






"""simple docstring"""



import functools
import operator

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


_lowerCAmelCase	:	str				=      logging.get_logger(__name__)

_lowerCAmelCase	:	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 			lowerCAmelCase__			(    __magic_name__   ):
   SCREAMING_SNAKE_CASE_    ='''sew-d'''
   def __init__(		self      :	Optional[int]							,			snake_case__      :	Dict=3_2							,			snake_case__      :	Tuple=7_6_8							,			snake_case__      :	Dict=1_2							,			snake_case__      :	Tuple=1_2							,			snake_case__      :	Union[str, Any]=3_0_7_2							,			snake_case__      :	Any=2							,			snake_case__      :	List[Any]=5_1_2							,			snake_case__      :	Any=2_5_6							,			snake_case__      :	Optional[Any]=True							,			snake_case__      :	Dict=True							,			snake_case__      :	Optional[int]=("p2c", "c2p")							,			snake_case__      :	Tuple="layer_norm"							,			snake_case__      :	Dict="gelu_python"							,			snake_case__      :	List[str]=0.1							,			snake_case__      :	Any=0.1							,			snake_case__      :	Optional[Any]=0.1							,			snake_case__      :	str=0.0							,			snake_case__      :	Optional[int]=0.1							,			snake_case__      :	Union[str, Any]=0.02							,			snake_case__      :	Dict=1e-7							,			snake_case__      :	Optional[int]=1e-5							,			snake_case__      :	List[str]="group"							,			snake_case__      :	str="gelu"							,			snake_case__      :	Tuple=(6_4, 1_2_8, 1_2_8, 1_2_8, 1_2_8, 2_5_6, 2_5_6, 2_5_6, 2_5_6, 5_1_2, 5_1_2, 5_1_2, 5_1_2)							,			snake_case__      :	Tuple=(5, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1)							,			snake_case__      :	str=(1_0, 3, 1, 3, 1, 3, 1, 3, 1, 2, 1, 2, 1)							,			snake_case__      :	Any=False							,			snake_case__      :	List[Any]=1_2_8							,			snake_case__      :	List[Any]=1_6							,			snake_case__      :	Optional[Any]=True							,			snake_case__      :	Dict=0.05							,			snake_case__      :	int=1_0							,			snake_case__      :	Dict=2							,			snake_case__      :	Union[str, Any]=0.0							,			snake_case__      :	Optional[int]=1_0							,			snake_case__      :	List[Any]=0							,			snake_case__      :	str="mean"							,			snake_case__      :	int=False							,			snake_case__      :	Tuple=False							,			snake_case__      :	List[str]=2_5_6							,			snake_case__      :	Dict=0							,			snake_case__      :	List[Any]=1							,			snake_case__      :	Optional[int]=2							,			**snake_case__      :	Union[str, Any]							,			):


        '''simple docstring'''
        super().__init__(**snake_case__							,			pad_token_id=snake_case__							,			bos_token_id=snake_case__							,			eos_token_id=snake_case__							)
        UpperCAmelCase__						:    List[Any]							=							hidden_size
        UpperCAmelCase__						:    int							=							feat_extract_norm
        UpperCAmelCase__						:    Dict							=							feat_extract_activation
        UpperCAmelCase__						:    Union[str, Any]							=							list(snake_case__							)
        UpperCAmelCase__						:    Dict							=							list(snake_case__							)
        UpperCAmelCase__						:    Any							=							list(snake_case__							)
        UpperCAmelCase__						:    Optional[Any]							=							conv_bias
        UpperCAmelCase__						:    int							=							num_conv_pos_embeddings
        UpperCAmelCase__						:    Tuple							=							num_conv_pos_embedding_groups
        UpperCAmelCase__						:    List[Any]							=							len(self.conv_dim							)
        UpperCAmelCase__						:    List[str]							=							num_hidden_layers
        UpperCAmelCase__						:    Union[str, Any]							=							intermediate_size
        UpperCAmelCase__						:    List[str]							=							squeeze_factor
        UpperCAmelCase__						:    Dict							=							max_position_embeddings
        UpperCAmelCase__						:    str							=							position_buckets
        UpperCAmelCase__						:    Any							=							share_att_key
        UpperCAmelCase__						:    List[str]							=							relative_attention
        UpperCAmelCase__						:    Any							=							norm_rel_ebd
        UpperCAmelCase__						:    int							=							list(snake_case__							)
        UpperCAmelCase__						:    int							=							hidden_act
        UpperCAmelCase__						:    List[str]							=							num_attention_heads
        UpperCAmelCase__						:    int							=							hidden_dropout
        UpperCAmelCase__						:    Any							=							attention_dropout
        UpperCAmelCase__						:    List[str]							=							activation_dropout
        UpperCAmelCase__						:    Any							=							feat_proj_dropout
        UpperCAmelCase__						:    List[Any]							=							final_dropout
        UpperCAmelCase__						:    Any							=							layer_norm_eps
        UpperCAmelCase__						:    List[Any]							=							feature_layer_norm_eps
        UpperCAmelCase__						:    List[Any]							=							initializer_range
        UpperCAmelCase__						:    Tuple							=							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
        UpperCAmelCase__						:    List[Any]							=							apply_spec_augment
        UpperCAmelCase__						:    Union[str, Any]							=							mask_time_prob
        UpperCAmelCase__						:    Optional[int]							=							mask_time_length
        UpperCAmelCase__						:    List[str]							=							mask_time_min_masks
        UpperCAmelCase__						:    Optional[Any]							=							mask_feature_prob
        UpperCAmelCase__						:    Dict							=							mask_feature_length
        UpperCAmelCase__						:    Tuple							=							mask_feature_min_masks

