





'''simple docstring'''

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


a   	=    logging.get_logger(__name__)

a   	=    {
    "facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json",
}







class __a			( _snake_case      ):
   __UpperCamelCase :			List[Any]						   =						'nllb-moe'
   __UpperCamelCase :			Dict						   =						['past_key_values']
   __UpperCamelCase :			Union[str, Any]						   =						{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}





   def __init__(       self					:      str					,lowerCamelCase					:      Optional[Any]=12_8112					,lowerCamelCase					:      List[str]=1024					,lowerCamelCase					:      Any=12					,lowerCamelCase					:      str=4096					,lowerCamelCase					:      Optional[Any]=16					,lowerCamelCase					:      Optional[Any]=12					,lowerCamelCase					:      int=4096					,lowerCamelCase					:      Tuple=16					,lowerCamelCase					:      str=0.05					,lowerCamelCase					:      Union[str, Any]=0.05					,lowerCamelCase					:      Union[str, Any]=True					,lowerCamelCase					:      Optional[Any]=True					,lowerCamelCase					:      List[str]="relu"					,lowerCamelCase					:      int=1024					,lowerCamelCase					:      List[Any]=0.1					,lowerCamelCase					:      str=0.1					,lowerCamelCase					:      Union[str, Any]=0.0					,lowerCamelCase					:      Tuple=0.02					,lowerCamelCase					:      Tuple=2					,lowerCamelCase					:      Union[str, Any]=True					,lowerCamelCase					:      Optional[Any]=False					,lowerCamelCase					:      Union[str, Any]="float32"					,lowerCamelCase					:      List[str]=False					,lowerCamelCase					:      int=128					,lowerCamelCase					:      List[Any]=64					,lowerCamelCase					:      List[str]=4					,lowerCamelCase					:      Dict=4					,lowerCamelCase					:      List[str]=0.001					,lowerCamelCase					:      str=0.001					,lowerCamelCase					:      Any="all"					,lowerCamelCase					:      Dict=False					,lowerCamelCase					:      Union[str, Any]=False					,lowerCamelCase					:      Tuple=1.0					,lowerCamelCase					:      Tuple=0.2					,lowerCamelCase					:      str=1					,lowerCamelCase					:      Dict=0					,lowerCamelCase					:      Optional[int]=2					,lowerCamelCase					:      Dict=False					,**lowerCamelCase					:      int					,):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							vocab_size
      __SCREAMING_SNAKE_CASE   				=							max_position_embeddings
      __SCREAMING_SNAKE_CASE   				=							d_model
      __SCREAMING_SNAKE_CASE   				=							encoder_ffn_dim
      __SCREAMING_SNAKE_CASE   				=							encoder_layers
      __SCREAMING_SNAKE_CASE   				=							encoder_attention_heads
      __SCREAMING_SNAKE_CASE   				=							decoder_ffn_dim
      __SCREAMING_SNAKE_CASE   				=							decoder_layers
      __SCREAMING_SNAKE_CASE   				=							decoder_attention_heads
      __SCREAMING_SNAKE_CASE   				=							dropout
      __SCREAMING_SNAKE_CASE   				=							attention_dropout
      __SCREAMING_SNAKE_CASE   				=							activation_dropout
      __SCREAMING_SNAKE_CASE   				=							activation_function
      __SCREAMING_SNAKE_CASE   				=							init_std
      __SCREAMING_SNAKE_CASE   				=							encoder_layerdrop
      __SCREAMING_SNAKE_CASE   				=							decoder_layerdrop
      __SCREAMING_SNAKE_CASE   				=							use_cache
      __SCREAMING_SNAKE_CASE   				=							encoder_layers
      __SCREAMING_SNAKE_CASE   				=							scale_embedding  # scale factor will be sqrt(d_model) if True
      __SCREAMING_SNAKE_CASE   				=							router_z_loss_coef
      __SCREAMING_SNAKE_CASE   				=							router_aux_loss_coef
      __SCREAMING_SNAKE_CASE   				=							decoder_sparse_step
      __SCREAMING_SNAKE_CASE   				=							encoder_sparse_step
      __SCREAMING_SNAKE_CASE   				=							num_experts
      __SCREAMING_SNAKE_CASE   				=							expert_capacity
      __SCREAMING_SNAKE_CASE   				=							router_bias
      if router_dtype not in ["float32", "float16", "bfloat16"]:
         raise ValueError(f"""`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}"""     )
      __SCREAMING_SNAKE_CASE   				=							router_dtype

