


"""simple docstring"""



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

import sentencepiece as spm

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


A__	:    int			 = logging.get_logger(__name__)

A__	:    List[Any]			 = {'vocab_file': 'spiece.model'}

A__	:    List[str]			 = {
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    }
}

A__	:    Dict			 = {
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
A__	:    Optional[int]			 = 0
A__	:    Tuple			 = 1
A__	:    Any			 = 2
A__	:    Union[str, Any]			 = 3
A__	:    Tuple			 = 4







class        lowercase__      (							snake_case__       ):
			_UpperCAmelCase		:Optional[Any]             =			VOCAB_FILES_NAMES
			_UpperCAmelCase		:Tuple             =			PRETRAINED_VOCAB_FILES_MAP
			_UpperCAmelCase		:Union[str, Any]             =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCAmelCase		:List[str]             =			'''left'''


			def __init__(				self					:  List[Any]       ,	snake_case__					:  List[Any]       ,	snake_case__					:  Dict=False       ,	snake_case__					:  Tuple=True       ,	snake_case__					:  List[Any]=False       ,	snake_case__					:  Optional[Any]="<s>"       ,	snake_case__					:  Dict="</s>"       ,	snake_case__					:  int="<unk>"       ,	snake_case__					:  List[str]="<sep>"       ,	snake_case__					:  Union[str, Any]="<pad>"       ,	snake_case__					:  Tuple="<cls>"       ,	snake_case__					:  Optional[int]="<mask>"       ,	snake_case__					:  Optional[int]=["<eop>", "<eod>"]       ,	snake_case__					:  Optional[Dict[str, Any]] = None       ,	**snake_case__					:  List[Any]       ,	):
										lowerCamelCase_	:							int									=AddedToken(lowerCAmelCase__       ,	lstrip=lowerCAmelCase__       ,	rstrip=lowerCAmelCase__ ) if isinstance(lowerCAmelCase__       ,	lowerCAmelCase__ ) else mask_token

										lowerCamelCase_	:							Dict									={} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    do_lower_case=lowerCAmelCase__       ,	remove_space=lowerCAmelCase__       ,	keep_accents=lowerCAmelCase__       ,	bos_token=lowerCAmelCase__       ,	eos_token=lowerCAmelCase__       ,	unk_token=lowerCAmelCase__       ,	sep_token=lowerCAmelCase__       ,	pad_token=lowerCAmelCase__       ,	cls_token=lowerCAmelCase__       ,	mask_token=lowerCAmelCase__       ,	additional_special_tokens=lowerCAmelCase__       ,	sp_model_kwargs=self.sp_model_kwargs       ,	**lowerCAmelCase__       ,	)

										lowerCamelCase_	:							Union[str, Any]									=3

										lowerCamelCase_	:							Union[str, Any]									=do_lower_case
										lowerCamelCase_	:							List[str]									=remove_space
										lowerCamelCase_	:							Optional[int]									=keep_accents
										lowerCamelCase_	:							Union[str, Any]									=vocab_file

										lowerCamelCase_	:							Dict									=spm.SentencePieceProcessor(**self.sp_model_kwargs )
										self.sp_model.Load(lowerCAmelCase__ )


			@property
			def      UpperCAmelCase__						(				self					:  Any ):
										return len(self.sp_model )


			def      UpperCAmelCase__						(				self					:  Tuple ):
										lowerCamelCase_	:							int									={self.convert_ids_to_tokens(lowerCAmelCase__ ): i for i in range(self.vocab_size )}
										vocab.update(self.added_tokens_encoder )
										return vocab


			def __getstate__(				self					:  Union[str, Any] ):
										lowerCamelCase_	:							Tuple									=self.__dict__.copy()
										lowerCamelCase_	:							Optional[Any]									=None
										return state


			def __setstate__(				self					:  str       ,	snake_case__					:  Dict ):
										lowerCamelCase_	:							Tuple									=d

