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

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
	from transformers.pipelines.conversational import Conversation


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

lowercase__			:				Tuple		=	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__			:				Union[str, Any]		=	{
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

lowercase__			:				str		=	{
    '''gpt-neox-20b''': 2_0_4_8,
}




class    lowercase_  (  UpperCamelCase_						):



	"""simple docstring"""





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


	def __init__(							self		,			__SCREAMING_SNAKE_CASE=None		,			__SCREAMING_SNAKE_CASE=None		,			__SCREAMING_SNAKE_CASE=None		,			__SCREAMING_SNAKE_CASE="<|endoftext|>"		,			__SCREAMING_SNAKE_CASE="<|endoftext|>"		,			__SCREAMING_SNAKE_CASE="<|endoftext|>"		,			__SCREAMING_SNAKE_CASE=False		,			**__SCREAMING_SNAKE_CASE		,			)						->Union[str, Any]:
								super().__init__(
								    UpperCAmelCase__		,			UpperCAmelCase__		,			tokenizer_file=UpperCAmelCase__		,			unk_token=UpperCAmelCase__		,			bos_token=UpperCAmelCase__		,			eos_token=UpperCAmelCase__		,			add_prefix_space=UpperCAmelCase__		,			**UpperCAmelCase__		,			)

								lowerCAmelCase			=		json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()				)
								if pre_tok_state.get('''add_prefix_space'''		,			UpperCAmelCase__				) != add_prefix_space:
															lowerCAmelCase			=		getattr(UpperCAmelCase__		,			pre_tok_state.pop('''type'''				)				)
															lowerCAmelCase			=		add_prefix_space
															lowerCAmelCase			=		pre_tok_class(**UpperCAmelCase__				)

								lowerCAmelCase			=		add_prefix_space


	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE		,			__SCREAMING_SNAKE_CASE = None				)						->Optional[int]:
								lowerCAmelCase			=		self._tokenizer.model.save(UpperCAmelCase__		,			name=UpperCAmelCase__				)
								return tuple(UpperCAmelCase__				)




	def 			SCREAMING_SNAKE_CASE_				(							self		,			__SCREAMING_SNAKE_CASE				)						->List[str]:
								lowerCAmelCase			=		[]
								for is_user, text in conversation.iter_texts():
															input_ids.extend(self.encode(UpperCAmelCase__		,			add_special_tokens=UpperCAmelCase__				) + [self.eos_token_id]				)

								if len(UpperCAmelCase__				) > self.model_max_length:
															lowerCAmelCase			=		input_ids[-self.model_max_length :]
								return input_ids






"""simple docstring"""





from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder


# @@protoc_insertion_point(imports)

_a       =							_symbol_database.Default()


