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							(				UpperCAmelCase_     ):
   __UpperCAmelCase : Tuple      =			'wavlm'


   def __init__(self     :						Union[str, Any]       ,  __UpperCAmelCase     :						int=3_2       ,  __UpperCAmelCase     :						int=7_6_8       ,  __UpperCAmelCase     :						Dict=1_2       ,  __UpperCAmelCase     :						List[Any]=1_2       ,  __UpperCAmelCase     :						int=3_0_7_2       ,  __UpperCAmelCase     :						List[str]="gelu"       ,  __UpperCAmelCase     :						Optional[Any]=0.1       ,  __UpperCAmelCase     :						Dict=0.1       ,  __UpperCAmelCase     :						Tuple=0.1       ,  __UpperCAmelCase     :						Any=0.0       ,  __UpperCAmelCase     :						Union[str, Any]=0.1       ,  __UpperCAmelCase     :						Union[str, Any]=0.1       ,  __UpperCAmelCase     :						Dict=0.02       ,  __UpperCAmelCase     :						Optional[Any]=1E-5       ,  __UpperCAmelCase     :						List[Any]="group"       ,  __UpperCAmelCase     :						Dict="gelu"       ,  __UpperCAmelCase     :						Tuple=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)       ,  __UpperCAmelCase     :						Any=(5, 2, 2, 2, 2, 2, 2)       ,  __UpperCAmelCase     :						int=(1_0, 3, 3, 3, 3, 2, 2)       ,  __UpperCAmelCase     :						Any=False       ,  __UpperCAmelCase     :						Optional[int]=1_2_8       ,  __UpperCAmelCase     :						Optional[int]=1_6       ,  __UpperCAmelCase     :						List[str]=3_2_0       ,  __UpperCAmelCase     :						List[str]=8_0_0       ,  __UpperCAmelCase     :						int=False       ,  __UpperCAmelCase     :						Optional[int]=True       ,  __UpperCAmelCase     :						int=0.05       ,  __UpperCAmelCase     :						List[Any]=1_0       ,  __UpperCAmelCase     :						Optional[int]=2       ,  __UpperCAmelCase     :						List[str]=0.0       ,  __UpperCAmelCase     :						Optional[Any]=1_0       ,  __UpperCAmelCase     :						List[str]=3_2_0       ,  __UpperCAmelCase     :						List[str]=2       ,  __UpperCAmelCase     :						int=0.1       ,  __UpperCAmelCase     :						Union[str, Any]=1_0_0       ,  __UpperCAmelCase     :						int=2_5_6       ,  __UpperCAmelCase     :						Union[str, Any]=2_5_6       ,  __UpperCAmelCase     :						List[str]=0.1       ,  __UpperCAmelCase     :						str="mean"       ,  __UpperCAmelCase     :						Union[str, Any]=False       ,  __UpperCAmelCase     :						str=False       ,  __UpperCAmelCase     :						Optional[int]=2_5_6       ,  __UpperCAmelCase     :						Tuple=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0)       ,  __UpperCAmelCase     :						List[Any]=(5, 3, 3, 1, 1)       ,  __UpperCAmelCase     :						List[Any]=(1, 2, 3, 1, 1)       ,  __UpperCAmelCase     :						Optional[Any]=5_1_2       ,  __UpperCAmelCase     :						Optional[int]=8_0       ,  __UpperCAmelCase     :						int=0       ,  __UpperCAmelCase     :						Optional[int]=1       ,  __UpperCAmelCase     :						Tuple=2       ,  __UpperCAmelCase     :						Tuple=False       ,  __UpperCAmelCase     :						List[str]=3       ,  __UpperCAmelCase     :						Optional[Any]=2       ,  __UpperCAmelCase     :						Optional[Any]=3       ,  __UpperCAmelCase     :						Optional[int]=None       ,  **__UpperCAmelCase     :						Optional[int]       ,  )						->				List[Any]:
         """simple docstring"""



         super().__init__(**__UpperCAmelCase       ,  pad_token_id=__UpperCAmelCase       ,  bos_token_id=__UpperCAmelCase       ,  eos_token_id=__UpperCAmelCase		)
         UpperCAmelCase__								=  hidden_size
         UpperCAmelCase__								=  feat_extract_norm
         UpperCAmelCase__								=  feat_extract_activation
         UpperCAmelCase__								=  list(__UpperCAmelCase		)
         UpperCAmelCase__								=  list(__UpperCAmelCase		)
         UpperCAmelCase__								=  list(__UpperCAmelCase		)
         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(__UpperCAmelCase		)
         UpperCAmelCase__								=  list(__UpperCAmelCase		)
         UpperCAmelCase__								=  list(__UpperCAmelCase		)
         UpperCAmelCase__								=  xvector_output_dim





