






from heapq import heappop, heappush

import numpy as np


def __A    (      __lowerCAmelCase ,		__lowerCAmelCase ,		__lowerCAmelCase ,		__lowerCAmelCase ,		)->  tuple[float | int, list[tuple[int, int]]]:





						"""simple docstring"""



						_UpperCAmelCase					, _UpperCAmelCase									=			grid.shape
						_UpperCAmelCase									=			[-1, 1, 0, 0]
						_UpperCAmelCase									=			[0, 0, -1, 1]
						if allow_diagonal:
												dx += [-1, -1, 1, 1]
												dy += [-1, 1, -1, 1]

						_UpperCAmelCase					, _UpperCAmelCase									=			[(0, source)], set()
						_UpperCAmelCase									=			np.full((rows, cols) ,		np.inf	)
						_UpperCAmelCase									=			0
						_UpperCAmelCase									=			np.empty((rows, cols) ,		dtype=__lowerCAmelCase	)
						_UpperCAmelCase									=			None

						while queue:
												((_UpperCAmelCase)					, (_UpperCAmelCase))									=			heappop(__lowerCAmelCase	)
												if (x, y) in visited:
																		continue
												visited.add((x, y)	)

												if (x, y) == destination:
																		_UpperCAmelCase									=			[]
																		while (x, y) != source:
																								path.append((x, y)	)
																								_UpperCAmelCase					, _UpperCAmelCase									=			predecessors[x, y]
																		path.append(__lowerCAmelCase	)  # add the source manually
																		path.reverse()
																		return matrix[destination], path

												for i in range(len(__lowerCAmelCase	)	):
																		_UpperCAmelCase					, _UpperCAmelCase									=			x + dx[i], y + dy[i]
																		if 0 <= nx < rows and 0 <= ny < cols:
																								_UpperCAmelCase									=			grid[nx][ny]
																								if next_node == 1 and matrix[nx, ny] > dist + 1:
																														heappush(__lowerCAmelCase ,		(dist + 1, (nx, ny))	)
																														_UpperCAmelCase									=			dist + 1
																														_UpperCAmelCase									=			(x, y)

						return np.inf, []


if __name__ == "__main__":
		import doctest

		doctest.testmod()








from collections import OrderedDict
from typing import Mapping

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


_a      	=  logging.get_logger(__name__)

_a      	=  {
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}





class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	UpperCamelCase__								=      "distilbert"
	UpperCamelCase__								=      {
	    "hidden_size": "dim",
	    "num_attention_heads": "n_heads",
	    "num_hidden_layers": "n_layers",
	}

	def __init__(							self       ,    UpperCAmelCase=3_0522       ,    UpperCAmelCase=512       ,    UpperCAmelCase=False       ,    UpperCAmelCase=6       ,    UpperCAmelCase=12       ,    UpperCAmelCase=768       ,    UpperCAmelCase=4 * 768       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase="gelu"       ,    UpperCAmelCase=0.02       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=0.2       ,    UpperCAmelCase=0       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							_UpperCAmelCase									=			vocab_size
							_UpperCAmelCase									=			max_position_embeddings
							_UpperCAmelCase									=			sinusoidal_pos_embds
							_UpperCAmelCase									=			n_layers
							_UpperCAmelCase									=			n_heads
							_UpperCAmelCase									=			dim
							_UpperCAmelCase									=			hidden_dim
							_UpperCAmelCase									=			dropout
							_UpperCAmelCase									=			attention_dropout
							_UpperCAmelCase									=			activation
							_UpperCAmelCase									=			initializer_range
							_UpperCAmelCase									=			qa_dropout
							_UpperCAmelCase									=			seq_classif_dropout
							super().__init__(**UpperCAmelCase       ,    pad_token_id=UpperCAmelCase    )





class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	@property
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







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