



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


snake_case__					:     List[Any]    		=   logging.get_logger(__name__)

snake_case__					:     Any    		=   """▁"""

snake_case__					:     str    		=   {"""vocab_file""": """sentencepiece.bpe.model"""}

snake_case__					:     str    		=   {
    """vocab_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

snake_case__					:     Dict    		=   {
    """facebook/mbart-large-50-one-to-many-mmt""": 10_24,
}

# fmt: off
snake_case__					:     List[Any]    		=   ["""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""", """af_ZA""", """az_AZ""", """bn_IN""", """fa_IR""", """he_IL""", """hr_HR""", """id_ID""", """ka_GE""", """km_KH""", """mk_MK""", """ml_IN""", """mn_MN""", """mr_IN""", """pl_PL""", """ps_AF""", """pt_XX""", """sv_SE""", """sw_KE""", """ta_IN""", """te_IN""", """th_TH""", """tl_XX""", """uk_UA""", """ur_PK""", """xh_ZA""", """gl_ES""", """sl_SI"""]

class   _A   ( _lowercase	):


						'''simple docstring'''





						_snake_case			:     Union[str, Any]      							=      VOCAB_FILES_NAMES
						_snake_case			:     Tuple      							=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_snake_case			:     Optional[int]      							=      PRETRAINED_VOCAB_FILES_MAP
						_snake_case			:     List[str]      							=      ["""input_ids""", """attention_mask"""]

						_snake_case			:     List[Any]      							=      []
						_snake_case			:     Dict      							=      []



						def __init__(	self	:							List[str]							,      lowerCamelCase	:							Dict							,      lowerCamelCase	:							Dict=None							,      lowerCamelCase	:							List[str]=None							,      lowerCamelCase	:							List[Any]="</s>"							,      lowerCamelCase	:							Any="</s>"							,      lowerCamelCase	:							Optional[Any]="<s>"							,      lowerCamelCase	:							List[str]="<unk>"							,      lowerCamelCase	:							Optional[Any]="<pad>"							,      lowerCamelCase	:							Tuple="<mask>"							,      lowerCamelCase	:							Optional[Dict[str, Any]] = None							,      **lowerCamelCase	:							Union[str, Any]							,      ):






							'''simple docstring'''



							__lowercase		       =			AddedToken(__A							,      lstrip=__A							,      rstrip=__A	) if isinstance(__A							,      __A	) else mask_token

							__lowercase		       =			{} if sp_model_kwargs is None else sp_model_kwargs

							__lowercase		       =			kwargs.get("additional_special_tokens"							,      []	)
							kwargs["additional_special_tokens"] += [
							    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
							]

							super().__init__(
							    src_lang=__A							,      tgt_lang=__A							,      eos_token=__A							,      unk_token=__A							,      sep_token=__A							,      cls_token=__A							,      pad_token=__A							,      mask_token=__A							,      sp_model_kwargs=self.sp_model_kwargs							,      **__A							,      )

							__lowercase		       =			spm.SentencePieceProcessor(**self.sp_model_kwargs	)
							self.sp_model.Load(str(__A	)	)
							__lowercase		       =			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
							__lowercase		       =			{"<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
							__lowercase		       =			1

							__lowercase		       =			len(self.sp_model	)
							__lowercase		       =			{
							    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(__A	)
							}
							__lowercase		       =			{v: k for k, v in self.lang_code_to_id.items()}
							__lowercase		       =			len(self.sp_model	) + len(self.lang_code_to_id	) + self.fairseq_offset

							self.fairseq_tokens_to_ids.update(self.lang_code_to_id	)
							__lowercase		       =			{v: k for k, v in self.fairseq_tokens_to_ids.items()}

							__lowercase		       =			src_lang if src_lang is not None else "en_XX"
							__lowercase		       =			self.lang_code_to_id[self._src_lang]
							__lowercase		       =			tgt_lang
							self.set_src_lang_special_tokens(self._src_lang	)



						@property
						def     _snake_case	(	self	:							str	):