   @property
   def 			lowercase_      (self     :						Tuple		)						->				Tuple:
         """simple docstring"""



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











from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


UpperCAmelCase__				   =		logging.get_logger(__name__)

UpperCAmelCase__				   =		{
    "t5-small": "https://huggingface.co/t5-small/resolve/main/config.json",
    "t5-base": "https://huggingface.co/t5-base/resolve/main/config.json",
    "t5-large": "https://huggingface.co/t5-large/resolve/main/config.json",
    "t5-3b": "https://huggingface.co/t5-3b/resolve/main/config.json",
    "t5-11b": "https://huggingface.co/t5-11b/resolve/main/config.json",
}






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      __snake_case       =  '''t5'''
      __snake_case       =  ['''past_key_values''']
      __snake_case       =  {'''hidden_size''': '''d_model''', '''num_attention_heads''': '''num_heads''', '''num_hidden_layers''': '''num_layers'''}







      def __init__(      self      :						Optional[Any] ,					__UpperCAmelCase      :						Optional[Any]=32_128 ,					__UpperCAmelCase      :						List[Any]=512 ,					__UpperCAmelCase      :						Dict=64 ,					__UpperCAmelCase      :						Tuple=2_048 ,					__UpperCAmelCase      :						int=6 ,					__UpperCAmelCase      :						Optional[int]=None ,					__UpperCAmelCase      :						Optional[int]=8 ,					__UpperCAmelCase      :						str=32 ,					__UpperCAmelCase      :						Tuple=128 ,					__UpperCAmelCase      :						Optional[Any]=0.1 ,					__UpperCAmelCase      :						int=1e-6 ,					__UpperCAmelCase      :						int=1.0 ,					__UpperCAmelCase      :						List[str]="relu" ,					__UpperCAmelCase      :						int=True ,					__UpperCAmelCase      :						int=True ,					__UpperCAmelCase      :						List[Any]=0 ,					__UpperCAmelCase      :						int=1 ,					**__UpperCAmelCase      :						str ,					)    ->Optional[Any]:




       """simple docstring"""


       a		  =      vocab_size
       a		  =      d_model
       a		  =      d_kv
       a		  =      d_ff
       a		  =      num_layers
       a		  =      (
           num_decoder_layers if num_decoder_layers is not None else self.num_layers
       )  # default = symmetry
       a		  =      num_heads
       a		  =      relative_attention_num_buckets
       a		  =      relative_attention_max_distance
       a		  =      dropout_rate
       a		  =      layer_norm_epsilon
       a		  =      initializer_factor
       a		  =      feed_forward_proj
       a		  =      use_cache

       a		  =      self.feed_forward_proj.split('''-'''  )
       a		  =      act_info[-1]
       a		  =      act_info[0] == '''gated'''

       if len(__UpperCAmelCase  ) > 1 and act_info[0] != "gated" or len(__UpperCAmelCase  ) > 2:
        raise ValueError(
            F"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
            '''Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '''
            '''\'gated-gelu\' or \'relu\''''  )

       # for backwards compatibility
       if feed_forward_proj == "gated-gelu":
        a		  =      '''gelu_new'''

       super().__init__(
           pad_token_id=__UpperCAmelCase ,					eos_token_id=__UpperCAmelCase ,					is_encoder_decoder=__UpperCAmelCase ,					**__UpperCAmelCase ,					)






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      @property
      def       __lowerCAmelCase					(      self      :						Optional[Any]  )    ->Mapping[str, Mapping[int, str]]:




       """simple docstring"""


       a		  =      {
           '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
           '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
       }
       if self.use_past:
        a		  =      '''past_encoder_sequence + sequence'''
        a		  =      {0: '''batch'''}
        a		  =      {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
       else:
        a		  =      {0: '''batch''', 1: '''decoder_sequence'''}
        a		  =      {0: '''batch''', 1: '''decoder_sequence'''}

       if self.use_past:
        self.fill_with_past_key_values_(__UpperCAmelCase ,					direction='''inputs'''  )

       return common_inputs







      @property
      def       __lowerCAmelCase					(      self      :						Union[str, Any]  )    ->int:




       """simple docstring"""


       return 13


