



import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer


if TYPE_CHECKING:
						from transformers.pipelines.conversational import Conversation


A__  :  str								=					logging.get_logger(__name__)

A__  :  Dict								=					{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

A__  :  Tuple								=					{
    '''vocab_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/vocab.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/vocab.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/vocab.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/vocab.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/merges.txt''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/merges.txt''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/merges.txt''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/merges.txt''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''gpt2''': '''https://huggingface.co/gpt2/resolve/main/tokenizer.json''',
        '''gpt2-medium''': '''https://huggingface.co/gpt2-medium/resolve/main/tokenizer.json''',
        '''gpt2-large''': '''https://huggingface.co/gpt2-large/resolve/main/tokenizer.json''',
        '''gpt2-xl''': '''https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json''',
        '''distilgpt2''': '''https://huggingface.co/distilgpt2/resolve/main/tokenizer.json''',
    },
}

A__  :  Optional[int]								=					{
    '''gpt2''': 1024,
    '''gpt2-medium''': 1024,
    '''gpt2-large''': 1024,
    '''gpt2-xl''': 1024,
    '''distilgpt2''': 1024,
}



class 				__snake_case						(     UpperCamelCase_						):
							_a			      = VOCAB_FILES_NAMES
							_a			      = PRETRAINED_VOCAB_FILES_MAP
							_a			      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_a			      = ['''input_ids''', '''attention_mask''']
							_a			      = GPTaTokenizer




							def __init__(       self     :       Tuple				,				A_     :       Any=None				,				A_     :       Any=None				,				A_     :       Any=None				,				A_     :       List[Any]="<|endoftext|>"				,				A_     :       Optional[Any]="<|endoftext|>"				,				A_     :       Dict="<|endoftext|>"				,				A_     :       Optional[Any]=False				,				**A_     :       int				,				):
									super().__init__(
									    A_				,				A_				,				tokenizer_file=A_				,				unk_token=A_				,				bos_token=A_				,				eos_token=A_				,				add_prefix_space=A_				,				**A_				,				)

									lowerCAmelCase_			:     str									= kwargs.pop('''add_bos_token'''				,				A_)

									lowerCAmelCase_			:     Optional[int]									= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
									if pre_tok_state.get('''add_prefix_space'''				,				A_) != add_prefix_space:
											lowerCAmelCase_			:     Any									= getattr(A_				,				pre_tok_state.pop('''type'''))
											lowerCAmelCase_			:     List[str]									= add_prefix_space
											lowerCAmelCase_			:     int									= pre_tok_class(**A_)

									lowerCAmelCase_			:     Union[str, Any]									= add_prefix_space




							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				*A_     :       Optional[Any]				,				**A_     :       Union[str, Any]):
									lowerCAmelCase_			:     List[str]									= kwargs.get('''is_split_into_words'''				,				A_)
									assert self.add_prefix_space or not is_split_into_words, (
									    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
									    "to use it with pretokenized inputs."
									)

									return super()._batch_encode_plus(*A_				,				**A_)




							def    UpperCAmelCase__			(       self     :       Dict				,				*A_     :       List[str]				,				**A_     :       Union[str, Any]):
									lowerCAmelCase_			:     Union[str, Any]									= kwargs.get('''is_split_into_words'''				,				A_)

									assert self.add_prefix_space or not is_split_into_words, (
									    F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
									    "to use it with pretokenized inputs."
									)

									return super()._encode_plus(*A_				,				**A_)




							def    UpperCAmelCase__			(       self     :       Optional[int]				,				A_     :       str				,				A_     :       Optional[str] = None):
									lowerCAmelCase_			:     List[Any]									= self._tokenizer.model.save(A_				,				name=A_)
									return tuple(A_)







							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       "Conversation"):
									lowerCAmelCase_			:     Optional[Any]									= []
									for is_user, text in conversation.iter_texts():
											input_ids.extend(self.encode(A_				,				add_special_tokens=A_) + [self.eos_token_id])

									if len(A_) > self.model_max_length:
											lowerCAmelCase_			:     Optional[int]									= input_ids[-self.model_max_length :]
									return input_ids











# 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.

from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser


def 						lowerCamelCase__    (		):







	'''simple docstring'''





	snake_case_		    =     ArgumentParser("Accelerate CLI tool"     ,	usage="accelerate <command> [<args>]"     ,	allow_abbrev=_A							)
	snake_case_		    =     parser.add_subparsers(help="accelerate command helpers"							)

	# Register commands
	get_config_parser(subparsers=_A							)
	env_command_parser(subparsers=_A							)
	launch_command_parser(subparsers=_A							)
	tpu_command_parser(subparsers=_A							)
	test_command_parser(subparsers=_A							)

	# Let's go
	snake_case_		    =     parser.parse_args()

	if not hasattr(_A     ,	"func"							):
		parser.print_help()
		exit(1							)

	# Run
	args.func(_A							)


if __name__ == "__main__":
		main()
