



"""simple docstring"""





import functools
import operator

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


lowercase  							=					logging.get_logger(__name__)

lowercase  							=					{
    '''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 			lowercase__			(      A    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					'''wavlm'''






							def __init__(  self	,       snake_case=32	,       snake_case=768	,       snake_case=12	,       snake_case=12	,       snake_case=3072	,       snake_case="gelu"	,       snake_case=0.1	,       snake_case=0.1	,       snake_case=0.1	,       snake_case=0.0	,       snake_case=0.1	,       snake_case=0.1	,       snake_case=0.02	,       snake_case=1E-5	,       snake_case="group"	,       snake_case="gelu"	,       snake_case=(512, 512, 512, 512, 512, 512, 512)	,       snake_case=(5, 2, 2, 2, 2, 2, 2)	,       snake_case=(10, 3, 3, 3, 3, 2, 2)	,       snake_case=False	,       snake_case=128	,       snake_case=16	,       snake_case=320	,       snake_case=800	,       snake_case=False	,       snake_case=True	,       snake_case=0.05	,       snake_case=10	,       snake_case=2	,       snake_case=0.0	,       snake_case=10	,       snake_case=320	,       snake_case=2	,       snake_case=0.1	,       snake_case=100	,       snake_case=256	,       snake_case=256	,       snake_case=0.1	,       snake_case="mean"	,       snake_case=False	,       snake_case=False	,       snake_case=256	,       snake_case=(512, 512, 512, 512, 1500)	,       snake_case=(5, 3, 3, 1, 1)	,       snake_case=(1, 2, 3, 1, 1)	,       snake_case=512	,       snake_case=80	,       snake_case=0	,       snake_case=1	,       snake_case=2	,       snake_case=False	,       snake_case=3	,       snake_case=2	,       snake_case=3	,       snake_case=None	,       **snake_case	,       )			->							List[str]:
									super().__init__(**snake_case	,       pad_token_id=snake_case	,       bos_token_id=snake_case	,       eos_token_id=snake_case						)
									_UpperCAmelCase							 =		hidden_size
									_UpperCAmelCase							 =		feat_extract_norm
									_UpperCAmelCase							 =		feat_extract_activation
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		conv_bias
									_UpperCAmelCase							 =		num_buckets
									_UpperCAmelCase							 =		max_bucket_distance
									_UpperCAmelCase							 =		num_conv_pos_embeddings
									_UpperCAmelCase							 =		num_conv_pos_embedding_groups
									_UpperCAmelCase							 =		len(self.conv_dim						)
									_UpperCAmelCase							 =		num_hidden_layers
									_UpperCAmelCase							 =		intermediate_size
									_UpperCAmelCase							 =		hidden_act
									_UpperCAmelCase							 =		num_attention_heads
									_UpperCAmelCase							 =		hidden_dropout
									_UpperCAmelCase							 =		attention_dropout
									_UpperCAmelCase							 =		activation_dropout
									_UpperCAmelCase							 =		feat_proj_dropout
									_UpperCAmelCase							 =		final_dropout
									_UpperCAmelCase							 =		layerdrop
									_UpperCAmelCase							 =		layer_norm_eps
									_UpperCAmelCase							 =		initializer_range
									_UpperCAmelCase							 =		num_ctc_classes
									_UpperCAmelCase							 =		vocab_size
									_UpperCAmelCase							 =		do_stable_layer_norm
									_UpperCAmelCase							 =		use_weighted_layer_sum
									_UpperCAmelCase							 =		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							 =		apply_spec_augment
									_UpperCAmelCase							 =		mask_time_prob
									_UpperCAmelCase							 =		mask_time_length
									_UpperCAmelCase							 =		mask_time_min_masks
									_UpperCAmelCase							 =		mask_feature_prob
									_UpperCAmelCase							 =		mask_feature_length

									# parameters for pretraining with codevector quantized representations
									_UpperCAmelCase							 =		num_codevectors_per_group
									_UpperCAmelCase							 =		num_codevector_groups
									_UpperCAmelCase							 =		contrastive_logits_temperature
									_UpperCAmelCase							 =		num_negatives
									_UpperCAmelCase							 =		codevector_dim
									_UpperCAmelCase							 =		proj_codevector_dim
									_UpperCAmelCase							 =		diversity_loss_weight

									# ctc loss
									_UpperCAmelCase							 =		ctc_loss_reduction
									_UpperCAmelCase							 =		ctc_zero_infinity

									# adapter
									_UpperCAmelCase							 =		add_adapter
									_UpperCAmelCase							 =		adapter_kernel_size
									_UpperCAmelCase							 =		adapter_stride
									_UpperCAmelCase							 =		num_adapter_layers
									_UpperCAmelCase							 =		output_hidden_size or hidden_size

									# SequenceClassification-specific parameter. Feel free to ignore for other classes.
									_UpperCAmelCase							 =		classifier_proj_size

									# XVector-specific parameters. Feel free to ignore for other classes.
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		list(snake_case						)
									_UpperCAmelCase							 =		xvector_output_dim






							@property
							def        lowerCamelCase_   (  self						)			->							Tuple:
									return functools.reduce(operator.mul	,       self.conv_stride	,       1						)







"""simple docstring"""





from __future__ import annotations

from cmath import sqrt




def 	UpperCAmelCase     (		A	:						int     ,				A	:						int     ,				A	:						int       ):

		'''simple docstring'''


		if a == 0:
				raise ValueError('Coefficient \'a\' must not be zero.'       )
		_UpperCAmelCase							 =		b * b - 4 * a * c

		_UpperCAmelCase							 =		(-b + sqrt(A       )) / (2 * a)
		_UpperCAmelCase							 =		(-b - sqrt(A       )) / (2 * a)

		return (
		    root_a.real if not root_a.imag else root_a,
		    root_a.real if not root_a.imag else root_a,
		)




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase ,					_UpperCAmelCase							 =		quadratic_roots(a=5     ,				b=6     ,				c=1       )
		print(f'The solutions are: {solutiona} and {solutiona}'       )


if __name__ == "__main__":
					main()


