





import math

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


UpperCAmelCase_     							= logging.get_logger(__name__)

UpperCAmelCase_     							= {
    '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     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							Optional[int]   		=		"data2vec-audio"




   def __init__(    self,		__magic_name__=32,		__magic_name__=768,		__magic_name__=12,		__magic_name__=12,		__magic_name__=3072,		__magic_name__="gelu",		__magic_name__=0.1,		__magic_name__=0.1,		__magic_name__=0.1,		__magic_name__=0.0,		__magic_name__=0.1,		__magic_name__=0.1,		__magic_name__=0.02,		__magic_name__=1E-5,		__magic_name__="gelu",		__magic_name__=(512, 512, 512, 512, 512, 512, 512),		__magic_name__=(5, 2, 2, 2, 2, 2, 2),		__magic_name__=(10, 3, 3, 3, 3, 2, 2),		__magic_name__=False,		__magic_name__=16,		__magic_name__=19,		__magic_name__=5,		__magic_name__=0.05,		__magic_name__=10,		__magic_name__=2,		__magic_name__=0.0,		__magic_name__=10,		__magic_name__=0,		__magic_name__="sum",		__magic_name__=False,		__magic_name__=False,		__magic_name__=256,		__magic_name__=(512, 512, 512, 512, 1500),		__magic_name__=(5, 3, 3, 1, 1),		__magic_name__=(1, 2, 3, 1, 1),		__magic_name__=512,		__magic_name__=0,		__magic_name__=1,		__magic_name__=2,		__magic_name__=False,		__magic_name__=3,		__magic_name__=2,		__magic_name__=3,		__magic_name__=None,		**__magic_name__,		) ->      List[str]:






       """simple docstring"""
       super().__init__(**__magic_name__,		pad_token_id=__magic_name__,		bos_token_id=__magic_name__,		eos_token_id=__magic_name__							)
       UpperCamelCase__							:				Union[str, Any]          =      hidden_size
       UpperCamelCase__							:				Optional[Any]          =      feat_extract_activation
       UpperCamelCase__							:				int          =      list(__magic_name__							)
       UpperCamelCase__							:				Optional[Any]          =      list(__magic_name__							)
       UpperCamelCase__							:				str          =      list(__magic_name__							)
       UpperCamelCase__							:				Optional[int]          =      conv_bias
       UpperCamelCase__							:				List[str]          =      num_conv_pos_embeddings
       UpperCamelCase__							:				Optional[Any]          =      num_conv_pos_embedding_groups
       UpperCamelCase__							:				Tuple          =      conv_pos_kernel_size
       UpperCamelCase__							:				Union[str, Any]          =      len(self.conv_dim							)
       UpperCamelCase__							:				Optional[Any]          =      num_hidden_layers
       UpperCamelCase__							:				Any          =      intermediate_size
       UpperCamelCase__							:				Union[str, Any]          =      hidden_act
       UpperCamelCase__							:				int          =      num_attention_heads
       UpperCamelCase__							:				List[str]          =      hidden_dropout
       UpperCamelCase__							:				Optional[Any]          =      attention_dropout
       UpperCamelCase__							:				List[Any]          =      activation_dropout
       UpperCamelCase__							:				Optional[Any]          =      feat_proj_dropout
       UpperCamelCase__							:				Tuple          =      final_dropout
       UpperCamelCase__							:				Any          =      layerdrop
       UpperCamelCase__							:				Optional[int]          =      layer_norm_eps
       UpperCamelCase__							:				Optional[int]          =      initializer_range
       UpperCamelCase__							:				Union[str, Any]          =      vocab_size
       UpperCamelCase__							:				Optional[Any]          =      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
       UpperCamelCase__							:				Optional[int]          =      mask_time_prob
       UpperCamelCase__							:				Optional[int]          =      mask_time_length
       UpperCamelCase__							:				Tuple          =      mask_time_min_masks
       UpperCamelCase__							:				Any          =      mask_feature_prob
       UpperCamelCase__							:				List[Any]          =      mask_feature_length
       UpperCamelCase__							:				List[Any]          =      mask_feature_min_masks

       # ctc loss
       UpperCamelCase__							:				Optional[Any]          =      ctc_loss_reduction
       UpperCamelCase__							:				List[Any]          =      ctc_zero_infinity

       # adapter
       UpperCamelCase__							:				Any          =      add_adapter
       UpperCamelCase__							:				Dict          =      adapter_kernel_size
       UpperCamelCase__							:				List[Any]          =      adapter_stride
       UpperCamelCase__							:				Any          =      num_adapter_layers
       UpperCamelCase__							:				List[Any]          =      output_hidden_size or hidden_size

       # SequenceClassification-specific parameter. Feel free to ignore for other classes.
       UpperCamelCase__							:				List[Any]          =      classifier_proj_size

       # XVector-specific parameters. Feel free to ignore for other classes.
       UpperCamelCase__							:				int          =      list(__magic_name__							)
       UpperCamelCase__							:				Union[str, Any]          =      list(__magic_name__							)
       UpperCamelCase__							:				List[str]          =      list(__magic_name__							)
       UpperCamelCase__							:				List[str]          =      xvector_output_dim




   @property
   def       UpperCamelCase__  (    self							) ->      int:






       """simple docstring"""
       return math.prod(self.conv_stride							)








class     lowercase__       :

   '''simple docstring'''


   def __init__(    self,		__magic_name__ = "",		__magic_name__ = False							) ->      None:






       """simple docstring"""
       # Mapping from the first character of the prefix of the node
       UpperCamelCase__							:				dict[str, RadixNode]          =      {}

       # A node will be a leaf if the tree contains its word
       UpperCamelCase__							:				Optional[Any]          =      is_leaf

       UpperCamelCase__							:				List[str]          =      prefix




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      tuple[str, str, str]:






