



import functools
import operator

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


__snake_case       :	str            =logging.get_logger(__name__)

__snake_case       :	List[Any]            ={
    '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  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_			="""wavlm"""



		def __init__(self	,__lowerCamelCase=32	,__lowerCamelCase=7_68	,__lowerCamelCase=12	,__lowerCamelCase=12	,__lowerCamelCase=30_72	,__lowerCamelCase="gelu"	,__lowerCamelCase=0.1	,__lowerCamelCase=0.1	,__lowerCamelCase=0.1	,__lowerCamelCase=0.0	,__lowerCamelCase=0.1	,__lowerCamelCase=0.1	,__lowerCamelCase=0.02	,__lowerCamelCase=1e-5	,__lowerCamelCase="group"	,__lowerCamelCase="gelu"	,__lowerCamelCase=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)	,__lowerCamelCase=(5, 2, 2, 2, 2, 2, 2)	,__lowerCamelCase=(10, 3, 3, 3, 3, 2, 2)	,__lowerCamelCase=False	,__lowerCamelCase=1_28	,__lowerCamelCase=16	,__lowerCamelCase=3_20	,__lowerCamelCase=8_00	,__lowerCamelCase=False	,__lowerCamelCase=True	,__lowerCamelCase=0.05	,__lowerCamelCase=10	,__lowerCamelCase=2	,__lowerCamelCase=0.0	,__lowerCamelCase=10	,__lowerCamelCase=3_20	,__lowerCamelCase=2	,__lowerCamelCase=0.1	,__lowerCamelCase=1_00	,__lowerCamelCase=2_56	,__lowerCamelCase=2_56	,__lowerCamelCase=0.1	,__lowerCamelCase="mean"	,__lowerCamelCase=False	,__lowerCamelCase=False	,__lowerCamelCase=2_56	,__lowerCamelCase=(5_12, 5_12, 5_12, 5_12, 15_00)	,__lowerCamelCase=(5, 3, 3, 1, 1)	,__lowerCamelCase=(1, 2, 3, 1, 1)	,__lowerCamelCase=5_12	,__lowerCamelCase=80	,__lowerCamelCase=0	,__lowerCamelCase=1	,__lowerCamelCase=2	,__lowerCamelCase=False	,__lowerCamelCase=3	,__lowerCamelCase=2	,__lowerCamelCase=3	,__lowerCamelCase=None	,**__lowerCamelCase	,)  ->    Tuple:

						"""simple docstring"""






						super().__init__(**__lowerCamelCase	,pad_token_id=__lowerCamelCase	,bos_token_id=__lowerCamelCase	,eos_token_id=__lowerCamelCase				)
						lowerCAmelCase__  :       Tuple				=  hidden_size
						lowerCAmelCase__  :       Dict				=  feat_extract_norm
						lowerCAmelCase__  :       List[Any]				=  feat_extract_activation
						lowerCAmelCase__  :       Union[str, Any]				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       Union[str, Any]				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       Tuple				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  conv_bias
						lowerCAmelCase__  :       Optional[int]				=  num_buckets
						lowerCAmelCase__  :       Dict				=  max_bucket_distance
						lowerCAmelCase__  :       Optional[Any]				=  num_conv_pos_embeddings
						lowerCAmelCase__  :       Dict				=  num_conv_pos_embedding_groups
						lowerCAmelCase__  :       Union[str, Any]				=  len(self.conv_dim				)
						lowerCAmelCase__  :       List[str]				=  num_hidden_layers
						lowerCAmelCase__  :       Union[str, Any]				=  intermediate_size
						lowerCAmelCase__  :       Optional[Any]				=  hidden_act
						lowerCAmelCase__  :       List[Any]				=  num_attention_heads
						lowerCAmelCase__  :       Tuple				=  hidden_dropout
						lowerCAmelCase__  :       List[Any]				=  attention_dropout
						lowerCAmelCase__  :       List[str]				=  activation_dropout
						lowerCAmelCase__  :       Any				=  feat_proj_dropout
						lowerCAmelCase__  :       int				=  final_dropout
						lowerCAmelCase__  :       Optional[Any]				=  layerdrop
						lowerCAmelCase__  :       Dict				=  layer_norm_eps
						lowerCAmelCase__  :       Optional[int]				=  initializer_range
						lowerCAmelCase__  :       int				=  num_ctc_classes
						lowerCAmelCase__  :       Tuple				=  vocab_size
						lowerCAmelCase__  :       Any				=  do_stable_layer_norm
						lowerCAmelCase__  :       List[str]				=  use_weighted_layer_sum
						lowerCAmelCase__  :       Any				=  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
						lowerCAmelCase__  :       Union[str, Any]				=  apply_spec_augment
						lowerCAmelCase__  :       List[Any]				=  mask_time_prob
						lowerCAmelCase__  :       int				=  mask_time_length
						lowerCAmelCase__  :       Union[str, Any]				=  mask_time_min_masks
						lowerCAmelCase__  :       List[Any]				=  mask_feature_prob
						lowerCAmelCase__  :       List[Any]				=  mask_feature_length

						# parameters for pretraining with codevector quantized representations
						lowerCAmelCase__  :       List[str]				=  num_codevectors_per_group
						lowerCAmelCase__  :       str				=  num_codevector_groups
						lowerCAmelCase__  :       Dict				=  contrastive_logits_temperature
						lowerCAmelCase__  :       Any				=  num_negatives
						lowerCAmelCase__  :       List[str]				=  codevector_dim
						lowerCAmelCase__  :       str				=  proj_codevector_dim
						lowerCAmelCase__  :       Union[str, Any]				=  diversity_loss_weight

						# ctc loss
						lowerCAmelCase__  :       Any				=  ctc_loss_reduction
						lowerCAmelCase__  :       Dict				=  ctc_zero_infinity

						# adapter
						lowerCAmelCase__  :       int				=  add_adapter
						lowerCAmelCase__  :       Dict				=  adapter_kernel_size
						lowerCAmelCase__  :       Dict				=  adapter_stride
						lowerCAmelCase__  :       Dict				=  num_adapter_layers
						lowerCAmelCase__  :       str				=  output_hidden_size or hidden_size

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

						# XVector-specific parameters. Feel free to ignore for other classes.
						lowerCAmelCase__  :       Union[str, Any]				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       List[Any]				=  list(__lowerCamelCase				)
						lowerCAmelCase__  :       int				=  xvector_output_dim



		@property
		def 	lowerCAmelCase__   (self				)  ->    List[str]:

						"""simple docstring"""






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






from collections.abc import Callable

import numpy as np






def 			lowerCAmelCase__	(					lowerCamelCase_	:	Callable ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float ,lowerCamelCase_	:	float):





				'''simple docstring'''

				lowerCAmelCase__  :       Dict				=  int(np.ceil((x_end - xa) / step_size))
				lowerCAmelCase__  :       Any				=  np.zeros((n + 1,))
				lowerCAmelCase__  :       Union[str, Any]				=  ya
				lowerCAmelCase__  :       str				=  xa

				for k in range(lowerCamelCase_):
								lowerCAmelCase__  :       Tuple				=  y[k] + step_size * ode_func(lowerCamelCase_ ,y[k])
								lowerCAmelCase__  :       str				=  y[k] + (
								    (step_size / 2) * (ode_func(lowerCamelCase_ ,y[k]) + ode_func(x + step_size ,lowerCamelCase_))
								)
								x += step_size

				return y


if __name__ == "__main__":
							import doctest

							doctest.testmod()

