import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


__lowercase							 =					logging.get_logger(__name__)

__lowercase							 =					'''▁'''

__lowercase							 =					{'''vocab_file''': '''sentencepiece.bpe.model'''}

__lowercase							 =					{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    }
}

__lowercase							 =					{
    '''facebook/mbart-large-en-ro''': 1024,
    '''facebook/mbart-large-cc25''': 1024,
}

# fmt: off
__lowercase							 =					['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']


class 	lowerCamelCase_     (   UpperCAmelCase_ ):






    '''simple docstring'''






    a__	:						int						=      VOCAB_FILES_NAMES
    a__	:						List[str]						=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a__	:						List[str]						=      PRETRAINED_VOCAB_FILES_MAP
    a__	:						Dict						=      ["""input_ids""", """attention_mask"""]

    a__	:						List[int]						=      []
    a__	:						List[int]						=      []







    def __init__(	self , __lowercase , __lowercase="<s>" , __lowercase="</s>" , __lowercase="</s>" , __lowercase="<s>" , __lowercase="<unk>" , __lowercase="<pad>" , __lowercase="<mask>" , __lowercase=None , __lowercase=None , __lowercase=None , __lowercase = None , __lowercase=None , **__lowercase , )       ->	List[Any]:
        # Mask token behave like a normal word, i.e. include the space before it
        __UpperCamelCase     :Optional[int]			  =		AddedToken(__lowercase , lstrip=__lowercase , rstrip=__lowercase) if isinstance(__lowercase , __lowercase) else mask_token

        __UpperCamelCase     :Tuple			  =		{} if sp_model_kwargs is None else sp_model_kwargs

        super().__init__(
            bos_token=__lowercase , eos_token=__lowercase , unk_token=__lowercase , sep_token=__lowercase , cls_token=__lowercase , pad_token=__lowercase , mask_token=__lowercase , tokenizer_file=__lowercase , src_lang=__lowercase , tgt_lang=__lowercase , additional_special_tokens=__lowercase , sp_model_kwargs=self.sp_model_kwargs , **__lowercase , )

        __UpperCamelCase     :List[Any]			  =		spm.SentencePieceProcessor(**self.sp_model_kwargs)
        self.sp_model.Load(str(__lowercase))
        __UpperCamelCase     :Dict			  =		vocab_file

        # Original fairseq vocab and spm vocab must be "aligned":
        # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
        # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
        # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
        # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

        # Mimic fairseq token-to-id alignment for the first 4 token
        __UpperCamelCase     :List[Any]			  =		{'''<s>''': 0, '''<pad>''': 1, '''</s>''': 2, '''<unk>''': 3}

        # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
        __UpperCamelCase     :Tuple			  =		1

        __UpperCamelCase     :List[Any]			  =		len(self.sp_model)
        __UpperCamelCase     :Optional[int]			  =		{
            code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__lowercase)
        }
        __UpperCamelCase     :Union[str, Any]			  =		{v: k for k, v in self.lang_code_to_id.items()}
        __UpperCamelCase     :int			  =		len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

        self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
        __UpperCamelCase     :Optional[int]			  =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}
        __UpperCamelCase     :Optional[int]			  =		list(self.lang_code_to_id.keys())

        if additional_special_tokens is not None:
            # Only add those special tokens if they are not already there.
            self._additional_special_tokens.extend(
                [t for t in additional_special_tokens if t not in self._additional_special_tokens])

        __UpperCamelCase     :List[str]			  =		src_lang if src_lang is not None else '''en_XX'''
        __UpperCamelCase     :Dict			  =		self.lang_code_to_id[self._src_lang]
        __UpperCamelCase     :List[Any]			  =		tgt_lang
        self.set_src_lang_special_tokens(self._src_lang)







    def __getstate__(	self)       ->	Tuple:
        __UpperCamelCase     :Dict			  =		self.__dict__.copy()
        __UpperCamelCase     :Union[str, Any]			  =		None
        __UpperCamelCase     :Tuple			  =		self.sp_model.serialized_model_proto()
        return state







    def __setstate__(	self , __lowercase)       ->	Any:
        __UpperCamelCase     :Optional[Any]			  =		d