							'''simple docstring'''



							return len(self.sp_model	) + len(self.lang_code_to_id	) + self.fairseq_offset + 1  # Plus 1 for the mask token



						@property
						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							return self._src_lang



						@src_lang.setter
						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			new_src_lang
							self.set_src_lang_special_tokens(self._src_lang	)



						def __getstate__(	self	:							str	):






							'''simple docstring'''



							__lowercase		       =			self.__dict__.copy()
							__lowercase		       =			None
							return state



						def __setstate__(	self	:							int							,      lowerCamelCase	:							Dict	):






							'''simple docstring'''



							__lowercase		       =			d

							# for backward compatibility
							if not hasattr(self							,      "sp_model_kwargs"	):
								__lowercase		       =			{}

							__lowercase		       =			spm.SentencePieceProcessor(**self.sp_model_kwargs	)
							self.sp_model.Load(self.vocab_file	)



						def     _snake_case	(	self	:							List[Any]	):






							'''simple docstring'''



							__lowercase		       =			{self.convert_ids_to_tokens(__A	): i for i in range(self.vocab_size	)}
							vocab.update(self.added_tokens_encoder	)
							return vocab



						def     _snake_case	(	self	:							Tuple							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							return self.sp_model.encode(__A							,      out_type=__A	)



						def     _snake_case	(	self	:							List[str]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							if token in self.fairseq_tokens_to_ids:
								return self.fairseq_tokens_to_ids[token]
							__lowercase		       =			self.sp_model.PieceToId(__A	)

							# 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     _snake_case	(	self	:							Tuple							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							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     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			[]
							__lowercase		       =			""
							__lowercase		       =			False
							for token in tokens:
								# make sure that special tokens are not decoded using sentencepiece model
								if token in self.all_special_tokens:
									if not prev_is_special:
										out_string += " "
									out_string += self.sp_model.decode(__A	) + token
									__lowercase		       =			True
									__lowercase		       =			[]
								else:
									current_sub_tokens.append(__A	)
									__lowercase		       =			False
							out_string += self.sp_model.decode(__A	)
							return out_string.strip()



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							str							,      lowerCamelCase	:							Optional[str] = None	):






							'''simple docstring'''



							if not os.path.isdir(__A	):
								logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
								return
							__lowercase		       =			os.path.join(
							    __A							,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)

							if os.path.abspath(self.vocab_file	) != os.path.abspath(__A	) and os.path.isfile(self.vocab_file	):
								copyfile(self.vocab_file							,      __A	)
							elif not os.path.isfile(self.vocab_file	):
								with open(__A							,      "wb"	) as fi:
									__lowercase		       =			self.sp_model.serialized_model_proto()
									fi.write(__A	)

							return (out_vocab_file,)



						def     _snake_case	(	self	:							Optional[int]							,      lowerCamelCase	:							List[int]							,      lowerCamelCase	:							Optional[List[int]] = None							,      lowerCamelCase	:							bool = False	):






							'''simple docstring'''



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

							__lowercase		       =			[1] * len(self.prefix_tokens	)
							__lowercase		       =			[1] * len(self.suffix_tokens	)
							if token_ids_a is None:
								return prefix_ones + ([0] * len(__A	)) + suffix_ones
							return prefix_ones + ([0] * len(__A	)) + ([0] * len(__A	)) + suffix_ones



						def     _snake_case	(	self	:							Tuple							,      lowerCamelCase	:							List[int]							,      lowerCamelCase	:							Optional[List[int]] = None	):






							'''simple docstring'''



							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     _snake_case	(	self	:							Tuple							,      lowerCamelCase	:							List[str]							,      lowerCamelCase	:							str							,      lowerCamelCase	:							Optional[str]							,      lowerCamelCase	:							Optional[str]							,      **lowerCamelCase	:							Any	):






