"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


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

lowerCAmelCase_:					Tuple     =					{
    "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}






class    a__    (   _a	):
       snake_case_							=      "gpt_neox"


       def __init__(     self,				_UpperCAmelCase=5_0432,				_UpperCAmelCase=6144,				_UpperCAmelCase=44,				_UpperCAmelCase=64,				_UpperCAmelCase=2_4576,				_UpperCAmelCase="gelu",				_UpperCAmelCase=0.25,				_UpperCAmelCase=1_0000,				_UpperCAmelCase=0.0,				_UpperCAmelCase=0.0,				_UpperCAmelCase=0.1,				_UpperCAmelCase=2048,				_UpperCAmelCase=0.02,				_UpperCAmelCase=1E-5,				_UpperCAmelCase=True,				_UpperCAmelCase=0,				_UpperCAmelCase=2,				_UpperCAmelCase=False,				_UpperCAmelCase=True,				_UpperCAmelCase=None,				**_UpperCAmelCase,				):
            '''simple docstring'''



            super().__init__(bos_token_id=_UpperCAmelCase,				eos_token_id=_UpperCAmelCase,				**_UpperCAmelCase  )
            lowercase__				 =							vocab_size
            lowercase__				 =							max_position_embeddings
            lowercase__				 =							hidden_size
            lowercase__				 =							num_hidden_layers
            lowercase__				 =							num_attention_heads
            lowercase__				 =							intermediate_size
            lowercase__				 =							hidden_act
            lowercase__				 =							rotary_pct
            lowercase__				 =							rotary_emb_base
            lowercase__				 =							attention_dropout
            lowercase__				 =							hidden_dropout
            lowercase__				 =							classifier_dropout
            lowercase__				 =							initializer_range
            lowercase__				 =							layer_norm_eps
            lowercase__				 =							use_cache
            lowercase__				 =							tie_word_embeddings
            lowercase__				 =							use_parallel_residual
            lowercase__				 =							rope_scaling
            self._rope_scaling_validation()

            if self.hidden_size % self.num_attention_heads != 0:
                 raise ValueError(
                     "The hidden size is not divisble by the number of attention heads! Make sure to update them!"  )


       def 	snake_case__	(     self  ):
            '''simple docstring'''



            if self.rope_scaling is None:
                 return

            if not isinstance(self.rope_scaling,				_UpperCAmelCase  ) or len(self.rope_scaling  ) != 2:
                 raise ValueError(
                     "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
                     F'''got {self.rope_scaling}'''  )
            lowercase__				 =							self.rope_scaling.get("type",				_UpperCAmelCase  )
            lowercase__				 =							self.rope_scaling.get("factor",				_UpperCAmelCase  )
            if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
                 raise ValueError(
                     F'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''  )
            if rope_scaling_factor is None or not isinstance(_UpperCAmelCase,				_UpperCAmelCase  ) or rope_scaling_factor <= 1.0:
                 raise ValueError(F'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''  )





"""simple docstring"""


from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader






class    a__    (   _a	):


   def __init__(     self,				_UpperCAmelCase,				_UpperCAmelCase = None,				_UpperCAmelCase = None,				_UpperCAmelCase = None,				_UpperCAmelCase = False,				_UpperCAmelCase = False,				_UpperCAmelCase = None,				**_UpperCAmelCase,				):
        '''simple docstring'''



        super().__init__(
            _UpperCAmelCase,				split=_UpperCAmelCase,				features=_UpperCAmelCase,				cache_dir=_UpperCAmelCase,				keep_in_memory=_UpperCAmelCase,				streaming=_UpperCAmelCase,				num_proc=_UpperCAmelCase,				**_UpperCAmelCase,				)
        lowercase__				 =							path_or_paths if isinstance(_UpperCAmelCase,				_UpperCAmelCase  ) else {self.split: path_or_paths}
        lowercase__				 =							Text(
            cache_dir=_UpperCAmelCase,				data_files=_UpperCAmelCase,				features=_UpperCAmelCase,				**_UpperCAmelCase,				)


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        if self.streaming:
             lowercase__				 =							self.builder.as_streaming_dataset(split=self.split  )
        # Build regular (map-style) dataset
        else:
             lowercase__				 =							None
             lowercase__				 =							None
             lowercase__				 =							None
             lowercase__				 =							None

             self.builder.download_and_prepare(
                 download_config=_UpperCAmelCase,				download_mode=_UpperCAmelCase,				verification_mode=_UpperCAmelCase,				base_path=_UpperCAmelCase,				num_proc=self.num_proc,				)
             lowercase__				 =							self.builder.as_dataset(
                 split=self.split,				verification_mode=_UpperCAmelCase,				in_memory=self.keep_in_memory  )
        return dataset




