to teleport
						quantum_circuit.h(1							)  # add hadamard gate
						quantum_circuit.cx(
						    1     ,				2							)  # add control gate with qubit 1 as control and 2 as target.
						quantum_circuit.cx(0     ,				1							)
						quantum_circuit.h(0							)
						quantum_circuit.cz(0     ,				2							)  # add control z gate.
						quantum_circuit.cx(1     ,				2							)

						quantum_circuit.measure([2]     ,				[0]							)  # measure the qubit.

						# Simulate the circuit using qasm simulator
						snake_case							:  str			=     Aer.get_backend('''aer_simulator'''							)
						snake_case							:  List[str]			=     execute(A_     ,				A_     ,				shots=1000							)

						return job.result().get_counts(A_							)


if __name__ == "__main__":
						print(
						    "Total count for teleported state is: "
						    f'''{quantum_teleportation(np.pi/2, np.pi/2, np.pi/2)}'''
						)

