





'''simple docstring'''







import functools
import operator

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


snake_case_     :       str						=  logging.get_logger(__name__)

snake_case_     :       int						=  {
    "microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
    # See all WavLM models at https://huggingface.co/models?filter=wavlm
}


class 					__a      (lowerCamelCase     ):
							__a					:   Dict									=       "wavlm"

							def __init__(							self							:     Dict       ,     __magic_name__							:     Any=32       ,     __magic_name__							:     Dict=7_68       ,     __magic_name__							:     int=12       ,     __magic_name__							:     List[str]=12       ,     __magic_name__							:     Optional[int]=30_72       ,     __magic_name__							:     List[str]="gelu"       ,     __magic_name__							:     Dict=0.1       ,     __magic_name__							:     Any=0.1       ,     __magic_name__							:     str=0.1       ,     __magic_name__							:     Any=0.0       ,     __magic_name__							:     List[str]=0.1       ,     __magic_name__							:     Optional[Any]=0.1       ,     __magic_name__							:     Tuple=0.0_2       ,     __magic_name__							:     int=1E-5       ,     __magic_name__							:     str="group"       ,     __magic_name__							:     Tuple="gelu"       ,     __magic_name__							:     int=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)       ,     __magic_name__							:     Any=(5, 2, 2, 2, 2, 2, 2)       ,     __magic_name__							:     Optional[int]=(10, 3, 3, 3, 3, 2, 2)       ,     __magic_name__							:     Optional[int]=False       ,     __magic_name__							:     Dict=1_28       ,     __magic_name__							:     int=16       ,     __magic_name__							:     Tuple=3_20       ,     __magic_name__							:     Any=8_00       ,     __magic_name__							:     Optional[int]=False       ,     __magic_name__							:     Any=True       ,     __magic_name__							:     Tuple=0.0_5       ,     __magic_name__							:     Tuple=10       ,     __magic_name__							:     Union[str, Any]=2       ,     __magic_name__							:     List[str]=0.0       ,     __magic_name__							:     Tuple=10       ,     __magic_name__							:     Optional[Any]=3_20       ,     __magic_name__							:     Tuple=2       ,     __magic_name__							:     Dict=0.1       ,     __magic_name__							:     Any=1_00       ,     __magic_name__							:     Dict=2_56       ,     __magic_name__							:     Any=2_56       ,     __magic_name__							:     Tuple=0.1       ,     __magic_name__							:     Dict="mean"       ,     __magic_name__							:     Dict=False       ,     __magic_name__							:     List[str]=False       ,     __magic_name__							:     int=2_56       ,     __magic_name__							:     Optional[int]=(5_12, 5_12, 5_12, 5_12, 15_00)       ,     __magic_name__							:     Union[str, Any]=(5, 3, 3, 1, 1)       ,     __magic_name__							:     str=(1, 2, 3, 1, 1)       ,     __magic_name__							:     Tuple=5_12       ,     __magic_name__							:     Any=80       ,     __magic_name__							:     Dict=0       ,     __magic_name__							:     List[Any]=1       ,     __magic_name__							:     int=2       ,     __magic_name__							:     List[str]=False       ,     __magic_name__							:     Dict=3       ,     __magic_name__							:     List[Any]=2       ,     __magic_name__							:     str=3       ,     __magic_name__							:     Any=None       ,     **__magic_name__							:     Any       ,     )					->       List[Any]:







													"""simple docstring"""
													super().__init__(**__magic_name__       ,     pad_token_id=__magic_name__       ,     bos_token_id=__magic_name__       ,     eos_token_id=__magic_name__   )
													UpperCAmelCase_			:      Optional[Any]     						=  hidden_size
													UpperCAmelCase_			:      Union[str, Any]     						=  feat_extract_norm
													UpperCAmelCase_			:      Union[str, Any]     						=  feat_extract_activation
													UpperCAmelCase_			:      List[Any]     						=  list(__magic_name__   )
													UpperCAmelCase_			:      Any     						=  list(__magic_name__   )
													UpperCAmelCase_			:      List[str]     						=  list(__magic_name__   )
													UpperCAmelCase_			:      Tuple     						=  conv_bias
													UpperCAmelCase_			:      Any     						=  num_buckets
													UpperCAmelCase_			:      Union[str, Any]     						=  max_bucket_distance
													UpperCAmelCase_			:      Tuple     						=  num_conv_pos_embeddings
													UpperCAmelCase_			:      Optional[Any]     						=  num_conv_pos_embedding_groups
													UpperCAmelCase_			:      Union[str, Any]     						=  len(self.conv_dim   )
													UpperCAmelCase_			:      Union[str, Any]     						=  num_hidden_layers
													UpperCAmelCase_			:      List[Any]     						=  intermediate_size
													UpperCAmelCase_			:      Any     						=  hidden_act
													UpperCAmelCase_			:      List[Any]     						=  num_attention_heads
													UpperCAmelCase_			:      List[str]     						=  hidden_dropout
													UpperCAmelCase_			:      int     						=  attention_dropout
													UpperCAmelCase_			:      int     						=  activation_dropout
													UpperCAmelCase_			:      Optional[int]     						=  feat_proj_dropout
													UpperCAmelCase_			:      Any     						=  final_dropout
													UpperCAmelCase_			:      List[Any]     						=  layerdrop
													UpperCAmelCase_			:      Optional[int]     						=  layer_norm_eps
													UpperCAmelCase_			:      Optional[Any]     						=  initializer_range
													UpperCAmelCase_			:      Optional[int]     						=  num_ctc_classes
													UpperCAmelCase_			:      List[str]     						=  vocab_size
													UpperCAmelCase_			:      Tuple     						=  do_stable_layer_norm
													UpperCAmelCase_			:      List[Any]     						=  use_weighted_layer_sum
													UpperCAmelCase_			:      Dict     						=  classifier_proj_size

