


"""simple docstring"""




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 lowerCAmelCase_						(			lowerCamelCase__	):

 '''simple docstring'''

 __snake_case												=  "data2vec-audio"



 def __init__(     self		,				_UpperCAmelCase=32		,				_UpperCAmelCase=7_68		,				_UpperCAmelCase=12		,				_UpperCAmelCase=12		,				_UpperCAmelCase=30_72		,				_UpperCAmelCase="gelu"		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=0.0		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=0.1		,				_UpperCAmelCase=0.02		,				_UpperCAmelCase=1E-5		,				_UpperCAmelCase="gelu"		,				_UpperCAmelCase=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)		,				_UpperCAmelCase=(5, 2, 2, 2, 2, 2, 2)		,				_UpperCAmelCase=(10, 3, 3, 3, 3, 2, 2)		,				_UpperCAmelCase=False		,				_UpperCAmelCase=16		,				_UpperCAmelCase=19		,				_UpperCAmelCase=5		,				_UpperCAmelCase=0.05		,				_UpperCAmelCase=10		,				_UpperCAmelCase=2		,				_UpperCAmelCase=0.0		,				_UpperCAmelCase=10		,				_UpperCAmelCase=0		,				_UpperCAmelCase="sum"		,				_UpperCAmelCase=False		,				_UpperCAmelCase=False		,				_UpperCAmelCase=2_56		,				_UpperCAmelCase=(5_12, 5_12, 5_12, 5_12, 15_00)		,				_UpperCAmelCase=(5, 3, 3, 1, 1)		,				_UpperCAmelCase=(1, 2, 3, 1, 1)		,				_UpperCAmelCase=5_12		,				_UpperCAmelCase=0		,				_UpperCAmelCase=1		,				_UpperCAmelCase=2		,				_UpperCAmelCase=False		,				_UpperCAmelCase=3		,				_UpperCAmelCase=2		,				_UpperCAmelCase=3		,				_UpperCAmelCase=None		,				**_UpperCAmelCase		,				):
       super().__init__(**_UpperCAmelCase		,				pad_token_id=_UpperCAmelCase		,				bos_token_id=_UpperCAmelCase		,				eos_token_id=_UpperCAmelCase )
       snake_case_	=				hidden_size
       snake_case_	=				feat_extract_activation
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				conv_bias
       snake_case_	=				num_conv_pos_embeddings
       snake_case_	=				num_conv_pos_embedding_groups
       snake_case_	=				conv_pos_kernel_size
       snake_case_	=				len(self.conv_dim )
       snake_case_	=				num_hidden_layers
       snake_case_	=				intermediate_size
       snake_case_	=				hidden_act
       snake_case_	=				num_attention_heads
       snake_case_	=				hidden_dropout
       snake_case_	=				attention_dropout
       snake_case_	=				activation_dropout
       snake_case_	=				feat_proj_dropout
       snake_case_	=				final_dropout
       snake_case_	=				layerdrop
       snake_case_	=				layer_norm_eps
       snake_case_	=				initializer_range
       snake_case_	=				vocab_size
       snake_case_	=				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
       snake_case_	=				mask_time_prob
       snake_case_	=				mask_time_length
       snake_case_	=				mask_time_min_masks
       snake_case_	=				mask_feature_prob
       snake_case_	=				mask_feature_length
       snake_case_	=				mask_feature_min_masks

       # ctc loss
       snake_case_	=				ctc_loss_reduction
       snake_case_	=				ctc_zero_infinity

       # adapter
       snake_case_	=				add_adapter
       snake_case_	=				adapter_kernel_size
       snake_case_	=				adapter_stride
       snake_case_	=				num_adapter_layers
       snake_case_	=				output_hidden_size or hidden_size

       # SequenceClassification-specific parameter. Feel free to ignore for other classes.
       snake_case_	=				classifier_proj_size

       # XVector-specific parameters. Feel free to ignore for other classes.
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				list(_UpperCAmelCase )
       snake_case_	=				xvector_output_dim





 @property
 def 						UpperCamelCase__					(     self ):
       return math.prod(self.conv_stride )



from __future__ import annotations

import time

UpperCAmelCase      =   list[tuple[int, int]]

UpperCAmelCase      =   [
    [0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 1, 0, 0, 0, 0],
    [1, 0, 1, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 1, 0, 0],
]

UpperCAmelCase      =   [[-1, 0], [0, -1], [1, 0], [0, 1]]  # up, left, down, right







