




"""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.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


lowercase__  		=		"""Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine"""







def   _snake_case    (       ):
				_lowerCamelCase  :    Optional[Any]					=					_ask_options(
				    'In which compute environment are you running?'							,					['This machine', 'AWS (Amazon SageMaker)']							,					_convert_compute_environment							,					)
				if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
								_lowerCamelCase  :    List[str]					=					get_sagemaker_input()
				else:
								_lowerCamelCase  :    str					=					get_cluster_input()
				return config







def   _snake_case    (       lowercase__=None	):
				if subparsers is not None:
								_lowerCamelCase  :    str					=					subparsers.add_parser('config'							,					description=lowercase__	)
				else:
								_lowerCamelCase  :    Tuple					=					argparse.ArgumentParser('Accelerate config command'							,					description=lowercase__	)

				parser.add_argument(
				    '--config_file'							,					default=lowercase__							,					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=lowercase__	)
				return parser







def   _snake_case    (       lowercase__	):
				_lowerCamelCase  :    Union[str, Any]					=					get_user_input()
				if args.config_file is not None:
								_lowerCamelCase  :    Dict					=					args.config_file
				else:
								if not os.path.isdir(lowercase__	):
												os.makedirs(lowercase__	)
								_lowerCamelCase  :    Optional[Any]					=					default_yaml_config_file

				if config_file.endswith('.json'	):
								config.to_json_file(lowercase__	)
				else:
								config.to_yaml_file(lowercase__	)
				print(f'''accelerate configuration saved at {config_file}'''	)







def   _snake_case    (       ):
				_lowerCamelCase  :    int					=					config_command_parser()
				_lowerCamelCase  :    List[Any]					=					parser.parse_args()
				config_command(lowercase__	)


if __name__ == "__main__":
			main()





"""simple docstring"""






import os
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 logging


lowercase__  		=		logging.get_logger(__name__)

lowercase__  		=		"""▁"""

lowercase__  		=		{"""vocab_file""": """sentencepiece.bpe.model"""}

lowercase__  		=		{
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

lowercase__  		=		{
    """xlm-roberta-base""": 512,
    """xlm-roberta-large""": 512,
    """xlm-roberta-large-finetuned-conll02-dutch""": 512,
    """xlm-roberta-large-finetuned-conll02-spanish""": 512,
    """xlm-roberta-large-finetuned-conll03-english""": 512,
    """xlm-roberta-large-finetuned-conll03-german""": 512,
}






class lowerCAmelCase__			(  lowercase		):






			'''simple docstring'''



			lowerCamelCase__   =    VOCAB_FILES_NAMES
			lowerCamelCase__   =    PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase__   =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase__   =    ["""input_ids""", """attention_mask"""]
			def __init__(						self						,   lowercase						,   lowercase="<s>"						,   lowercase="</s>"						,   lowercase="</s>"						,   lowercase="<s>"						,   lowercase="<unk>"						,   lowercase="<pad>"						,   lowercase="<mask>"						,   lowercase = None						,   **lowercase						,   ):
							# Mask token behave like a normal word, i.e. include the space before it
							_lowerCamelCase  :    str					=					AddedToken(lowercase						,   lstrip=lowercase						,   rstrip=lowercase						) if isinstance(lowercase						,   lowercase						) else mask_token

							_lowerCamelCase  :    Union[str, Any]					=					{} 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						,   sp_model_kwargs=self.sp_model_kwargs						,   **lowercase						,   )

							_lowerCamelCase  :    Any					=					spm.SentencePieceProcessor(**self.sp_model_kwargs						)
							self.sp_model.Load(str(lowercase						)						)
							_lowerCamelCase  :    str					=					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
							_lowerCamelCase  :    List[str]					=					{'<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
							_lowerCamelCase  :    List[Any]					=					1

							_lowerCamelCase  :    List[Any]					=					len(self.sp_model						) + self.fairseq_offset
							_lowerCamelCase  :    int					=					{v: k for k, v in self.fairseq_tokens_to_ids.items()}
			def __getstate__(						self						):
							_lowerCamelCase  :    Tuple					=					self.__dict__.copy()
							_lowerCamelCase  :    Tuple					=					None
							_lowerCamelCase  :    Union[str, Any]					=					self.sp_model.serialized_model_proto()
							return state
			def __setstate__(						self						,   lowercase						):
							_lowerCamelCase  :    List[Any]					=					d

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

							_lowerCamelCase  :    List[str]					=					spm.SentencePieceProcessor(**self.sp_model_kwargs						)
							self.sp_model.LoadFromSerializedProto(self.sp_model_proto						)
			def       A_					(						self						,   lowercase						,   lowercase = None						):

							if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							_lowerCamelCase  :    Any					=					[self.cls_token_id]
							_lowerCamelCase  :    List[Any]					=					[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep
			def       A_					(						self						,   lowercase						,   lowercase = None						,   lowercase = False						):

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

							if token_ids_a is None:
											return [1] + ([0] * len(lowercase						)) + [1]
							return [1] + ([0] * len(lowercase						)) + [1, 1] + ([0] * len(lowercase						)) + [1]
			def       A_					(						self						,   lowercase						,   lowercase = None						):
							_lowerCamelCase  :    Tuple					=					[self.sep_token_id]
							_lowerCamelCase  :    Optional[int]					=					[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]
			@property
			def       A_					(						self						):
							return len(self.sp_model						) + self.fairseq_offset + 1  # Add the <mask> token
			def       A_					(						self						):
							_lowerCamelCase  :    Dict					=					{self.convert_ids_to_tokens(lowercase						): i for i in range(self.vocab_size						)}
							vocab.update(self.added_tokens_encoder						)
							return vocab
			def       A_					(						self						,   lowercase						):
							return self.sp_model.encode(lowercase						,   out_type=lowercase						)
			def       A_					(						self						,   lowercase						):
							if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
							_lowerCamelCase  :    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       A_					(						self						,   lowercase						):
							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       A_					(						self						,   lowercase						):
							_lowerCamelCase  :    List[Any]					=					''.join(lowercase						).replace(lowercase						,   ' '						).strip()
							return out_string






			def       A_					(						self						,   lowercase						,   lowercase = None						):
							if not os.path.isdir(lowercase						):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
											return
							_lowerCamelCase  :    int					=					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:
															_lowerCamelCase  :    str					=					self.sp_model.serialized_model_proto()
															fi.write(lowercase						)

							return (out_vocab_file,)