






'''simple docstring'''







from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


UpperCamelCase     :   Dict	      =		{
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}




class 		UpperCamelCase__     (a      ):




		'''simple docstring'''





		_UpperCamelCase						=       "ernie_m"
		_UpperCamelCase						=       {"dropout": "classifier_dropout", "num_classes": "num_labels"}






		def __init__(   self ,_lowerCAmelCase = 25_00_02 ,_lowerCAmelCase = 7_68 ,_lowerCAmelCase = 12 ,_lowerCAmelCase = 12 ,_lowerCAmelCase = 30_72 ,_lowerCAmelCase = "gelu" ,_lowerCAmelCase = 0.1 ,_lowerCAmelCase = 0.1 ,_lowerCAmelCase = 5_14 ,_lowerCAmelCase = 0.02 ,_lowerCAmelCase = 1 ,_lowerCAmelCase = 1E-05 ,_lowerCAmelCase=None ,_lowerCAmelCase=False ,_lowerCAmelCase=0.0 ,**_lowerCAmelCase ,):
								super().__init__(pad_token_id=_lowerCAmelCase ,**_lowerCAmelCase							)
								lowerCamelCase__								=	vocab_size
								lowerCamelCase__								=	hidden_size
								lowerCamelCase__								=	num_hidden_layers
								lowerCamelCase__								=	num_attention_heads
								lowerCamelCase__								=	intermediate_size
								lowerCamelCase__								=	hidden_act
								lowerCamelCase__								=	hidden_dropout_prob
								lowerCamelCase__								=	attention_probs_dropout_prob
								lowerCamelCase__								=	max_position_embeddings
								lowerCamelCase__								=	initializer_range
								lowerCamelCase__								=	layer_norm_eps
								lowerCamelCase__								=	classifier_dropout
								lowerCamelCase__								=	is_decoder
								lowerCamelCase__								=	act_dropout








'''simple docstring'''


import math

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


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE									=				{
    "facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}

class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				List[Any]								=       "data2vec-audio"




 def __init__(						self      ,  _lowerCAmelCase=32      ,  _lowerCAmelCase=768      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=3072      ,  _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="gelu"      ,  _lowerCAmelCase=(512, 512, 512, 512, 512, 512, 512)      ,  _lowerCAmelCase=(5, 2, 2, 2, 2, 2, 2)      ,  _lowerCAmelCase=(10, 3, 3, 3, 3, 2, 2)      ,  _lowerCAmelCase=False      ,  _lowerCAmelCase=16      ,  _lowerCAmelCase=19      ,  _lowerCAmelCase=5      ,  _lowerCAmelCase=0.05      ,  _lowerCAmelCase=10      ,  _lowerCAmelCase=2      ,  _lowerCAmelCase=0.0      ,  _lowerCAmelCase=10      ,  _lowerCAmelCase=0      ,  _lowerCAmelCase="sum"      ,  _lowerCAmelCase=False      ,  _lowerCAmelCase=False      ,  _lowerCAmelCase=256      ,  _lowerCAmelCase=(512, 512, 512, 512, 1500)      ,  _lowerCAmelCase=(5, 3, 3, 1, 1)      ,  _lowerCAmelCase=(1, 2, 3, 1, 1)      ,  _lowerCAmelCase=512      ,  _lowerCAmelCase=0      ,  _lowerCAmelCase=1      ,  _lowerCAmelCase=2      ,  _lowerCAmelCase=False      ,  _lowerCAmelCase=3      ,  _lowerCAmelCase=2      ,  _lowerCAmelCase=3      ,  _lowerCAmelCase=None      ,  **_lowerCAmelCase      ,  )     ->				Dict:
     super().__init__(**_lowerCAmelCase      ,  pad_token_id=_lowerCAmelCase      ,  bos_token_id=_lowerCAmelCase      ,  eos_token_id=_lowerCAmelCase		)
     _lowerCAmelCase						      =   hidden_size
     _lowerCAmelCase						      =   feat_extract_activation
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   conv_bias
     _lowerCAmelCase						      =   num_conv_pos_embeddings
     _lowerCAmelCase						      =   num_conv_pos_embedding_groups
     _lowerCAmelCase						      =   conv_pos_kernel_size
     _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						      =   vocab_size
     _lowerCAmelCase						      =   use_weighted_layer_sum

     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						      =   mask_time_prob
     _lowerCAmelCase						      =   mask_time_length
     _lowerCAmelCase						      =   mask_time_min_masks
     _lowerCAmelCase						      =   mask_feature_prob
     _lowerCAmelCase						      =   mask_feature_length
     _lowerCAmelCase						      =   mask_feature_min_masks

     # 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(_lowerCAmelCase		)
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   list(_lowerCAmelCase		)
     _lowerCAmelCase						      =   xvector_output_dim





 @property
 def 				_snake_case (						self		)     ->				str:
     return math.prod(self.conv_stride		)