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

										lowerCamelCase_	:							str									=spm.SentencePieceProcessor(**self.sp_model_kwargs )
										self.sp_model.Load(self.vocab_file )


			def      UpperCAmelCase__						(				self					:  Optional[Any]       ,	snake_case__					:  int ):




										if self.remove_space:
																	lowerCamelCase_	:							Optional[Any]									=" ".join(inputs.strip().split() )
										else:
																	lowerCamelCase_	:							Optional[int]									=inputs
										lowerCamelCase_	:							Optional[Any]									=outputs.replace("``"       ,	"\"" ).replace("''"       ,	"\"" )

										if not self.keep_accents:
																	lowerCamelCase_	:							Dict									=unicodedata.normalize("NFKD"       ,	lowerCAmelCase__ )
																	lowerCamelCase_	:							str									="".join([c for c in outputs if not unicodedata.combining(lowerCAmelCase__ )] )
										if self.do_lower_case:
																	lowerCamelCase_	:							Optional[int]									=outputs.lower()

										return outputs


			def      UpperCAmelCase__						(				self					:  List[str]       ,	snake_case__					:  str ):
										lowerCamelCase_	:							List[Any]									=self.preprocess_text(lowerCAmelCase__ )
										lowerCamelCase_	:							int									=self.sp_model.encode(lowerCAmelCase__       ,	out_type=lowerCAmelCase__ )
										lowerCamelCase_	:							Optional[int]									=[]
										for piece in pieces:
																	if len(lowerCAmelCase__ ) > 1 and piece[-1] == str("," ) and piece[-2].isdigit():
																								lowerCamelCase_	:							int									=self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCAmelCase__       ,	"" ) )
																								if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																															if len(cur_pieces[0] ) == 1:
																																						lowerCamelCase_	:							Dict									=cur_pieces[1:]
																															else:
																																						lowerCamelCase_	:							Dict									=cur_pieces[0][1:]
																								cur_pieces.append(piece[-1] )
																								new_pieces.extend(lowerCAmelCase__ )
																	else:
																								new_pieces.append(lowerCAmelCase__ )

										return new_pieces


			def      UpperCAmelCase__						(				self					:  Tuple       ,	snake_case__					:  Dict ):
										return self.sp_model.PieceToId(lowerCAmelCase__ )


			def      UpperCAmelCase__						(				self					:  Optional[Any]       ,	snake_case__					:  str ):
										return self.sp_model.IdToPiece(lowerCAmelCase__ )


			def      UpperCAmelCase__						(				self					:  int       ,	snake_case__					:  List[Any] ):
										lowerCamelCase_	:							Optional[int]									="".join(lowerCAmelCase__ ).replace(lowerCAmelCase__       ,	" " ).strip()
										return out_string


			def      UpperCAmelCase__						(				self					:  List[Any]       ,	snake_case__					:  List[int]       ,	snake_case__					:  bool = False       ,	snake_case__					:  bool = None       ,	snake_case__					:  bool = True       ,	**snake_case__					:  Optional[int]       ,	):
										lowerCamelCase_	:							Dict									=kwargs.pop("use_source_tokenizer"       ,	lowerCAmelCase__ )

										lowerCamelCase_	:							Tuple									=self.convert_ids_to_tokens(lowerCAmelCase__       ,	skip_special_tokens=lowerCAmelCase__ )

										# To avoid mixing byte-level and unicode for byte-level BPT
										# we need to build string separately for added tokens and byte-level tokens
										# cf. https://github.com/huggingface/transformers/issues/1133
										lowerCamelCase_	:							Optional[Any]									=[]
										lowerCamelCase_	:							List[str]									=[]
										for token in filtered_tokens:
																	if skip_special_tokens and token in self.all_special_ids:
																								continue
																	if token in self.added_tokens_encoder:
																								if current_sub_text:
																															sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase__ ) )
																															lowerCamelCase_	:							List[str]									=[]
																								sub_texts.append(lowerCAmelCase__ )
																	else:
																								current_sub_text.append(lowerCAmelCase__ )
										if current_sub_text:
																	sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase__ ) )