      __SCREAMING_SNAKE_CASE   				=							router_ignore_padding_tokens
      __SCREAMING_SNAKE_CASE   				=							batch_prioritized_routing
      __SCREAMING_SNAKE_CASE   				=							second_expert_policy
      __SCREAMING_SNAKE_CASE   				=							normalize_router_prob_before_dropping
      __SCREAMING_SNAKE_CASE   				=							moe_eval_capacity_token_fraction
      __SCREAMING_SNAKE_CASE   				=							moe_token_dropout
      __SCREAMING_SNAKE_CASE   				=							output_router_logits
      super().__init__(
          pad_token_id=lowerCamelCase					,bos_token_id=lowerCamelCase					,eos_token_id=lowerCamelCase					,is_encoder_decoder=lowerCamelCase					,decoder_start_token_id=lowerCamelCase					,**lowerCamelCase					,)












'''simple docstring'''

import numpy as np







class __a			:





   def __init__(       self					:      Optional[int]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							(0, 0)
      __SCREAMING_SNAKE_CASE   				=							None
      __SCREAMING_SNAKE_CASE   				=							0
      __SCREAMING_SNAKE_CASE   				=							0
      __SCREAMING_SNAKE_CASE   				=							0





   def __eq__(       self					:      int					,lowerCamelCase					:      List[str]     ):

      '''simple docstring'''

      return self.position == cell.position





   def   UpperCAmelCase__  (       self					:      Union[str, Any]     ):

      '''simple docstring'''

      print(self.position     )







class __a			:





   def __init__(       self					:      int					,lowerCamelCase					:      Optional[int]=(5, 5)     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							np.zeros(lowerCamelCase     )
      __SCREAMING_SNAKE_CASE   				=							world_size[0]
      __SCREAMING_SNAKE_CASE   				=							world_size[1]





   def   UpperCAmelCase__  (       self					:      Optional[int]     ):

      '''simple docstring'''

      print(self.w     )





   def   UpperCAmelCase__  (       self					:      List[str]					,lowerCamelCase					:      int     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							[
          (-1, -1),
          (-1, 0),
          (-1, 1),
          (0, -1),
          (0, 1),
          (1, -1),
          (1, 0),
          (1, 1),
      ]
      __SCREAMING_SNAKE_CASE   				=							cell.position[0]
      __SCREAMING_SNAKE_CASE   				=							cell.position[1]
      __SCREAMING_SNAKE_CASE   				=							[]
      for n in neughbour_cord:
         __SCREAMING_SNAKE_CASE   				=							current_x + n[0]
         __SCREAMING_SNAKE_CASE   				=							current_y + n[1]
         if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
            __SCREAMING_SNAKE_CASE   				=							Cell()
            __SCREAMING_SNAKE_CASE   				=							(x, y)
            __SCREAMING_SNAKE_CASE   				=							cell
            neighbours.append(lowerCamelCase     )
      return neighbours





def     __magic_name__							(				__UpperCAmelCase				,						__UpperCAmelCase				,						__UpperCAmelCase   )    ->       Any:

   '''simple docstring'''







   __SCREAMING_SNAKE_CASE   				=							[]
   __SCREAMING_SNAKE_CASE   				=							[]
   _open.append(__UpperCAmelCase   )

   while _open:
      __SCREAMING_SNAKE_CASE   				=							np.argmin([n.f for n in _open]   )
      __SCREAMING_SNAKE_CASE   				=							_open[min_f]
      _closed.append(_open.pop(__UpperCAmelCase   )   )
      if current == goal:
         break
      for n in world.get_neigbours(__UpperCAmelCase   ):
         for c in _closed:
            if c == n:
               continue
         __SCREAMING_SNAKE_CASE   				=							current.g + 1
         __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE   				=							n.position
         __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE   				=							goal.position
         __SCREAMING_SNAKE_CASE   				=							(ya - ya) ** 2 + (xa - xa) ** 2
         __SCREAMING_SNAKE_CASE   				=							n.h + n.g

         for c in _open:
            if c == n and c.f < n.f:
               continue
         _open.append(__UpperCAmelCase   )
   __SCREAMING_SNAKE_CASE   				=							[]
   while current.parent is not None:
      path.append(current.position   )
      __SCREAMING_SNAKE_CASE   				=							current.parent
   path.append(current.position   )
   return path[::-1]


if __name__ == "__main__":
    a   	=    Gridworld()
    # Start position and goal
    a   	=    Cell()
    a   	=    (0, 0)
    a   	=    Cell()
    a   	=    (4, 4)
    print(F'''path from {start.position} to {goal.position}''')
    a   	=    astar(world, start, goal)
    #   Just for visual reasons.
    for i in s:
        a   	=    1
    print(world.w)