													if (
													    (len(self.conv_stride   ) != self.num_feat_extract_layers)
													    or (len(self.conv_kernel   ) != self.num_feat_extract_layers)
													    or (len(self.conv_dim   ) != self.num_feat_extract_layers)
													):
																			raise ValueError(
																			    '''Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='''
																			    ''' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='''
																			    F""" {len(self.conv_dim   )}`, `len(config.conv_stride) = {len(self.conv_stride   )}`,"""
																			    F""" `len(config.conv_kernel) = {len(self.conv_kernel   )}`."""   )

													# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
													UpperCAmelCase_			:      Optional[int]     						=  apply_spec_augment
													UpperCAmelCase_			:      Optional[Any]     						=  mask_time_prob
													UpperCAmelCase_			:      Dict     						=  mask_time_length
													UpperCAmelCase_			:      Dict     						=  mask_time_min_masks
													UpperCAmelCase_			:      Optional[Any]     						=  mask_feature_prob
													UpperCAmelCase_			:      Union[str, Any]     						=  mask_feature_length

													# parameters for pretraining with codevector quantized representations
													UpperCAmelCase_			:      str     						=  num_codevectors_per_group
													UpperCAmelCase_			:      List[Any]     						=  num_codevector_groups
													UpperCAmelCase_			:      str     						=  contrastive_logits_temperature
													UpperCAmelCase_			:      List[Any]     						=  num_negatives
													UpperCAmelCase_			:      List[str]     						=  codevector_dim
													UpperCAmelCase_			:      List[str]     						=  proj_codevector_dim
													UpperCAmelCase_			:      int     						=  diversity_loss_weight

													# ctc loss
													UpperCAmelCase_			:      List[Any]     						=  ctc_loss_reduction
													UpperCAmelCase_			:      Union[str, Any]     						=  ctc_zero_infinity

													# adapter
													UpperCAmelCase_			:      Dict     						=  add_adapter
													UpperCAmelCase_			:      Union[str, Any]     						=  adapter_kernel_size
													UpperCAmelCase_			:      str     						=  adapter_stride
													UpperCAmelCase_			:      Any     						=  num_adapter_layers
													UpperCAmelCase_			:      List[Any]     						=  output_hidden_size or hidden_size

													# SequenceClassification-specific parameter. Feel free to ignore for other classes.
													UpperCAmelCase_			:      str     						=  classifier_proj_size

													# XVector-specific parameters. Feel free to ignore for other classes.
													UpperCAmelCase_			:      List[Any]     						=  list(__magic_name__   )
													UpperCAmelCase_			:      str     						=  list(__magic_name__   )
													UpperCAmelCase_			:      Dict     						=  list(__magic_name__   )
													UpperCAmelCase_			:      List[str]     						=  xvector_output_dim



							@property
							def     UpperCAmelCase__	(							self							:     Tuple   )					->       Union[str, Any]:







													"""simple docstring"""
													return functools.reduce(operator.mul       ,     self.conv_stride       ,     1   )












'''simple docstring'''







def        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int = 10,			SCREAMING_SNAKE_CASE__      :			int = 22   ) ->	int:
						UpperCAmelCase_			:      Optional[int]     						=  range(1,			SCREAMING_SNAKE_CASE__   )
						UpperCAmelCase_			:      List[Any]     						=  range(1,			SCREAMING_SNAKE_CASE__   )
						return sum(
						    1 for power in powers for base in bases if len(str(base**power   )   ) == power   )


if __name__ == "__main__":
					print(f'''{solution(10, 22) = }''')





