






"""simple docstring"""





import functools
import operator

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


_SCREAMING_SNAKE_CASE					:				Any					    =						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:				Optional[Any]					    =						{
    '''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json''',
    # See all SEW-D models at https://huggingface.co/models?filter=sew-d
}






class      a						(					__snake_case		):
    SCREAMING_SNAKE_CASE						:     str						= """sew-d"""






    def __init__(       self     :							Any       ,						__SCREAMING_SNAKE_CASE     :							str=32       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=768       ,						__SCREAMING_SNAKE_CASE     :							int=12       ,						__SCREAMING_SNAKE_CASE     :							Dict=12       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=3072       ,						__SCREAMING_SNAKE_CASE     :							Any=2       ,						__SCREAMING_SNAKE_CASE     :							List[str]=512       ,						__SCREAMING_SNAKE_CASE     :							str=256       ,						__SCREAMING_SNAKE_CASE     :							Dict=True       ,						__SCREAMING_SNAKE_CASE     :							Tuple=True       ,						__SCREAMING_SNAKE_CASE     :							int=("p2c", "c2p")       ,						__SCREAMING_SNAKE_CASE     :							Tuple="layer_norm"       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]="gelu_python"       ,						__SCREAMING_SNAKE_CASE     :							int=0.1       ,						__SCREAMING_SNAKE_CASE     :							str=0.1       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=0.1       ,						__SCREAMING_SNAKE_CASE     :							int=0.0       ,						__SCREAMING_SNAKE_CASE     :							str=0.1       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=0.02       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=1e-7       ,						__SCREAMING_SNAKE_CASE     :							str=1e-5       ,						__SCREAMING_SNAKE_CASE     :							List[str]="group"       ,						__SCREAMING_SNAKE_CASE     :							int="gelu"       ,						__SCREAMING_SNAKE_CASE     :							Any=(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     :							Union[str, Any]=(10, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)       ,						__SCREAMING_SNAKE_CASE     :							int=False       ,						__SCREAMING_SNAKE_CASE     :							Any=128       ,						__SCREAMING_SNAKE_CASE     :							List[Any]=16       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=True       ,						__SCREAMING_SNAKE_CASE     :							Any=0.05       ,						__SCREAMING_SNAKE_CASE     :							List[str]=10       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]=2       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]=0.0       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=10       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]=0       ,						__SCREAMING_SNAKE_CASE     :							Dict="mean"       ,						__SCREAMING_SNAKE_CASE     :							Optional[int]=False       ,						__SCREAMING_SNAKE_CASE     :							List[str]=False       ,						__SCREAMING_SNAKE_CASE     :							int=256       ,						__SCREAMING_SNAKE_CASE     :							str=0       ,						__SCREAMING_SNAKE_CASE     :							Tuple=1       ,						__SCREAMING_SNAKE_CASE     :							Any=2       ,						**__SCREAMING_SNAKE_CASE     :							Tuple       ,						)     ->		Union[str, Any]:
      super().__init__(**__SCREAMING_SNAKE_CASE       ,						pad_token_id=__SCREAMING_SNAKE_CASE       ,						bos_token_id=__SCREAMING_SNAKE_CASE       ,						eos_token_id=__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						hidden_size
      lowerCamelCase_         =						feat_extract_norm
      lowerCamelCase_         =						feat_extract_activation
      lowerCamelCase_         =						list(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						list(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						list(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						conv_bias
      lowerCamelCase_         =						num_conv_pos_embeddings
      lowerCamelCase_         =						num_conv_pos_embedding_groups
      lowerCamelCase_         =						len(self.conv_dim					)
      lowerCamelCase_         =						num_hidden_layers
      lowerCamelCase_         =						intermediate_size
      lowerCamelCase_         =						squeeze_factor
      lowerCamelCase_         =						max_position_embeddings
      lowerCamelCase_         =						position_buckets
      lowerCamelCase_         =						share_att_key
      lowerCamelCase_         =						relative_attention
      lowerCamelCase_         =						norm_rel_ebd
      lowerCamelCase_         =						list(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						hidden_act
      lowerCamelCase_         =						num_attention_heads
      lowerCamelCase_         =						hidden_dropout
      lowerCamelCase_         =						attention_dropout
      lowerCamelCase_         =						activation_dropout
      lowerCamelCase_         =						feat_proj_dropout
      lowerCamelCase_         =						final_dropout
      lowerCamelCase_         =						layer_norm_eps
      lowerCamelCase_         =						feature_layer_norm_eps
      lowerCamelCase_         =						initializer_range
      lowerCamelCase_         =						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_         =						apply_spec_augment
      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