							'''simple docstring'''



							if src_lang is None or tgt_lang is None:
								raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"	)
							__lowercase		       =			src_lang
							__lowercase		       =			self(__A							,      add_special_tokens=__A							,      return_tensors=__A							,      **__A	)
							__lowercase		       =			self.convert_tokens_to_ids(__A	)
							__lowercase		       =			tgt_lang_id
							return inputs



						def     _snake_case	(	self	:							Optional[int]							,      lowerCamelCase	:							List[str]							,      lowerCamelCase	:							str = "en_XX"							,      lowerCamelCase	:							Optional[List[str]] = None							,      lowerCamelCase	:							str = "ro_RO"							,      **lowerCamelCase	:							Optional[Any]							,      ):






							'''simple docstring'''



							__lowercase		       =			src_lang
							__lowercase		       =			tgt_lang
							return super().prepare_seqaseq_batch(__A							,      __A							,      **__A	)



						def     _snake_case	(	self	:							List[str]	):






							'''simple docstring'''



							return self.set_src_lang_special_tokens(self.src_lang	)



						def     _snake_case	(	self	:							Tuple	):






							'''simple docstring'''



							return self.set_tgt_lang_special_tokens(self.tgt_lang	)



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			self.lang_code_to_id[src_lang]
							__lowercase		       =			[self.cur_lang_code_id]
							__lowercase		       =			[self.eos_token_id]



						def     _snake_case	(	self	:							List[str]							,      lowerCamelCase	:							str	):






							'''simple docstring'''



							__lowercase		       =			self.lang_code_to_id[tgt_lang]
							__lowercase		       =			[self.cur_lang_code_id]
							__lowercase		       =			[self.eos_token_id]








from __future__ import annotations

from typing import Any

class   _A   :


						'''simple docstring'''





						def __init__(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							__lowercase		       =			num_of_nodes
							__lowercase		       =			[]
							__lowercase		       =			{}



						def     _snake_case	(	self	:							Dict							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							self.m_edges.append([u_node, v_node, weight]	)



						def     _snake_case	(	self	:							List[Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] == u_node:
								return u_node
							return self.find_component(self.m_component[u_node]	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if self.m_component[u_node] != u_node:
								for k in self.m_component:
									__lowercase		       =			self.find_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Union[str, Any]							,      lowerCamelCase	:							list[int]							,      lowerCamelCase	:							int							,      lowerCamelCase	:							int	):






							'''simple docstring'''



							if component_size[u_node] <= component_size[v_node]:
								__lowercase		       =			v_node
								component_size[v_node] += component_size[u_node]
								self.set_component(lowerCamelCase	)

							elif component_size[u_node] >= component_size[v_node]:
								__lowercase		       =			self.find_component(lowerCamelCase	)
								component_size[u_node] += component_size[v_node]
								self.set_component(lowerCamelCase	)



						def     _snake_case	(	self	:							Any	):






							'''simple docstring'''



							__lowercase		       =			[]
							__lowercase		       =			0

							__lowercase		       =			[-1] * self.m_num_of_nodes

							# A list of components (initialized to all of the nodes)
							for node in range(self.m_num_of_nodes	):
								self.m_component.update({node: node}	)
								component_size.append(1	)

							__lowercase		       =			self.m_num_of_nodes

							while num_of_components > 1:
								for edge in self.m_edges:
									__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

									__lowercase		       =			self.m_component[u]
									__lowercase		       =			self.m_component[v]

									if u_component != v_component:

										for component in (u_component, v_component):
											if (
											    minimum_weight_edge[component] == -1
											    or minimum_weight_edge[component][2] > w
											):
												__lowercase		       =			[u, v, w]

								for edge in minimum_weight_edge:
									if isinstance(lowerCamelCase							,      lowerCamelCase	):
										__lowercase       ,    __lowercase       ,    __lowercase		       =			edge

										__lowercase		       =			self.m_component[u]
										__lowercase		       =			self.m_component[v]

										if u_component != v_component:
											mst_weight += w
											self.union(lowerCamelCase							,      lowerCamelCase							,      lowerCamelCase	)
											print(f"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""	)
											num_of_components -= 1

								__lowercase		       =			[-1] * self.m_num_of_nodes
							print(f"""The total weight of the minimal spanning tree is: {mst_weight}"""	)



def    snake_case_				(    ):
	pass


if __name__ == "__main__":
	import doctest

	doctest.testmod()