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				pos_x
       snake_case_	=				pos_y
       snake_case_	=				(pos_y, pos_x)
       snake_case_	=				goal_x
       snake_case_	=				goal_y
       snake_case_	=				parent







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				Node(start[1]		,				start[0]		,				goal[1]		,				goal[0]		,				_UpperCAmelCase )
       snake_case_	=				Node(goal[1]		,				goal[0]		,				goal[1]		,				goal[0]		,				_UpperCAmelCase )

       snake_case_	=				[self.start]
       snake_case_	=				False



 def 						UpperCamelCase__					(     self ):
       while self.node_queue:
             snake_case_	=				self.node_queue.pop(0 )

             if current_node.pos == self.target.pos:
                   snake_case_	=				True
                   return self.retrace_path(_UpperCAmelCase )

             snake_case_	=				self.get_successors(_UpperCAmelCase )

             for node in successors:
                   self.node_queue.append(_UpperCAmelCase )

       if not self.reached:
             return [self.start.pos]
       return None



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       snake_case_	=				[]
       for action in delta:
             snake_case_	=				parent.pos_x + action[1]
             snake_case_	=				parent.pos_y + action[0]
             if not (0 <= pos_x <= len(grid[0] ) - 1 and 0 <= pos_y <= len(_UpperCAmelCase ) - 1):
                   continue

             if grid[pos_y][pos_x] != 0:
                   continue

             successors.append(
                 Node(_UpperCAmelCase		,				_UpperCAmelCase		,				self.target.pos_y		,				self.target.pos_x		,				_UpperCAmelCase ) )
       return successors





 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       snake_case_	=				node
       snake_case_	=				[]
       while current_node is not None:
             path.append((current_node.pos_y, current_node.pos_x) )
             snake_case_	=				current_node.parent
       path.reverse()
       return path







class lowerCAmelCase_						:

 '''simple docstring'''

 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				BreadthFirstSearch(_UpperCAmelCase		,				_UpperCAmelCase )
       snake_case_	=				BreadthFirstSearch(_UpperCAmelCase		,				_UpperCAmelCase )
       snake_case_	=				False



 def 						UpperCamelCase__					(     self ):
       while self.fwd_bfs.node_queue or self.bwd_bfs.node_queue:
             snake_case_	=				self.fwd_bfs.node_queue.pop(0 )
             snake_case_	=				self.bwd_bfs.node_queue.pop(0 )

             if current_bwd_node.pos == current_fwd_node.pos:
                   snake_case_	=				True
                   return self.retrace_bidirectional_path(
                       _UpperCAmelCase		,				_UpperCAmelCase )

             snake_case_	=				current_bwd_node
             snake_case_	=				current_fwd_node

             snake_case_	=				{
                 self.fwd_bfs: self.fwd_bfs.get_successors(_UpperCAmelCase ),
                 self.bwd_bfs: self.bwd_bfs.get_successors(_UpperCAmelCase ),
             }

             for bfs in [self.fwd_bfs, self.bwd_bfs]:
                   for node in successors[bfs]:
                         bfs.node_queue.append(_UpperCAmelCase )

       if not self.reached:
             return [self.fwd_bfs.start.pos]
       return None





 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase ):
       snake_case_	=				self.fwd_bfs.retrace_path(_UpperCAmelCase )
       snake_case_	=				self.bwd_bfs.retrace_path(_UpperCAmelCase )
       bwd_path.pop()
       bwd_path.reverse()
       snake_case_	=				fwd_path + bwd_path
       return path


if __name__ == "__main__":
   # all coordinates are given in format [y,x]
   import doctest

   doctest.testmod()
   UpperCAmelCase      =   (0, 0)
   UpperCAmelCase      =   (len(grid) - 1, len(grid[0]) - 1)
   for elem in grid:
      print(elem)

   UpperCAmelCase      =   time.time()
   UpperCAmelCase      =   BreadthFirstSearch(init, goal)
   UpperCAmelCase      =   bfs.search()
   UpperCAmelCase      =   time.time() - start_bfs_time

   print("""Unidirectional BFS computation time : """, bfs_time)

   UpperCAmelCase      =   time.time()
   UpperCAmelCase      =   BidirectionalBreadthFirstSearch(init, goal)
   UpperCAmelCase      =   bd_bfs.search()
   UpperCAmelCase      =   time.time() - start_bd_bfs_time

   print("""Bidirectional BFS computation time : """, bd_bfs_time)