
'''simple docstring'''





import functools
import operator

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


UpperCamelCase_   	=	logging.get_logger(__name__)

UpperCamelCase_   	=	{
    "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		(   A_					):
							lowercase_		:						List[Any]   							=  '''wavlm'''







							def __init__(						self  :  Optional[int]      ,				snake_case__  :  Union[str, Any]=32      ,				snake_case__  :  List[str]=768      ,				snake_case__  :  Optional[Any]=12      ,				snake_case__  :  Tuple=12      ,				snake_case__  :  str=3_072      ,				snake_case__  :  Tuple="gelu"      ,				snake_case__  :  List[str]=0.1      ,				snake_case__  :  Any=0.1      ,				snake_case__  :  Optional[int]=0.1      ,				snake_case__  :  int=0.0      ,				snake_case__  :  Optional[int]=0.1      ,				snake_case__  :  List[Any]=0.1      ,				snake_case__  :  Optional[Any]=0.0_2      ,				snake_case__  :  str=1E-5      ,				snake_case__  :  Tuple="group"      ,				snake_case__  :  Union[str, Any]="gelu"      ,				snake_case__  :  List[str]=(512, 512, 512, 512, 512, 512, 512)      ,				snake_case__  :  List[Any]=(5, 2, 2, 2, 2, 2, 2)      ,				snake_case__  :  Optional[Any]=(10, 3, 3, 3, 3, 2, 2)      ,				snake_case__  :  Dict=False      ,				snake_case__  :  Optional[Any]=128      ,				snake_case__  :  int=16      ,				snake_case__  :  Optional[int]=320      ,				snake_case__  :  List[str]=800      ,				snake_case__  :  str=False      ,				snake_case__  :  int=True      ,				snake_case__  :  List[Any]=0.0_5      ,				snake_case__  :  str=10      ,				snake_case__  :  Any=2      ,				snake_case__  :  Optional[int]=0.0      ,				snake_case__  :  List[str]=10      ,				snake_case__  :  List[str]=320      ,				snake_case__  :  str=2      ,				snake_case__  :  Optional[int]=0.1      ,				snake_case__  :  Optional[Any]=100      ,				snake_case__  :  List[str]=256      ,				snake_case__  :  int=256      ,				snake_case__  :  Dict=0.1      ,				snake_case__  :  int="mean"      ,				snake_case__  :  Union[str, Any]=False      ,				snake_case__  :  List[Any]=False      ,				snake_case__  :  str=256      ,				snake_case__  :  List[Any]=(512, 512, 512, 512, 1_500)      ,				snake_case__  :  Tuple=(5, 3, 3, 1, 1)      ,				snake_case__  :  str=(1, 2, 3, 1, 1)      ,				snake_case__  :  List[Any]=512      ,				snake_case__  :  str=80      ,				snake_case__  :  List[str]=0      ,				snake_case__  :  Union[str, Any]=1      ,				snake_case__  :  Optional[Any]=2      ,				snake_case__  :  Optional[int]=False      ,				snake_case__  :  int=3      ,				snake_case__  :  Any=2      ,				snake_case__  :  Union[str, Any]=3      ,				snake_case__  :  Tuple=None      ,				**snake_case__  :  Dict      ,				):
								"""simple docstring"""







								super().__init__(**snake_case__      ,				pad_token_id=snake_case__      ,				bos_token_id=snake_case__      ,				eos_token_id=snake_case__ )
								__lowerCAmelCase         =							hidden_size
								__lowerCAmelCase         =							feat_extract_norm
								__lowerCAmelCase         =							feat_extract_activation
								__lowerCAmelCase         =							list(snake_case__ )
								__lowerCAmelCase         =							list(snake_case__ )
								__lowerCAmelCase         =							list(snake_case__ )
								__lowerCAmelCase         =							conv_bias
								__lowerCAmelCase         =							num_buckets
								__lowerCAmelCase         =							max_bucket_distance
								__lowerCAmelCase         =							num_conv_pos_embeddings
								__lowerCAmelCase         =							num_conv_pos_embedding_groups
								__lowerCAmelCase         =							len(self.conv_dim )
								__lowerCAmelCase         =							num_hidden_layers
								__lowerCAmelCase         =							intermediate_size
								__lowerCAmelCase         =							hidden_act
								__lowerCAmelCase         =							num_attention_heads
								__lowerCAmelCase         =							hidden_dropout
								__lowerCAmelCase         =							attention_dropout
								__lowerCAmelCase         =							activation_dropout
								__lowerCAmelCase         =							feat_proj_dropout
								__lowerCAmelCase         =							final_dropout
								__lowerCAmelCase         =							layerdrop
								__lowerCAmelCase         =							layer_norm_eps
								__lowerCAmelCase         =							initializer_range
								__lowerCAmelCase         =							num_ctc_classes
								__lowerCAmelCase         =							vocab_size
								__lowerCAmelCase         =							do_stable_layer_norm
								__lowerCAmelCase         =							use_weighted_layer_sum
								__lowerCAmelCase         =							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         =							apply_spec_augment
								__lowerCAmelCase         =							mask_time_prob
								__lowerCAmelCase         =							mask_time_length
								__lowerCAmelCase         =							mask_time_min_masks
								__lowerCAmelCase         =							mask_feature_prob
								__lowerCAmelCase         =							mask_feature_length

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

								# ctc loss
								__lowerCAmelCase         =							ctc_loss_reduction
								__lowerCAmelCase         =							ctc_zero_infinity

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

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

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







							@property
							def       UpperCAmelCase__					(						self  :  List[Any] ):
								"""simple docstring"""







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








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,
)


UpperCamelCase_   	=	pytest.mark.integration






@pytest.mark.parametrize("path"			,							["paws", "csv"]  )
def 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	inspect_dataset(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@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 		_UpperCAmelCase   (	UpperCamelCase:     List[Any]			,							UpperCamelCase:     Any  ):






	"""simple docstring"""


	inspect_metric(UpperCamelCase			,							UpperCamelCase  )
	__lowerCAmelCase         =							path + ".py"
	assert script_name in os.listdir(UpperCamelCase  )
	assert "__pycache__" not in os.listdir(UpperCamelCase  )






@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 		_UpperCAmelCase   (	UpperCamelCase:     Optional[Any]			,							UpperCamelCase:     int			,							UpperCamelCase:     Tuple  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_info(UpperCamelCase			,							config_name=UpperCamelCase  )
	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 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     Any			,							UpperCamelCase:     List[str]  ):






	"""simple docstring"""


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






@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 		_UpperCAmelCase   (	UpperCamelCase:     List[str]			,							UpperCamelCase:     Optional[int]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_config_names(UpperCamelCase  )
	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 		_UpperCAmelCase   (	UpperCamelCase:     str			,							UpperCamelCase:     Tuple			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert list(infos.keys()  ) == expected_configs
	__lowerCAmelCase         =							expected_configs[0]
	assert expected_config in infos
	__lowerCAmelCase         =							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 		_UpperCAmelCase   (	UpperCamelCase:     Optional[int]			,							UpperCamelCase:     int			,							UpperCamelCase:     Optional[Any]  ):






	"""simple docstring"""


	__lowerCAmelCase         =							get_dataset_infos(UpperCamelCase  )
	assert expected_config in infos
	__lowerCAmelCase         =							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 		_UpperCAmelCase   (	UpperCamelCase:     Dict			,							UpperCamelCase:     List[str]			,							UpperCamelCase:     List[Any]  ):






	"""simple docstring"""


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






