





from collections import OrderedDict
from typing import Mapping

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


_A   :       List[str]    					=    logging.get_logger(__name__)

_A   :       List[str]    					=    {
    'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/resolve/main/config.json',
    'xlm-mlm-ende-1024': 'https://huggingface.co/xlm-mlm-ende-1024/resolve/main/config.json',
    'xlm-mlm-enfr-1024': 'https://huggingface.co/xlm-mlm-enfr-1024/resolve/main/config.json',
    'xlm-mlm-enro-1024': 'https://huggingface.co/xlm-mlm-enro-1024/resolve/main/config.json',
    'xlm-mlm-tlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-tlm-xnli15-1024/resolve/main/config.json',
    'xlm-mlm-xnli15-1024': 'https://huggingface.co/xlm-mlm-xnli15-1024/resolve/main/config.json',
    'xlm-clm-enfr-1024': 'https://huggingface.co/xlm-clm-enfr-1024/resolve/main/config.json',
    'xlm-clm-ende-1024': 'https://huggingface.co/xlm-clm-ende-1024/resolve/main/config.json',
    'xlm-mlm-17-1280': 'https://huggingface.co/xlm-mlm-17-1280/resolve/main/config.json',
    'xlm-mlm-100-1280': 'https://huggingface.co/xlm-mlm-100-1280/resolve/main/config.json',
}


class   __SCREAMING_SNAKE_CASE     (					__snake_case   ):
       _UpperCAmelCase :    List[str]					       =       """xlm"""
       _UpperCAmelCase :    str					       =       {
           """hidden_size""": """emb_dim""",
           """num_attention_heads""": """n_heads""",
           """num_hidden_layers""": """n_layers""",
           """n_words""": """vocab_size""",  # For backward compatibility
       }







       def __init__( self	:      Any						,   A	:      List[str]=3_0_1_4_5						,   A	:      Optional[int]=2_0_4_8						,   A	:      str=1_2						,   A	:      int=1_6						,   A	:      List[str]=0.1						,   A	:      List[str]=0.1						,   A	:      Any=True						,   A	:      str=False						,   A	:      str=False						,   A	:      List[Any]=False						,   A	:      Any=1						,   A	:      List[Any]=True						,   A	:      Optional[Any]=5_1_2						,   A	:      Union[str, Any]=2_0_4_8**-0.5						,   A	:      int=1e-12						,   A	:      Union[str, Any]=0.02						,   A	:      Optional[Any]=0						,   A	:      List[Any]=1						,   A	:      Any=2						,   A	:      Optional[Any]=3						,   A	:      List[Any]=5						,   A	:      Union[str, Any]=True						,   A	:      Optional[Any]="first"						,   A	:      Union[str, Any]=True						,   A	:      Any=None						,   A	:      Dict=True						,   A	:      Union[str, Any]=0.1						,   A	:      Optional[Any]=5						,   A	:      Tuple=5						,   A	:      List[Any]=0						,   A	:      Union[str, Any]=0						,   A	:      List[Any]=2						,   A	:      Tuple=0						,   **A	:      str						,   )  ->Dict:
          lowerCamelCase__  :		str     =				vocab_size
          lowerCamelCase__  :		Dict     =				emb_dim
          lowerCamelCase__  :		int     =				n_layers
          lowerCamelCase__  :		Union[str, Any]     =				n_heads
          lowerCamelCase__  :		str     =				dropout
          lowerCamelCase__  :		str     =				attention_dropout
          lowerCamelCase__  :		int     =				gelu_activation
          lowerCamelCase__  :		int     =				sinusoidal_embeddings
          lowerCamelCase__  :		Optional[Any]     =				causal
          lowerCamelCase__  :		Optional[int]     =				asm
          lowerCamelCase__  :		int     =				n_langs
          lowerCamelCase__  :		Union[str, Any]     =				use_lang_emb
          lowerCamelCase__  :		List[str]     =				layer_norm_eps
          lowerCamelCase__  :		Optional[int]     =				bos_index
          lowerCamelCase__  :		Any     =				eos_index
          lowerCamelCase__  :		Tuple     =				pad_index
          lowerCamelCase__  :		List[str]     =				unk_index
          lowerCamelCase__  :		Union[str, Any]     =				mask_index
          lowerCamelCase__  :		Optional[Any]     =				is_encoder
          lowerCamelCase__  :		str     =				max_position_embeddings
          lowerCamelCase__  :		Dict     =				embed_init_std
          lowerCamelCase__  :		Optional[Any]     =				init_std
          lowerCamelCase__  :		List[Any]     =				summary_type
          lowerCamelCase__  :		Optional[int]     =				summary_use_proj
          lowerCamelCase__  :		Optional[Any]     =				summary_activation
          lowerCamelCase__  :		Optional[Any]     =				summary_proj_to_labels
          lowerCamelCase__  :		Dict     =				summary_first_dropout
          lowerCamelCase__  :		Any     =				start_n_top
          lowerCamelCase__  :		int     =				end_n_top
          lowerCamelCase__  :		List[Any]     =				mask_token_id
          lowerCamelCase__  :		Any     =				lang_id

