




from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			def __init__(      self			,						lowerCamelCase__			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						lowerCamelCase__ = False			,						lowerCamelCase__ = False			,						lowerCamelCase__ = None			,						lowerCamelCase__ = None			,						**lowerCamelCase__			,						)    ->      Union[str, Any]:



							'''simple docstring'''
							super().__init__(
							    features=lowerCamelCase__			,						cache_dir=lowerCamelCase__			,						keep_in_memory=lowerCamelCase__			,						streaming=lowerCamelCase__			,						num_proc=lowerCamelCase__			,						**lowerCamelCase__			,						)
							__lowerCamelCase		       =    Generator(
							    cache_dir=lowerCamelCase__			,						features=lowerCamelCase__			,						generator=lowerCamelCase__			,						gen_kwargs=lowerCamelCase__			,						**lowerCamelCase__			,						)






			def       lowercase_    (      self							)    ->      Optional[int]:



							'''simple docstring'''
							# Build iterable dataset
							if self.streaming:
											__lowerCamelCase		       =    self.builder.as_streaming_dataset(split='train'							)
							# Build regular (map-style) dataset
							else:
											__lowerCamelCase		       =    None
											__lowerCamelCase		       =    None
											__lowerCamelCase		       =    None
											__lowerCamelCase		       =    None

											self.builder.download_and_prepare(
											    download_config=lowerCamelCase__			,						download_mode=lowerCamelCase__			,						verification_mode=lowerCamelCase__			,						base_path=lowerCamelCase__			,						num_proc=self.num_proc			,						)
											__lowerCamelCase		       =    self.builder.as_dataset(
											    split='train'			,						verification_mode=lowerCamelCase__			,						in_memory=self.keep_in_memory							)
							return dataset








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


__A        =    logging.get_logger(__name__)

__A        =    {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__A        =    {
    "tokenizer_file": {
        "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json",
    },
}

__A        =    {
    "gpt-neox-20b": 20_48,
}







class     __lowerCAmelCase (       __magic_name__ ):

			"""simple docstring"""







			snake_case_   		=       VOCAB_FILES_NAMES
			snake_case_   		=       PRETRAINED_VOCAB_FILES_MAP
			snake_case_   		=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case_   		=       ['''input_ids''', '''attention_mask''']


			def __init__(      self			,						lowerCamelCase__=None			,						lowerCamelCase__=None			,						lowerCamelCase__=None			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__="<|endoftext|>"			,						lowerCamelCase__=False			,						**lowerCamelCase__			,						)    ->      int:



							'''simple docstring'''
							super().__init__(
							    lowerCamelCase__			,						lowerCamelCase__			,						tokenizer_file=lowerCamelCase__			,						unk_token=lowerCamelCase__			,						bos_token=lowerCamelCase__			,						eos_token=lowerCamelCase__			,						add_prefix_space=lowerCamelCase__			,						**lowerCamelCase__			,						)

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

							__lowerCamelCase		       =    add_prefix_space


			def       lowercase_    (      self			,						lowerCamelCase__			,						lowerCamelCase__ = None							)    ->      Tuple[str]:



							'''simple docstring'''
							__lowerCamelCase		       =    self._tokenizer.model.save(lowerCamelCase__			,						name=lowerCamelCase__							)
							return tuple(lowerCamelCase__							)






			def       lowercase_    (      self			,						lowerCamelCase__							)    ->      List[int]:



							'''simple docstring'''
							__lowerCamelCase		       =    []
							for is_user, text in conversation.iter_texts():
											input_ids.extend(self.encode(lowerCamelCase__			,						add_special_tokens=lowerCamelCase__							) + [self.eos_token_id]							)

							if len(lowerCamelCase__							) > self.model_max_length:
											__lowerCamelCase		       =    input_ids[-self.model_max_length :]
							return input_ids