      # sequence classification
      lowerCamelCase_         =						use_weighted_layer_sum
      lowerCamelCase_         =						classifier_proj_size






    @property
    def    UpperCamelCase       (       self     :							Optional[int]					)     ->		Optional[Any]:
      return functools.reduce(operator.mul       ,						self.conv_stride       ,						1					)












"""simple docstring"""





from __future__ import annotations

from typing import Generic, TypeVar

_SCREAMING_SNAKE_CASE					:				Optional[Any]					    =						TypeVar('''T''')






class      a						(					Generic[T]		):






    def __init__(       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							T					)     ->		None:
      lowerCamelCase_         =						data
      lowerCamelCase_         =						self
      lowerCamelCase_         =						0






class      a						(					Generic[T]		):






    def __init__(       self     :							Any					)     ->		None:
      # map from node name to the node object
      lowerCamelCase_         =						{}






    def    UpperCamelCase       (       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							T					)     ->		None:
      # create a new set with x as its member
      lowerCamelCase_         =						DisjointSetTreeNode(__SCREAMING_SNAKE_CASE					)






    def    UpperCamelCase       (       self     :							Optional[int]       ,						__SCREAMING_SNAKE_CASE     :							T					)     ->		DisjointSetTreeNode[T]:
      # find the set x belongs to (with path-compression)
      lowerCamelCase_         =						self.map[data]
      if elem_ref != elem_ref.parent:
        lowerCamelCase_         =						self.find_set(elem_ref.parent.data					)
      return elem_ref.parent






    def    UpperCamelCase       (       self     :							str       ,						__SCREAMING_SNAKE_CASE     :							DisjointSetTreeNode[T]       ,						__SCREAMING_SNAKE_CASE     :							DisjointSetTreeNode[T]					)     ->		None:
      # helper function for union operation
      if nodea.rank > nodea.rank:
        lowerCamelCase_         =						nodea
      else:
        lowerCamelCase_         =						nodea
        if nodea.rank == nodea.rank:
          nodea.rank += 1






    def    UpperCamelCase       (       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							T       ,						__SCREAMING_SNAKE_CASE     :							T					)     ->		None:
      # merge 2 disjoint sets
      self.link(self.find_set(__SCREAMING_SNAKE_CASE					)       ,						self.find_set(__SCREAMING_SNAKE_CASE					)					)






class      a						(					Generic[T]		):






    def __init__(       self     :							Optional[int]					)     ->		None:
      # connections: map from the node to the neighbouring nodes (with weights)
      lowerCamelCase_         =						{}






    def    UpperCamelCase       (       self     :							Optional[int]       ,						__SCREAMING_SNAKE_CASE     :							T					)     ->		None:
      # add a node ONLY if its not present in the graph
      if node not in self.connections:
        lowerCamelCase_         =						{}






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							T       ,						__SCREAMING_SNAKE_CASE     :							T       ,						__SCREAMING_SNAKE_CASE     :							int					)     ->		None:
      # add an edge with the given weight
      self.add_node(__SCREAMING_SNAKE_CASE					)
      self.add_node(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						weight
      lowerCamelCase_         =						weight






    def    UpperCamelCase       (       self     :							List[Any]					)     ->		GraphUndirectedWeighted[T]:
      lowerCamelCase_         =						[]
      lowerCamelCase_         =						set()
      for start in self.connections:
        for end in self.connections[start]:
          if (start, end) not in seen:
            seen.add((end, start)					)
            edges.append((start, end, self.connections[start][end])					)
      edges.sort(key=lambda __SCREAMING_SNAKE_CASE					: x[2]					)

      # creating the disjoint set
      lowerCamelCase_         =						DisjointSetTree[T]()
      for node in self.connections:
        disjoint_set.make_set(__SCREAMING_SNAKE_CASE					)

      # MST generation
      lowerCamelCase_         =						0
      lowerCamelCase_         =						0
      lowerCamelCase_         =						GraphUndirectedWeighted[T]()
      while num_edges < len(self.connections					) - 1:
        lowerCamelCase_     ,	lowerCamelCase_     ,	lowerCamelCase_         =						edges[index]
        index += 1
        lowerCamelCase_         =						disjoint_set.find_set(__SCREAMING_SNAKE_CASE					)
        lowerCamelCase_         =						disjoint_set.find_set(__SCREAMING_SNAKE_CASE					)
        if parent_u != parent_v:
          num_edges += 1
          graph.add_edge(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)
          disjoint_set.union(__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE					)
      return graph