        # for backward compatibility
        if not hasattr(self , '''sp_model_kwargs'''):
            __UpperCamelCase     :str			  =		{}

        __UpperCamelCase     :Optional[Any]			  =		spm.SentencePieceProcessor(**self.sp_model_kwargs)
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto)







    @property
    def 			UpperCamelCase__   (	self)       ->	Optional[Any]:
        return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token







    @property
    def 			UpperCamelCase__   (	self)       ->	str:
        return self._src_lang







    @src_lang.setter
    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        __UpperCamelCase     :List[str]			  =		new_src_lang
        self.set_src_lang_special_tokens(self._src_lang)







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase = None , __lowercase = False)       ->	List[int]:

        if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=__lowercase , token_ids_a=__lowercase , already_has_special_tokens=__lowercase)

        __UpperCamelCase     :Optional[int]			  =		[1] * len(self.prefix_tokens)
        __UpperCamelCase     :List[Any]			  =		[1] * len(self.suffix_tokens)
        if token_ids_a is None:
            return prefix_ones + ([0] * len(__lowercase)) + suffix_ones
        return prefix_ones + ([0] * len(__lowercase)) + ([0] * len(__lowercase)) + suffix_ones







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase = None)       ->	List[int]:
        if token_ids_a is None:
            return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase = None)       ->	List[int]:
        __UpperCamelCase     :Dict			  =		[self.sep_token_id]
        __UpperCamelCase     :Optional[Any]			  =		[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]







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase , __lowercase , __lowercase , **__lowercase)       ->	Optional[Any]:
        if src_lang is None or tgt_lang is None:
            raise ValueError('''Translation requires a `src_lang` and a `tgt_lang` for this model''')
        __UpperCamelCase     :List[Any]			  =		src_lang
        __UpperCamelCase     :Dict			  =		self(__lowercase , add_special_tokens=__lowercase , return_tensors=__lowercase , **__lowercase)
        __UpperCamelCase     :str			  =		self.convert_tokens_to_ids(__lowercase)
        __UpperCamelCase     :List[Any]			  =		tgt_lang_id
        return inputs







    def 			UpperCamelCase__   (	self)       ->	Tuple:
        __UpperCamelCase     :Optional[int]			  =		{self.convert_ids_to_tokens(__lowercase): i for i in range(self.vocab_size)}
        vocab.update(self.added_tokens_encoder)
        return vocab







    def 			UpperCamelCase__   (	self , __lowercase)       ->	List[str]:
        return self.sp_model.encode(__lowercase , out_type=__lowercase)







    def 			UpperCamelCase__   (	self , __lowercase)       ->	List[str]:
        if token in self.fairseq_tokens_to_ids:
            return self.fairseq_tokens_to_ids[token]
        __UpperCamelCase     :Union[str, Any]			  =		self.sp_model.PieceToId(__lowercase)

        # Need to return unknown token if the SP model returned 0
        return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







    def 			UpperCamelCase__   (	self , __lowercase)       ->	Any:
        if index in self.fairseq_ids_to_tokens:
            return self.fairseq_ids_to_tokens[index]
        return self.sp_model.IdToPiece(index - self.fairseq_offset)







    def 			UpperCamelCase__   (	self , __lowercase)       ->	List[str]:
        __UpperCamelCase     :List[Any]			  =		''''''.join(__lowercase).replace(__lowercase , ''' ''').strip()
        return out_string







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase = None)       ->	Tuple[str]:
        if not os.path.isdir(__lowercase):
            logger.error(f"""Vocabulary path ({save_directory}) should be a directory""")
            return
        __UpperCamelCase     :Any			  =		os.path.join(
            __lowercase , (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

        if os.path.abspath(self.vocab_file) != os.path.abspath(__lowercase) and os.path.isfile(self.vocab_file):
            copyfile(self.vocab_file , __lowercase)
        elif not os.path.isfile(self.vocab_file):
            with open(__lowercase , '''wb''') as fi:
                __UpperCamelCase     :List[str]			  =		self.sp_model.serialized_model_proto()
                fi.write(__lowercase)

        return (out_vocab_file,)







