

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


_SCREAMING_SNAKE_CASE  :						int         =    logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE  :						Optional[Any]         =    {}






class  UpperCAmelCase__	( A__ ):






  """simple docstring"""


  a     =      "llama"
  a     =      ["past_key_values"]






  def __init__(							self		:	int			,     __lowerCamelCase		:	Dict=3_2000			,     __lowerCamelCase		:	Union[str, Any]=4096			,     __lowerCamelCase		:	str=1_1008			,     __lowerCamelCase		:	List[str]=32			,     __lowerCamelCase		:	Tuple=32			,     __lowerCamelCase		:	int=None			,     __lowerCamelCase		:	List[Any]="silu"			,     __lowerCamelCase		:	Optional[Any]=2048			,     __lowerCamelCase		:	Any=0.02			,     __lowerCamelCase		:	List[str]=1e-6			,     __lowerCamelCase		:	Tuple=True			,     __lowerCamelCase		:	Union[str, Any]=0			,     __lowerCamelCase		:	int=1			,     __lowerCamelCase		:	List[Any]=2			,     __lowerCamelCase		:	Optional[Any]=1			,     __lowerCamelCase		:	Dict=False			,     __lowerCamelCase		:	Optional[Any]=None			,     **__lowerCamelCase		:	Optional[Any]			,     )	->							List[Any]:
       SCREAMING_SNAKE_CASE__			=					vocab_size
       SCREAMING_SNAKE_CASE__			=					max_position_embeddings
       SCREAMING_SNAKE_CASE__			=					hidden_size
       SCREAMING_SNAKE_CASE__			=					intermediate_size
       SCREAMING_SNAKE_CASE__			=					num_hidden_layers
       SCREAMING_SNAKE_CASE__			=					num_attention_heads

       # for backward compatibility
       if num_key_value_heads is None:
            SCREAMING_SNAKE_CASE__			=					num_attention_heads

       SCREAMING_SNAKE_CASE__			=					num_key_value_heads
       SCREAMING_SNAKE_CASE__			=					hidden_act
       SCREAMING_SNAKE_CASE__			=					initializer_range
       SCREAMING_SNAKE_CASE__			=					rms_norm_eps
       SCREAMING_SNAKE_CASE__			=					pretraining_tp
       SCREAMING_SNAKE_CASE__			=					use_cache
       SCREAMING_SNAKE_CASE__			=					rope_scaling
       self._rope_scaling_validation()

       super().__init__(
           pad_token_id=__lowerCamelCase			,     bos_token_id=__lowerCamelCase			,     eos_token_id=__lowerCamelCase			,     tie_word_embeddings=__lowerCamelCase			,     **__lowerCamelCase			,     )







  def    lowercase_	(							self		:	Optional[Any]      )	->							Tuple:







       if self.rope_scaling is None:
            return

       if not isinstance(self.rope_scaling			,     __lowerCamelCase      ) 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}'''      )
       SCREAMING_SNAKE_CASE__			=					self.rope_scaling.get('''type'''			,     __lowerCamelCase      )
       SCREAMING_SNAKE_CASE__			=					self.rope_scaling.get('''factor'''			,     __lowerCamelCase      )
       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(__lowerCamelCase			,     __lowerCamelCase      ) or rope_scaling_factor <= 1.0:
            raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''      )





from typing import List

import datasets
from datasets.tasks import AudioClassification

from ..folder_based_builder import folder_based_builder


_SCREAMING_SNAKE_CASE  :						Optional[Any]         =    datasets.utils.logging.get_logger(__name__)






class  UpperCAmelCase__	( folder_based_builder.FolderBasedBuilderConfig ):






  """simple docstring"""


  a     =      None
  a     =      None






class  UpperCAmelCase__	( folder_based_builder.FolderBasedBuilder ):






  """simple docstring"""


  a     =      datasets.Audio()
  a     =      "audio"
  a     =      AudioFolderConfig
  a     =      42  # definition at the bottom of the script
  a     =      AudioClassification(audio_column="audio"		,  label_column="label" )



_SCREAMING_SNAKE_CASE  :						str         =    [
    '''.aiff''',
    '''.au''',
    '''.avr''',
    '''.caf''',
    '''.flac''',
    '''.htk''',
    '''.svx''',
    '''.mat4''',
    '''.mat5''',
    '''.mpc2k''',
    '''.ogg''',
    '''.paf''',
    '''.pvf''',
    '''.raw''',
    '''.rf64''',
    '''.sd2''',
    '''.sds''',
    '''.ircam''',
    '''.voc''',
    '''.w64''',
    '''.wav''',
    '''.nist''',
    '''.wavex''',
    '''.wve''',
    '''.xi''',
    '''.mp3''',
    '''.opus''',
]
_SCREAMING_SNAKE_CASE  :						List[Any]         =    AUDIO_EXTENSIONS