        # ctc loss
        UpperCAmelCase__						:    List[Any]							=							ctc_loss_reduction
        UpperCAmelCase__						:    Tuple							=							ctc_zero_infinity

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




   @property
   def       __a							(		self      :	Optional[int]							):


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










"""simple docstring"""



from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class 			lowerCAmelCase__			:
   def __init__(		self      :	Any							,			snake_case__      :	Any							):


        '''simple docstring'''
        UpperCAmelCase__						:    Any							=							data
        UpperCAmelCase__						:    Node | None							=							None




class 			lowerCAmelCase__			:
   def __init__(		self      :	Dict							):


        '''simple docstring'''
        UpperCAmelCase__						:    Tuple							=							None
        UpperCAmelCase__						:    Optional[int]							=							None
   def __iter__(		self      :	Tuple							):


        '''simple docstring'''
        UpperCAmelCase__						:    Optional[int]							=							self.head
        while self.head:
             yield node.data
             UpperCAmelCase__						:    Optional[Any]							=							node.next
             if node == self.head:
                  break
   def __len__(		self      :	Tuple							):


        '''simple docstring'''
        return sum(1 for _ in self							)
   def __repr__(		self      :	str							):


        '''simple docstring'''
        return "->".join(str(snake_case__							) for item in iter(self							)							)
   def       __a							(		self      :	Optional[Any]							,			snake_case__      :	Any							):


        '''simple docstring'''
        self.insert_nth(len(self							)							,			snake_case__							)
   def       __a							(		self      :	Optional[Any]							,			snake_case__      :	Any							):


        '''simple docstring'''
        self.insert_nth(0							,			snake_case__							)
   def       __a							(		self      :	Any							,			snake_case__      :	int							,			snake_case__      :	Any							):


        '''simple docstring'''
        if index < 0 or index > len(self							):
             raise IndexError("list index out of range."							)
        UpperCAmelCase__						:    Any							=							Node(snake_case__							)
        if self.head is None:
             UpperCAmelCase__						:    Union[str, Any]							=							new_node  # first node points itself
             UpperCAmelCase__						:    List[str]							=							new_node
        elif index == 0:  # insert at head
             UpperCAmelCase__						:    Optional[Any]							=							self.head
             UpperCAmelCase__						:    List[Any]							=							new_node
        else:
             UpperCAmelCase__						:    Union[str, Any]							=							self.head
             for _ in range(index - 1							):
                  UpperCAmelCase__						:    Dict							=							temp.next
             UpperCAmelCase__						:    Tuple							=							temp.next
             UpperCAmelCase__						:    str							=							new_node
             if index == len(self							) - 1:  # insert at tail
                  UpperCAmelCase__						:    Union[str, Any]							=							new_node
   def       __a							(		self      :	List[Any]							):


        '''simple docstring'''
        return self.delete_nth(0							)
   def       __a							(		self      :	Optional[Any]							):


        '''simple docstring'''
        return self.delete_nth(len(self							) - 1							)
   def       __a							(		self      :	Tuple							,			snake_case__      :	int = 0							):


        '''simple docstring'''
        if not 0 <= index < len(self							):
             raise IndexError("list index out of range."							)
        UpperCAmelCase__						:    Union[str, Any]							=							self.head
        if self.head == self.tail:  # just one node
             UpperCAmelCase__						:    str							=							None
        elif index == 0:  # delete head node
             UpperCAmelCase__						:    List[Any]							=							self.tail.next.next
             UpperCAmelCase__						:    Dict							=							self.head.next
        else:
             UpperCAmelCase__						:    List[Any]							=							self.head
             for _ in range(index - 1							):
                  UpperCAmelCase__						:    Tuple							=							temp.next
             UpperCAmelCase__						:    Dict							=							temp.next
             UpperCAmelCase__						:    Dict							=							temp.next.next
             if index == len(self							) - 1:  # delete at tail
                  UpperCAmelCase__						:    int							=							temp
        return delete_node.data




   def       __a							(		self      :	Any							):


        '''simple docstring'''
        return len(self							) == 0




def 	SCREAMING_SNAKE_CASE__       (  )->		None:






     '''simple docstring'''



     UpperCAmelCase__						:    str							=							CircularLinkedList()
     assert len(snake_case				) == 0
     assert circular_linked_list.is_empty() is True
     assert str(snake_case				) == ""

     try:
          circular_linked_list.delete_front()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_tail()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_nth(-1				)
          raise AssertionError
     except IndexError:
          assert True

     try:
          circular_linked_list.delete_nth(0				)
          raise AssertionError
     except IndexError:
          assert True

     assert circular_linked_list.is_empty() is True
     for i in range(5				):
          assert len(snake_case				) == i
          circular_linked_list.insert_nth(snake_case			,					i + 1				)
     assert str(snake_case				) == "->".join(str(snake_case				) for i in range(1			,					6				)				)

     circular_linked_list.insert_tail(6				)
     assert str(snake_case				) == "->".join(str(snake_case				) for i in range(1			,					7				)				)
     circular_linked_list.insert_head(0				)
     assert str(snake_case				) == "->".join(str(snake_case				) for i in range(0			,					7				)				)

     assert circular_linked_list.delete_front() == 0
     assert circular_linked_list.delete_tail() == 6
     assert str(snake_case				) == "->".join(str(snake_case				) for i in range(1			,					6				)				)
     assert circular_linked_list.delete_nth(2				) == 3

     circular_linked_list.insert_nth(2			,					3				)
     assert str(snake_case				) == "->".join(str(snake_case				) for i in range(1			,					6				)				)

     assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
 import doctest

 doctest.testmod()


