



"""simple docstring"""






import functools
import operator

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


__snake_case							:     List[str]   =					logging.get_logger(__name__)

__snake_case							:     Dict   =					{
    'asapp/sew-tiny-100k': 'https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json',
    # See all SEW models at https://huggingface.co/models?filter=sew
}



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			'sew'

	def __init__(  self:	Optional[Any] ,    _SCREAMING_SNAKE_CASE:	int=32 ,    _SCREAMING_SNAKE_CASE:	Union[str, Any]=768 ,    _SCREAMING_SNAKE_CASE:	str=12 ,    _SCREAMING_SNAKE_CASE:	int=12 ,    _SCREAMING_SNAKE_CASE:	int=3072 ,    _SCREAMING_SNAKE_CASE:	Any=2 ,    _SCREAMING_SNAKE_CASE:	int="gelu" ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=0.1 ,    _SCREAMING_SNAKE_CASE:	Dict=0.1 ,    _SCREAMING_SNAKE_CASE:	List[str]=0.1 ,    _SCREAMING_SNAKE_CASE:	List[str]=0.0 ,    _SCREAMING_SNAKE_CASE:	List[Any]=0.1 ,    _SCREAMING_SNAKE_CASE:	int=0.1 ,    _SCREAMING_SNAKE_CASE:	Any=0.02 ,    _SCREAMING_SNAKE_CASE:	List[Any]=1e-5 ,    _SCREAMING_SNAKE_CASE:	str="group" ,    _SCREAMING_SNAKE_CASE:	Optional[int]="gelu" ,    _SCREAMING_SNAKE_CASE:	Dict=(64, 128, 128, 128, 128, 256, 256, 256, 256, 512, 512, 512, 512) ,    _SCREAMING_SNAKE_CASE:	str=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1) ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1) ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=False ,    _SCREAMING_SNAKE_CASE:	int=128 ,    _SCREAMING_SNAKE_CASE:	Any=16 ,    _SCREAMING_SNAKE_CASE:	List[str]=True ,    _SCREAMING_SNAKE_CASE:	Union[str, Any]=0.05 ,    _SCREAMING_SNAKE_CASE:	int=10 ,    _SCREAMING_SNAKE_CASE:	List[str]=2 ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=0.0 ,    _SCREAMING_SNAKE_CASE:	int=10 ,    _SCREAMING_SNAKE_CASE:	Any=0 ,    _SCREAMING_SNAKE_CASE:	Tuple="mean" ,    _SCREAMING_SNAKE_CASE:	Tuple=False ,    _SCREAMING_SNAKE_CASE:	List[Any]=False ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=256 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=0 ,    _SCREAMING_SNAKE_CASE:	Tuple=1 ,    _SCREAMING_SNAKE_CASE:	Optional[int]=2 ,    **_SCREAMING_SNAKE_CASE:	Optional[int] ,    )       -> Union[str, Any]:

				"""simple docstring"""

				super().__init__(**_SCREAMING_SNAKE_CASE ,    pad_token_id=_SCREAMING_SNAKE_CASE ,    bos_token_id=_SCREAMING_SNAKE_CASE ,    eos_token_id=_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[str]				= hidden_size
				__lowerCAmelCase   :						List[Any]				= feat_extract_norm
				__lowerCAmelCase   :						List[str]				= feat_extract_activation
				__lowerCAmelCase   :						Optional[int]				= list(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						Optional[Any]				= list(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						List[Any]				= list(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase   :						str				= conv_bias
				__lowerCAmelCase   :						Dict				= num_conv_pos_embeddings
				__lowerCAmelCase   :						int				= num_conv_pos_embedding_groups
				__lowerCAmelCase   :						Union[str, Any]				= len(self.conv_dim)
				__lowerCAmelCase   :						int				= num_hidden_layers
				__lowerCAmelCase   :						List[Any]				= intermediate_size
				__lowerCAmelCase   :						Union[str, Any]				= squeeze_factor
				__lowerCAmelCase   :						List[str]				= hidden_act
				__lowerCAmelCase   :						Dict				= num_attention_heads
				__lowerCAmelCase   :						str				= hidden_dropout
				__lowerCAmelCase   :						List[Any]				= attention_dropout
				__lowerCAmelCase   :						Union[str, Any]				= activation_dropout
				__lowerCAmelCase   :						Tuple				= feat_proj_dropout
				__lowerCAmelCase   :						str				= final_dropout
				__lowerCAmelCase   :						Union[str, Any]				= layerdrop
				__lowerCAmelCase   :						List[Any]				= layer_norm_eps
				__lowerCAmelCase   :						str				= initializer_range
				__lowerCAmelCase   :						Any				= vocab_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)`,"
							    F"""but is `len(config.conv_dim) = {len(self.conv_dim)}`, `len(config.conv_stride)"""
							    F"""= {len(self.conv_stride)}`, `len(config.conv_kernel) = {len(self.conv_kernel)}`.""")

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

				# ctc loss
				__lowerCAmelCase   :						str				= ctc_loss_reduction
				__lowerCAmelCase   :						Optional[Any]				= ctc_zero_infinity

				# sequence classification
				__lowerCAmelCase   :						Any				= use_weighted_layer_sum
				__lowerCAmelCase   :						Union[str, Any]				= classifier_proj_size







	@property
	def 							_SCREAMING_SNAKE_CASE     (  self:	List[Any])       -> int:

				"""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,
)


__snake_case							:     str   =					pytest.mark.integration


@pytest.mark.parametrize("path"      ,["paws", "csv"]			)
def     _lowercase       (						__snake_case      ,__snake_case			)		->     Any:
			inspect_dataset(__snake_case      ,__snake_case			)
			__lowerCAmelCase   :						str				= path + ".py"
			assert script_name in os.listdir(__snake_case			)
			assert "__pycache__" not in os.listdir(__snake_case			)


@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     _lowercase       (						__snake_case      ,__snake_case			)		->     int:
			inspect_metric(__snake_case      ,__snake_case			)
			__lowerCAmelCase   :						str				= path + ".py"
			assert script_name in os.listdir(__snake_case			)
			assert "__pycache__" not in os.listdir(__snake_case			)


@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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     Optional[int]:
			__lowerCAmelCase   :						str				= get_dataset_config_info(__snake_case      ,config_name=__snake_case			)
			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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     List[str]:
			with pytest.raises(__snake_case			):
						get_dataset_config_info(__snake_case      ,config_name=__snake_case			)


@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     _lowercase       (						__snake_case      ,__snake_case			)		->     int:
			__lowerCAmelCase   :						Dict				= get_dataset_config_names(__snake_case			)
			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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     Optional[Any]:
			__lowerCAmelCase   :						List[Any]				= get_dataset_infos(__snake_case			)
			assert list(infos.keys()			) == expected_configs
			__lowerCAmelCase   :						List[Any]				= expected_configs[0]
			assert expected_config in infos
			__lowerCAmelCase   :						Tuple				= 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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     Union[str, Any]:
			__lowerCAmelCase   :						Tuple				= get_dataset_infos(__snake_case			)
			assert expected_config in infos
			__lowerCAmelCase   :						int				= 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     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case			)		->     Any:
			with pytest.raises(__snake_case			):
						get_dataset_split_names(__snake_case      ,config_name=__snake_case			)