       """simple docstring"""
       UpperCamelCase__							:				Dict          =      0
       for q, w in zip(self.prefix,		__magic_name__							):
           if q != w:
               break

           x += 1

       return self.prefix[:x], self.prefix[x:], word[x:]




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      None:






       """simple docstring"""
       for word in words:
           self.insert(__magic_name__							)




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      None:






       """simple docstring"""
       # Case 1: If the word is the prefix of the node
       # Solution: We set the current node as leaf
       if self.prefix == word:
           UpperCamelCase__							:				Union[str, Any]          =      True

       # Case 2: The node has no edges that have a prefix to the word
       # Solution: We create an edge from the current node to a new one
       # containing the word
       elif word[0] not in self.nodes:
           UpperCamelCase__							:				Tuple          =      RadixNode(prefix=__magic_name__,		is_leaf=__magic_name__							)

       else:
           UpperCamelCase__							:				Any          =      self.nodes[word[0]]
           UpperCamelCase__   ,UpperCamelCase__   ,UpperCamelCase__							:				Union[str, Any]          =      incoming_node.match(
               __magic_name__							)

           # Case 3: The node prefix is equal to the matching
           # Solution: We insert remaining word on the next node
           if remaining_prefix == "":
               self.nodes[matching_string[0]].insert(__magic_name__							)

           # Case 4: The word is greater equal to the matching
           # Solution: Create a node in between both nodes, change
           # prefixes and add the new node for the remaining word
           else:
               UpperCamelCase__							:				Tuple          =      remaining_prefix

               UpperCamelCase__							:				Tuple          =      self.nodes[matching_string[0]]
               UpperCamelCase__							:				List[Any]          =      RadixNode(__magic_name__,		__magic_name__							)
               UpperCamelCase__							:				str          =      aux_node

               if remaining_word == "":
                   UpperCamelCase__							:				Any          =      True
               else:
                   self.nodes[matching_string[0]].insert(__magic_name__							)




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      bool:






       """simple docstring"""
       UpperCamelCase__							:				Optional[Any]          =      self.nodes.get(word[0],		__magic_name__							)
       if not incoming_node:
           return False
       else:
           UpperCamelCase__   ,UpperCamelCase__   ,UpperCamelCase__							:				Dict          =      incoming_node.match(
               __magic_name__							)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
               return False
           # This applies when the word and the prefix are equal
           elif remaining_word == "":
               return incoming_node.is_leaf
           # We have word remaining so we check the next node
           else:
               return incoming_node.find(__magic_name__							)




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      bool:






       """simple docstring"""
       UpperCamelCase__							:				Optional[Any]          =      self.nodes.get(word[0],		__magic_name__							)
       if not incoming_node:
           return False
       else:
           UpperCamelCase__   ,UpperCamelCase__   ,UpperCamelCase__							:				Union[str, Any]          =      incoming_node.match(
               __magic_name__							)
           # If there is remaining prefix, the word can't be on the tree
           if remaining_prefix != "":
               return False
           # We have word remaining so we check the next node
           elif remaining_word != "":
               return incoming_node.delete(__magic_name__							)
           else:
               # If it is not a leaf, we don't have to delete
               if not incoming_node.is_leaf:
                   return False
               else:
                   # We delete the nodes if no edges go from it
                   if len(incoming_node.nodes							) == 0:
                       del self.nodes[word[0]]
                       # We merge the current node with its only child
                       if len(self.nodes							) == 1 and not self.is_leaf:
                           UpperCamelCase__							:				Optional[Any]          =      list(self.nodes.values()							)[0]
                           UpperCamelCase__							:				Union[str, Any]          =      merging_node.is_leaf
                           self.prefix += merging_node.prefix
                           UpperCamelCase__							:				int          =      merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
                   elif len(incoming_node.nodes							) > 1:
                       UpperCamelCase__							:				Any          =      False
                   # If there is 1 edge, we merge it with its child
                   else:
                       UpperCamelCase__							:				Union[str, Any]          =      list(incoming_node.nodes.values()							)[0]
                       UpperCamelCase__							:				List[str]          =      merging_node.is_leaf
                       incoming_node.prefix += merging_node.prefix
                       UpperCamelCase__							:				int          =      merging_node.nodes

                   return True




   def       UpperCamelCase__  (    self,		__magic_name__ = 0							) ->      None:






       """simple docstring"""
       if self.prefix != "":
           print('''-''' * height,		self.prefix,		'''  (leaf)''' if self.is_leaf else ''''''							)

       for value in self.nodes.values():
           value.print_tree(height + 1							)




def 		lowerCAmelCase_    (  )      ->	bool:
    UpperCamelCase__							:				Optional[int]          =      '''banana bananas bandana band apple all beast'''.split()
    UpperCamelCase__							:				Optional[int]          =      RadixNode()
    root.insert_many(__UpperCAmelCase      )

    assert all(root.find(__UpperCAmelCase      ) for word in words      )
    assert not root.find('''bandanas'''      )
    assert not root.find('''apps'''      )
    root.delete('''all'''      )
    assert not root.find('''all'''      )
    root.delete('''banana'''      )
    assert not root.find('''banana'''      )
    assert root.find('''bananas'''      )

    return True




def 		lowerCAmelCase_    (  )      ->	None:
    assert test_trie()




def 		lowerCAmelCase_    (  )      ->	None:
    UpperCamelCase__							:				int          =      RadixNode()
    UpperCamelCase__							:				Any          =      '''banana bananas bandanas bandana band apple all beast'''.split()
    root.insert_many(__UpperCAmelCase      )

    print('''Words:'''		,   __UpperCAmelCase      )
    print('''Tree:'''      )
    root.print_tree()


if __name__ == "__main__":
  main()