										# Mimic the behavior of the Rust tokenizer:
										# By default, there are no spaces between special tokens
										lowerCamelCase_	:							Optional[int]									="".join(lowerCAmelCase__ )

										lowerCamelCase_	:							Any									=(
										    clean_up_tokenization_spaces
										    if clean_up_tokenization_spaces is not None
										    else self.clean_up_tokenization_spaces
										)
										if clean_up_tokenization_spaces:
																	lowerCamelCase_	:							Union[str, Any]									=self.clean_up_tokenization(lowerCAmelCase__ )
																	return clean_text
										else:
																	return text


			def      UpperCAmelCase__						(				self					:  str       ,	snake_case__					:  List[int]       ,	snake_case__					:  Optional[List[int]] = None ):
										lowerCamelCase_	:							str									=[self.sep_token_id]
										lowerCamelCase_	:							Optional[Any]									=[self.cls_token_id]
										if token_ids_a is None:
																	return token_ids_a + sep + cls
										return token_ids_a + sep + token_ids_a + sep + cls


			def      UpperCAmelCase__						(				self					:  List[Any]       ,	snake_case__					:  List[int]       ,	snake_case__					:  Optional[List[int]] = None       ,	snake_case__					:  bool = False ):




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

										if token_ids_a is not None:
																	return ([0] * len(lowerCAmelCase__ )) + [1] + ([0] * len(lowerCAmelCase__ )) + [1, 1]
										return ([0] * len(lowerCAmelCase__ )) + [1, 1]


			def      UpperCAmelCase__						(				self					:  Optional[Any]       ,	snake_case__					:  List[int]       ,	snake_case__					:  Optional[List[int]] = None ):
										lowerCamelCase_	:							Optional[Any]									=[self.sep_token_id]
										lowerCamelCase_	:							Tuple									=[2]

										if token_ids_a is None:
																	return len(token_ids_a + sep ) * [0] + cls_segment_id
										return len(token_ids_a + sep ) * [0] + len(token_ids_a + sep ) * [1] + cls_segment_id


			def      UpperCAmelCase__						(				self					:  Tuple       ,	snake_case__					:  str       ,	snake_case__					:  Optional[str] = None ):




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

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

										return (out_vocab_file,)











"""simple docstring"""



# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async

def 			_snake_case    (					lowerCamelCase__     :   int=None  )    ->     Union[str, Any]:
							if subparsers is not None:
														lowerCamelCase_	:							List[Any]									=subparsers.add_parser("test"  )
							else:
														lowerCamelCase_	:							List[str]									=argparse.ArgumentParser("Accelerate test command"  )

							parser.add_argument(
							    "--config_file"    ,						default=lowerCamelCase__    ,						help=(
							        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
							        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
							        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
							        "with 'huggingface'."
							    )    ,						)

							if subparsers is not None:
														parser.set_defaults(func=lowerCamelCase__  )
							return parser

def 			_snake_case    (					lowerCamelCase__     :   List[Any]  )    ->     Any:
							lowerCamelCase_	:							Optional[Any]									=os.path.sep.join(__file__.split(os.path.sep  )[:-2] + ["test_utils", "scripts", "test_script.py"]  )

							if args.config_file is None:
														lowerCamelCase_	:							List[Any]									=script_name
							else:
														lowerCamelCase_	:							Union[str, Any]									=F"""--config_file={args.config_file} {script_name}"""

							lowerCamelCase_	:							List[str]									=["accelerate-launch"] + test_args.split()
							lowerCamelCase_	:							Tuple									=execute_subprocess_async(lowerCamelCase__    ,						env=os.environ.copy()  )
							if result.returncode == 0:
														print("Test is a success! You are ready for your distributed training!"  )

def 			_snake_case    (					)    ->     Tuple:
							lowerCamelCase_	:							Any									=test_command_parser()
							lowerCamelCase_	:							List[Any]									=parser.parse_args()
							test_command(lowerCamelCase__  )


if __name__ == "__main__":
						main()