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase = "en_XX" , __lowercase = None , __lowercase = "ro_RO" , **__lowercase , )       ->	BatchEncoding:
        __UpperCamelCase     :Optional[int]			  =		src_lang
        __UpperCamelCase     :str			  =		tgt_lang
        return super().prepare_seqaseq_batch(__lowercase , __lowercase , **__lowercase)







    def 			UpperCamelCase__   (	self)       ->	List[str]:
        return self.set_src_lang_special_tokens(self.src_lang)







    def 			UpperCamelCase__   (	self)       ->	Tuple:
        return self.set_tgt_lang_special_tokens(self.tgt_lang)







    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        __UpperCamelCase     :Optional[Any]			  =		self.lang_code_to_id[src_lang]
        __UpperCamelCase     :Optional[Any]			  =		[]
        __UpperCamelCase     :Tuple			  =		[self.eos_token_id, self.cur_lang_code]







    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        __UpperCamelCase     :str			  =		self.lang_code_to_id[lang]
        __UpperCamelCase     :Any			  =		[]
        __UpperCamelCase     :Dict			  =		[self.eos_token_id, self.cur_lang_code]






import math

import qiskit



def lowerCamelCase  (   SCREAMING_SNAKE_CASE = 1  ,			SCREAMING_SNAKE_CASE = 1  ,			SCREAMING_SNAKE_CASE = 1	):
    '''simple docstring'''







    if (
        isinstance(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)
        or isinstance(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)
        or isinstance(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)
    ):
        raise TypeError('''inputs must be integers.'''	)

    if (input_a < 0) or (input_a < 0) or (carry_in < 0):
        raise ValueError('''inputs must be positive.'''	)

    if (
        (math.floor(SCREAMING_SNAKE_CASE	) != input_a)
        or (math.floor(SCREAMING_SNAKE_CASE	) != input_a)
        or (math.floor(SCREAMING_SNAKE_CASE	) != carry_in)
    ):
        raise ValueError('''inputs must be exact integers.'''	)

    if (input_a > 2) or (input_a > 2) or (carry_in > 2):
        raise ValueError('''inputs must be less or equal to 2.'''	)

    # build registers
    __UpperCamelCase     :List[str]			  =		qiskit.QuantumRegister(4  ,			'''qr'''	)
    __UpperCamelCase     :str			  =		qiskit.ClassicalRegister(2  ,			'''cr'''	)
    # list the entries
    __UpperCamelCase     :Tuple			  =		[input_a, input_a, carry_in]

    __UpperCamelCase     :Optional[int]			  =		qiskit.QuantumCircuit(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)

    for i in range(0  ,			3	):
        if entry[i] == 2:
            quantum_circuit.h(SCREAMING_SNAKE_CASE	)  # for hadamard entries
        elif entry[i] == 1:
            quantum_circuit.x(SCREAMING_SNAKE_CASE	)  # for 1 entries
        elif entry[i] == 0:
            quantum_circuit.i(SCREAMING_SNAKE_CASE	)  # for 0 entries

    # build the circuit
    quantum_circuit.ccx(0  ,			1  ,			3	)  # ccx = toffoli gate
    quantum_circuit.cx(0  ,			1	)
    quantum_circuit.ccx(1  ,			2  ,			3	)
    quantum_circuit.cx(1  ,			2	)
    quantum_circuit.cx(0  ,			1	)

    quantum_circuit.measure([2, 3]  ,			SCREAMING_SNAKE_CASE	)  # measure the last two qbits

    __UpperCamelCase     :Optional[Any]			  =		qiskit.Aer.get_backend('''aer_simulator'''	)
    __UpperCamelCase     :Tuple			  =		qiskit.execute(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			shots=1_000	)

    return job.result().get_counts(SCREAMING_SNAKE_CASE	)


if __name__ == "__main__":
    print(F'Total sum count for state is: {quantum_full_adder(1, 1, 1)}')





