


'''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    __magic_name__				(						lowerCAmelCase							):
       UpperCAmelCase		 ="wavlm"






       def __init__(     self    ,				snake_case=3_2    ,				snake_case=7_6_8    ,				snake_case=1_2    ,				snake_case=1_2    ,				snake_case=3_0_7_2    ,				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=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)    ,				snake_case=(5, 2, 2, 2, 2, 2, 2)    ,				snake_case=(1_0, 3, 3, 3, 3, 2, 2)    ,				snake_case=False    ,				snake_case=1_2_8    ,				snake_case=1_6    ,				snake_case=3_2_0    ,				snake_case=8_0_0    ,				snake_case=False    ,				snake_case=True    ,				snake_case=0.05    ,				snake_case=1_0    ,				snake_case=2    ,				snake_case=0.0    ,				snake_case=1_0    ,				snake_case=3_2_0    ,				snake_case=2    ,				snake_case=0.1    ,				snake_case=1_0_0    ,				snake_case=2_5_6    ,				snake_case=2_5_6    ,				snake_case=0.1    ,				snake_case="mean"    ,				snake_case=False    ,				snake_case=False    ,				snake_case=2_5_6    ,				snake_case=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0)    ,				snake_case=(5, 3, 3, 1, 1)    ,				snake_case=(1, 2, 3, 1, 1)    ,				snake_case=5_1_2    ,				snake_case=8_0    ,				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    ,				)		->    Union[str, Any]:




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

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

          # ctc loss
          _UpperCAmelCase  :  int				       =ctc_loss_reduction
          _UpperCAmelCase  :  Optional[int]				       =ctc_zero_infinity

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

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

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






       @property
       def      lowerCAmelCase						(     self)		->    str:




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





'''simple docstring'''






import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


lowercase				=pytest.mark.integration





@pytest.mark.parametrize('path'			,       ['paws', 'csv']				)
def lowerCamelCase__     (		__lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				Optional[Any]				):







   '''simple docstring'''




   inspect_dataset(__lowerCamelCase			,       __lowerCamelCase				)
   _UpperCAmelCase  :  List[str]				       =path + '.py'
   assert script_name in os.listdir(__lowerCamelCase				)
   assert "__pycache__" not in os.listdir(__lowerCamelCase				)





@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'				)
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'				)
@pytest.mark.parametrize('path'			,       ['accuracy']				)
def lowerCamelCase__     (		__lowerCamelCase			:				Dict			,       __lowerCamelCase			:				str				):







   '''simple docstring'''




   inspect_metric(__lowerCamelCase			,       __lowerCamelCase				)
   _UpperCAmelCase  :  List[Any]				       =path + '.py'
   assert script_name in os.listdir(__lowerCamelCase				)
   assert "__pycache__" not in os.listdir(__lowerCamelCase				)





@pytest.mark.parametrize(
    'path, config_name, expected_splits'			,       [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Any			,       __lowerCamelCase			:				Optional[int]			,       __lowerCamelCase			:				str				):







   '''simple docstring'''




   _UpperCAmelCase  :  str				       =get_dataset_config_info(__lowerCamelCase			,       config_name=__lowerCamelCase				)
   assert info.config_name == config_name
   assert list(info.splits.keys()				) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'			,       [
        ('paws', None, ValueError),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				Optional[Any]			,       __lowerCamelCase			:				List[str]				):







   '''simple docstring'''




   with pytest.raises(__lowerCamelCase				):
      get_dataset_config_info(__lowerCamelCase			,       config_name=__lowerCamelCase				)





@pytest.mark.parametrize(
    'path, expected'			,       [
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				List[str]				):







   '''simple docstring'''




   _UpperCAmelCase  :  Dict				       =get_dataset_config_names(__lowerCamelCase				)
   assert expected in config_names





@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'			,       [
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				List[Any]			,       __lowerCamelCase			:				List[Any]				):







   '''simple docstring'''




   _UpperCAmelCase  :  Optional[int]				       =get_dataset_infos(__lowerCamelCase				)
   assert list(infos.keys()				) == expected_configs
   _UpperCAmelCase  :  Optional[int]				       =expected_configs[0]
   assert expected_config in infos
   _UpperCAmelCase  :  Optional[int]				       =infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys()				) == expected_splits_in_first_config





@pytest.mark.parametrize(
    'path, expected_config, expected_splits'			,       [
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				Tuple			,       __lowerCamelCase			:				int				):







   '''simple docstring'''




   _UpperCAmelCase  :  str				       =get_dataset_infos(__lowerCamelCase				)
   assert expected_config in infos
   _UpperCAmelCase  :  Dict				       =infos[expected_config]
   assert info.config_name == expected_config
   assert list(info.splits.keys()				) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'			,       [
        ('paws', None, ValueError),
    ]			,       )
def lowerCamelCase__     (		__lowerCamelCase			:				Union[str, Any]			,       __lowerCamelCase			:				Optional[Any]			,       __lowerCamelCase			:				Any				):







   '''simple docstring'''




   with pytest.raises(__lowerCamelCase				):
      get_dataset_split_names(__lowerCamelCase			,       config_name=__lowerCamelCase				)