          if "n_words" in kwargs:
             lowerCamelCase__  :		Union[str, Any]     =				kwargs["""n_words"""]

          super().__init__(pad_token_id=A						,   bos_token_id=A						,   **A     )


class   __SCREAMING_SNAKE_CASE     (					__snake_case   ):







       @property
       def 		__lowerCamelCase       ( self	:      Optional[int]     )  ->Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
             lowerCamelCase__  :		Union[str, Any]     =				{0: """batch""", 1: """choice""", 2: """sequence"""}
          else:
             lowerCamelCase__  :		Optional[int]     =				{0: """batch""", 1: """sequence"""}
          return OrderedDict(
              [
                  ('''input_ids''', dynamic_axis),
                  ('''attention_mask''', dynamic_axis),
                  ('''token_type_ids''', dynamic_axis),
              ]     )











"""simple docstring"""







import numpy as np


class      UpperCamelCase		:






						def __init__(		self  :List[Any]				)      ->Optional[Any]:
										lowercase    :      Dict       = (0, 0)
										lowercase    :      str       = None
										lowercase    :      Any       = 0
										lowercase    :      List[Any]       = 0
										lowercase    :      Union[str, Any]       = 0






						def __eq__(		self  :List[Any]			, __magic_name__  :Optional[Any]				)      ->Tuple:
										return self.position == cell.position






						def      __snake_case      (		self  :Any				)      ->List[Any]:
										print(self.position				)


class      UpperCamelCase		:






						def __init__(		self  :Any			, __magic_name__  :int=(5, 5)				)      ->Dict:
										lowercase    :      Tuple       = np.zeros(__magic_name__				)
										lowercase    :      List[str]       = world_size[0]
										lowercase    :      str       = world_size[1]






						def      __snake_case      (		self  :str				)      ->int:
										print(self.w				)






						def      __snake_case      (		self  :Any			, __magic_name__  :Any				)      ->Optional[int]:
										lowercase    :      Optional[Any]       = [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										lowercase    :      List[str]       = cell.position[0]
										lowercase    :      List[str]       = cell.position[1]
										lowercase    :      Optional[int]       = []
										for n in neughbour_cord:
														lowercase    :      List[Any]       = current_x + n[0]
														lowercase    :      List[Any]       = current_y + n[1]
														if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																		lowercase    :      Tuple       = Cell()
																		lowercase    :      Union[str, Any]       = (x, y)
																		lowercase    :      Dict       = cell
																		neighbours.append(__magic_name__				)
										return neighbours


def      UpperCamelCase       ( _A  ,				_A  ,				_A )     ->       Tuple:
				lowercase    :      Dict       = []
				lowercase    :      List[str]       = []
				_open.append(_A )

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

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


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