






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__							  =						logging.get_logger(__name__)

UpperCAmelCase__							  =						{
    "facebook/xmod-base": "https://huggingface.co/facebook/xmod-base/resolve/main/config.json",
    "facebook/xmod-large-prenorm": "https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json",
    "facebook/xmod-base-13-125k": "https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json",
    "facebook/xmod-base-30-125k": "https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json",
    "facebook/xmod-base-30-195k": "https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json",
    "facebook/xmod-base-60-125k": "https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json",
    "facebook/xmod-base-60-265k": "https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json",
    "facebook/xmod-base-75-125k": "https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json",
    "facebook/xmod-base-75-269k": "https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json",
}






class 						lowercase_   (      lowercase  ):






      '''simple docstring'''




      __snake_case	    =    '''xmod'''







      def __init__( self :		Tuple					,   __UpperCAmelCase :		str=30_522					,   __UpperCAmelCase :		Tuple=768					,   __UpperCAmelCase :		int=12					,   __UpperCAmelCase :		Tuple=12					,   __UpperCAmelCase :		Tuple=3_072					,   __UpperCAmelCase :		Union[str, Any]="gelu"					,   __UpperCAmelCase :		Tuple=0.1					,   __UpperCAmelCase :		Tuple=0.1					,   __UpperCAmelCase :		Tuple=512					,   __UpperCAmelCase :		Optional[Any]=2					,   __UpperCAmelCase :		List[str]=0.02					,   __UpperCAmelCase :		str=1e-1_2					,   __UpperCAmelCase :		Tuple=1					,   __UpperCAmelCase :		List[str]=0					,   __UpperCAmelCase :		List[str]=2					,   __UpperCAmelCase :		int="absolute"					,   __UpperCAmelCase :		Tuple=True					,   __UpperCAmelCase :		str=None					,   __UpperCAmelCase :		Optional[Any]=False					,   __UpperCAmelCase :		Optional[int]=2					,   __UpperCAmelCase :		Tuple=False					,   __UpperCAmelCase :		Union[str, Any]=True					,   __UpperCAmelCase :		Tuple=True					,   __UpperCAmelCase :		Any=("en_XX",)					,   __UpperCAmelCase :		Union[str, Any]=None					,   **__UpperCAmelCase :		Union[str, Any]					,   )       ->Optional[int]:




       """simple docstring"""


       super().__init__(pad_token_id=__UpperCAmelCase					,   bos_token_id=__UpperCAmelCase					,   eos_token_id=__UpperCAmelCase					,   **__UpperCAmelCase    )

       a						    = vocab_size
       a						    = hidden_size
       a						    = num_hidden_layers
       a						    = num_attention_heads
       a						    = hidden_act
       a						    = intermediate_size
       a						    = hidden_dropout_prob
       a						    = attention_probs_dropout_prob
       a						    = max_position_embeddings
       a						    = type_vocab_size
       a						    = initializer_range
       a						    = layer_norm_eps
       a						    = position_embedding_type
       a						    = use_cache
       a						    = classifier_dropout
       a						    = pre_norm
       a						    = adapter_reduction_factor
       a						    = adapter_layer_norm
       a						    = adapter_reuse_layer_norm
       a						    = ln_before_adapter
       a						    = list(__UpperCAmelCase    )
       a						    = default_language






class 						lowercase_   (      lowercase  ):






      '''simple docstring'''




      @property
      def  __lowerCAmelCase   ( self :		Any    )       ->Mapping[str, Mapping[int, str]]:




       """simple docstring"""


       if self.task == "multiple-choice":
        a						    = {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
       else:
        a						    = {0: '''batch''', 1: '''sequence'''}
       return OrderedDict(
           [
               ('''input_ids''', dynamic_axis),
               ('''attention_mask''', dynamic_axis),
           ]    )










from __future__ import annotations

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 						lowercase_   :






      '''simple docstring'''




      def __init__( self :		Dict					,   __UpperCAmelCase :		int					,   __UpperCAmelCase :		int					,   __UpperCAmelCase :		int					,   __UpperCAmelCase :		int					,   __UpperCAmelCase :		float					,   __UpperCAmelCase :		Node | None					,   )       ->int:




       """simple docstring"""


       a						    = pos_x
       a						    = pos_y
       a						    = (pos_y, pos_x)
       a						    = goal_x
       a						    = goal_y
       a						    = g_cost
       a						    = parent
       a						    = self.calculate_heuristic()







      def  __lowerCAmelCase   ( self :		Any    )       ->float:




       """simple docstring"""


       a						    = abs(self.pos_x - self.goal_x    )
       a						    = abs(self.pos_y - self.goal_y    )
       return dx + dy







      def __lt__( self :		Any					,   __UpperCAmelCase :		Tuple    )       ->bool:




       """simple docstring"""


       return self.f_cost < other.f_cost






class 						lowercase_   :






      '''simple docstring'''




      def __init__( self :		Optional[Any]					,   __UpperCAmelCase :		tuple[int, int]					,   __UpperCAmelCase :		tuple[int, int]    )       ->Dict:




       """simple docstring"""


       a						    = Node(start[1]					,   start[0]					,   goal[1]					,   goal[0]					,   0					,   __UpperCAmelCase    )
       a						    = Node(goal[1]					,   goal[0]					,   goal[1]					,   goal[0]					,   99_999					,   __UpperCAmelCase    )

       a						    = [self.start]
       a						    = []

       a						    = False







      def  __lowerCAmelCase   ( self :		str    )       ->Path | None:




       """simple docstring"""


       while self.open_nodes:
        # Open Nodes are sorted using __lt__
        self.open_nodes.sort()
        a						    = self.open_nodes.pop(0    )

        if current_node.pos == self.target.pos:
         a						    = True
         return self.retrace_path(__UpperCAmelCase    )

        self.closed_nodes.append(__UpperCAmelCase    )
        a						    = self.get_successors(__UpperCAmelCase    )

        for child_node in successors:
         if child_node in self.closed_nodes:
          continue

         if child_node not in self.open_nodes:
          self.open_nodes.append(__UpperCAmelCase    )
         else:
          # retrieve the best current path
          a						    = self.open_nodes.pop(self.open_nodes.index(__UpperCAmelCase    )    )

          if child_node.g_cost < better_node.g_cost:
           self.open_nodes.append(__UpperCAmelCase    )
          else:
           self.open_nodes.append(__UpperCAmelCase    )

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







      def  __lowerCAmelCase   ( self :		Dict					,   __UpperCAmelCase :		Node    )       ->list[Node]:




       """simple docstring"""


       a						    = []
       for action in delta:
        a						    = parent.pos_x + action[1]
        a						    = 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					,   parent.g_cost + 1					,   __UpperCAmelCase					,   )    )
       return successors







      def  __lowerCAmelCase   ( self :		Optional[Any]					,   __UpperCAmelCase :		Node | None    )       ->Path:




       """simple docstring"""


       a						    = node
       a						    = []
       while current_node is not None:
        path.append((current_node.pos_y, current_node.pos_x)    )
        a						    = current_node.parent
       path.reverse()
       return path


if __name__ == "__main__":
     UpperCAmelCase__							  =						(0, 0)
     UpperCAmelCase__							  =						(len(grid) - 1, len(grid[0]) - 1)
     for elem in grid:
          print(elem)

     print("------")

     UpperCAmelCase__							  =						GreedyBestFirst(init, goal)
     UpperCAmelCase__							  =						greedy_bf.search()
     if path:
          for pos_x, pos_y in path:
               UpperCAmelCase__							  =						2

          for elem in grid:
               print(elem)