_a       =							_descriptor_pool.Default().AddSerializedFile(
    b'\n\x19sentencepiece_model.proto\x12\rsentencepiece"\x80\x0c\n\x0bTrainerSpec\x12\r\n\x05input\x18\x01 \x03(\t\x12\x14\n\x0cinput_format\x18\x07 \x01(\t\x12\x14\n\x0cmodel_prefix\x18\x02 \x01(\t\x12\x41\n\nmodel_type\x18\x03 \x01(\x0e\x32$.sentencepiece.TrainerSpec.ModelType:\x07UNIGRAM\x12\x18\n\nvocab_size\x18\x04 \x01(\x05:\x04\x38\x30\x30\x30\x12\x17\n\x0f\x61\x63\x63\x65pt_language\x18\x05 \x03(\t\x12 \n\x15self_test_sample_size\x18\x06 \x01(\x05:\x01\x30\x12*\n\x1b\x65nable_differential_privacy\x18\x32 \x01(\x08:\x05\x66\x61lse\x12+\n differential_privacy_noise_level\x18\x33 \x01(\x02:\x01\x30\x12\x32\n\'differential_privacy_clipping_threshold\x18\x34 \x01(\x04:\x01\x30\x12"\n\x12\x63haracter_coverage\x18\n \x01(\x02:\x06\x30.9995\x12\x1e\n\x13input_sentence_size\x18\x0b \x01(\x04:\x01\x30\x12$\n\x16shuffle_input_sentence\x18\x13 \x01(\x08:\x04true\x12 \n\x14mining_sentence_size\x18\x0c \x01(\x05\x42\x02\x18\x01\x12"\n\x16training_sentence_size\x18\r \x01(\x05\x42\x02\x18\x01\x12(\n\x17seed_sentencepiece_size\x18\x0e \x01(\x05:\x07\x31\x30\x30\x30\x30\x30\x30\x12\x1e\n\x10shrinking_factor\x18\x0f \x01(\x02:\x04\x30.75\x12!\n\x13max_sentence_length\x18\x12 \x01(\x05:\x04\x34\x31\x39\x32\x12\x17\n\x0bnum_threads\x18\x10 \x01(\x05:\x02\x31\x36\x12\x1d\n\x12num_sub_iterations\x18\x11 \x01(\x05:\x01\x32\x12$\n\x18max_sentencepiece_length\x18\x14 \x01(\x05:\x02\x31\x36\x12%\n\x17split_by_unicode_script\x18\x15 \x01(\x08:\x04true\x12\x1d\n\x0fsplit_by_number\x18\x17 \x01(\x08:\x04true\x12!\n\x13split_by_whitespace\x18\x16 \x01(\x08:\x04true\x12)\n\x1atreat_whitespace_as_suffix\x18\x18 \x01(\x08:\x05\x66\x61lse\x12+\n\x1c\x61llow_whitespace_only_pieces\x18\x1a \x01(\x08:\x05\x66\x61lse\x12\x1b\n\x0csplit_digits\x18\x19 \x01(\x08:\x05\x66\x61lse\x12#\n\x19pretokenization_delimiter\x18\x35 \x01(\t:\x00\x12\x17\n\x0f\x63ontrol_symbols\x18\x1e \x03(\t\x12\x1c\n\x14user_defined_symbols\x18\x1f \x03(\t\x12\x16\n\x0erequired_chars\x18$ \x01(\t\x12\x1c\n\rbyte_fallback\x18# \x01(\x08:\x05\x66\x61lse\x12+\n\x1dvocabulary_output_piece_score\x18  \x01(\x08:\x04true\x12\x1e\n\x10hard_vocab_limit\x18! \x01(\x08:\x04true\x12\x1c\n\ruse_all_vocab\x18" \x01(\x08:\x05\x66\x61lse\x12\x11\n\x06unk_id\x18( \x01(\x05:\x01\x30\x12\x11\n\x06\x62os_id\x18) \x01(\x05:\x01\x31\x12\x11\n\x06\x65os_id\x18* \x01(\x05:\x01\x32\x12\x12\n\x06pad_id\x18+ \x01(\x05:\x02-1\x12\x18\n\tunk_piece\x18- \x01(\t:\x05<unk>\x12\x16\n\tbos_piece\x18. \x01(\t:\x03<s>\x12\x17\n\teos_piece\x18/ \x01(\t:\x04</s>\x12\x18\n\tpad_piece\x18\x30 \x01(\t:\x05<pad>\x12\x1a\n\x0bunk_surface\x18, \x01(\t:\x05 \xe2\x81\x87 \x12+\n\x1ctrain_extremely_large_corpus\x18\x31 \x01(\x08:\x05\x66\x61lse"5\n\tModelType\x12\x0b\n\x07UNIGRAM\x10\x01\x12\x07\n\x03\x42PE\x10\x02\x12\x08\n\x04WORD\x10\x03\x12\x08\n\x04\x43HAR\x10\x04*\t\x08\xc8\x01\x10\x80\x80\x80\x80\x02"\xd1\x01\n\x0eNormalizerSpec\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x1c\n\x14precompiled_charsmap\x18\x02 \x01(\x0c\x12\x1e\n\x10\x61\x64\x64_dummy_prefix\x18\x03 \x01(\x08:\x04true\x12&\n\x18remove_extra_whitespaces\x18\x04 \x01(\x08:\x04true\x12 \n\x12\x65scape_whitespaces\x18\x05 \x01(\x08:\x04true\x12\x1e\n\x16normalization_rule_tsv\x18\x06 \x01(\t*\t\x08\xc8\x01\x10\x80\x80\x80\x80\x02"y\n\x0cSelfTestData\x12\x33\n\x07samples\x18\x01 \x03(\x0b\x32".sentencepiece.SelfTestData.Sample\x1a)\n\x06Sample\x12\r\n\x05input\x18\x01 \x01(\t\x12\x10\n\x08\x65xpected\x18\x02 \x01(\t*\t\x08\xc8\x01\x10\x80\x80\x80\x80\x02"\xfe\x03\n\nModelProto\x12\x37\n\x06pieces\x18\x01 \x03(\x0b\x32\'.sentencepiece.ModelProto.SentencePiece\x12\x30\n\x0ctrainer_spec\x18\x02 \x01(\x0b\x32\x1a.sentencepiece.TrainerSpec\x12\x36\n\x0fnormalizer_spec\x18\x03 \x01(\x0b\x32\x1d.sentencepiece.NormalizerSpec\x12\x33\n\x0eself_test_data\x18\x04 \x01(\x0b\x32\x1b.sentencepiece.SelfTestData\x12\x38\n\x11\x64\x65normalizer_spec\x18\x05 \x01(\x0b\x32\x1d.sentencepiece.NormalizerSpec\x1a\xd2\x01\n\rSentencePiece\x12\r\n\x05piece\x18\x01 \x01(\t\x12\r\n\x05score\x18\x02 \x01(\x02\x12\x42\n\x04type\x18\x03 \x01(\x0e\x32,.sentencepiece.ModelProto.SentencePiece.Type:\x06NORMAL"T\n\x04Type\x12\n\n\x06NORMAL\x10\x01\x12\x0b\n\x07UNKNOWN\x10\x02\x12\x0b\n\x07\x43ONTROL\x10\x03\x12\x10\n\x0cUSER_DEFINED\x10\x04\x12\x08\n\x04\x42YTE\x10\x06\x12\n\n\x06UNUSED\x10\x05*\t\x08\xc8\x01\x10\x80\x80\x80\x80\x02*\t\x08\xc8\x01\x10\x80\x80\x80\x80\x02\x42\x02H\x03'
)

_a       =							globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'sentencepiece_model_pb2', _globals)
if _descriptor._USE_C_DESCRIPTORS is False:
   _a       =							None
   _a       =							b'H\003'
   # (generated by protobuf compiler, but `_TRAINERSPEC` is not defined)
   # _TRAINERSPEC.fields_by_name["mining_sentence_size"]._options = None
   # _TRAINERSPEC.fields_by_name["mining_sentence_size"]._serialized_options = b"\030\001"
   # _TRAINERSPEC.fields_by_name["training_sentence_size"]._options = None
   # _TRAINERSPEC.fields_by_name["training_sentence_size"]._serialized_options = b"\030\001"
   _a       =							45
   _a       =							15_81
   _a       =							15_17
   _a       =							15_70
   _a       =							15_84
   _a       =							17_93
   _a       =							17_95
   _a       =							19_16
   _a       =							18_64
   _a       =							19_05
   _a       =							19_19
   _a       =							24_29
   _a       =							22_08
   _a       =							24_18
   _a       =							23_23
   _a       =							24_07
# @@protoc_insertion_point(module_scope)




