




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		lowercase__				:     int 		=						None


lowercase__				:     str 		=						logging.get_logger(__name__)


lowercase__				:     Optional[int] 		=						{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase__				:     Dict 		=						{
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

lowercase__				:     List[Any] 		=						{
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
lowercase__				:     List[Any] 		=						["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN"]
class 		UpperCAmelCase   (				UpperCAmelCase__			):







						'''simple docstring'''





						lowerCAmelCase_     		=   VOCAB_FILES_NAMES
						lowerCAmelCase_     		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						lowerCAmelCase_     		=   PRETRAINED_VOCAB_FILES_MAP
						lowerCAmelCase_     		=   ['''input_ids''', '''attention_mask''']
						lowerCAmelCase_     		=   MBartTokenizer

						lowerCAmelCase_     		=   []
						lowerCAmelCase_     		=   []






						def __init__(						self							:     List[Any]       ,	__lowercase							:     str=None       ,	__lowercase							:     Optional[int]=None       ,	__lowercase							:     int="<s>"       ,	__lowercase							:     List[str]="</s>"       ,	__lowercase							:     Union[str, Any]="</s>"       ,	__lowercase							:     List[Any]="<s>"       ,	__lowercase							:     Optional[Any]="<unk>"       ,	__lowercase							:     List[str]="<pad>"       ,	__lowercase							:     Optional[int]="<mask>"       ,	__lowercase							:     List[Any]=None       ,	__lowercase							:     List[str]=None       ,	__lowercase							:     Optional[Any]=None       ,	**__lowercase							:     Any       ,	):






							"""simple docstring"""






							snake_case_		    =     AddedToken(__lowercase       ,	lstrip=__lowercase       ,	rstrip=__lowercase						) if isinstance(__lowercase       ,	__lowercase						) else mask_token

							super().__init__(
							    vocab_file=__lowercase       ,	tokenizer_file=__lowercase       ,	bos_token=__lowercase       ,	eos_token=__lowercase       ,	sep_token=__lowercase       ,	cls_token=__lowercase       ,	unk_token=__lowercase       ,	pad_token=__lowercase       ,	mask_token=__lowercase       ,	src_lang=__lowercase       ,	tgt_lang=__lowercase       ,	additional_special_tokens=__lowercase       ,	**__lowercase       ,	)

							snake_case_		    =     vocab_file
							snake_case_		    =     False if not self.vocab_file else True

							snake_case_		    =     FAIRSEQ_LANGUAGE_CODES.copy()

							if additional_special_tokens is not None:
								# Only add those special tokens if they are not already there.
								_additional_special_tokens.extend(
								    [t for t in additional_special_tokens if t not in _additional_special_tokens]						)

							self.add_special_tokens({"additional_special_tokens": _additional_special_tokens}						)
							snake_case_		    =     {
							    lang_code: self.convert_tokens_to_ids(__lowercase						) for lang_code in FAIRSEQ_LANGUAGE_CODES
							}

							snake_case_		    =     src_lang if src_lang is not None else "en_XX"
							snake_case_		    =     self.convert_tokens_to_ids(self._src_lang						)
							snake_case_		    =     tgt_lang
							self.set_src_lang_special_tokens(self._src_lang						)






						@property
						def        snake_case__						(						self							:     Tuple						):






							"""simple docstring"""






							return self._src_lang






						@src_lang.setter
						def        snake_case__						(						self							:     List[Any]       ,	__lowercase							:     str						):






							"""simple docstring"""






							snake_case_		    =     new_src_lang
							self.set_src_lang_special_tokens(self._src_lang						)






						def        snake_case__						(						self							:     Any       ,	__lowercase							:     List[int]       ,	__lowercase							:     Optional[List[int]] = None						):






							"""simple docstring"""






							if token_ids_a is None:
								return self.prefix_tokens + token_ids_a + self.suffix_tokens
							# We don't expect to process pairs, but leave the pair logic for API consistency
							return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens






						def        snake_case__						(						self							:     int       ,	__lowercase							:     List[int]       ,	__lowercase							:     Optional[List[int]] = None						):






							"""simple docstring"""






							snake_case_		    =     [self.sep_token_id]
							snake_case_		    =     [self.cls_token_id]

							if token_ids_a is None:
								return len(cls + token_ids_a + sep						) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep						) * [0]






						def        snake_case__						(						self							:     int       ,	__lowercase							:     str       ,	__lowercase							:     str       ,	__lowercase							:     Optional[str]       ,	__lowercase							:     Optional[str]       ,	**__lowercase							:     Optional[Any]						):






							"""simple docstring"""






							if src_lang is None or tgt_lang is None:
								raise ValueError("Translation requires a `src_lang` and a `tgt_lang` for this model"						)
							snake_case_		    =     src_lang
							snake_case_		    =     self(__lowercase       ,	add_special_tokens=__lowercase       ,	return_tensors=__lowercase       ,	**__lowercase						)
							snake_case_		    =     self.convert_tokens_to_ids(__lowercase						)
							snake_case_		    =     tgt_lang_id
							return inputs






						def        snake_case__						(						self							:     Optional[int]       ,	__lowercase							:     List[str]       ,	__lowercase							:     str = "en_XX"       ,	__lowercase							:     Optional[List[str]] = None       ,	__lowercase							:     str = "ro_RO"       ,	**__lowercase							:     List[Any]       ,	):






							"""simple docstring"""






							snake_case_		    =     src_lang
							snake_case_		    =     tgt_lang
							return super().prepare_seqaseq_batch(__lowercase       ,	__lowercase       ,	**__lowercase						)






						def        snake_case__						(						self							:     Optional[Any]						):






							"""simple docstring"""






							return self.set_src_lang_special_tokens(self.src_lang						)






						def        snake_case__						(						self							:     Optional[Any]						):






							"""simple docstring"""






							return self.set_tgt_lang_special_tokens(self.tgt_lang						)






						def        snake_case__						(						self							:     int       ,	__lowercase							:     str						):






							"""simple docstring"""






							snake_case_		    =     self.convert_tokens_to_ids(__lowercase						)
							snake_case_		    =     []
							snake_case_		    =     [self.eos_token_id, self.cur_lang_code]

							snake_case_		    =     self.convert_ids_to_tokens(self.prefix_tokens						)
							snake_case_		    =     self.convert_ids_to_tokens(self.suffix_tokens						)

							snake_case_		    =     processors.TemplateProcessing(
							    single=prefix_tokens_str + ["$A"] + suffix_tokens_str       ,	pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str       ,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str       ,	self.prefix_tokens + self.suffix_tokens						)						)       ,	)






						def        snake_case__						(						self							:     str       ,	__lowercase							:     str						):






							"""simple docstring"""






							snake_case_		    =     self.convert_tokens_to_ids(__lowercase						)
							snake_case_		    =     []
							snake_case_		    =     [self.eos_token_id, self.cur_lang_code]

							snake_case_		    =     self.convert_ids_to_tokens(self.prefix_tokens						)
							snake_case_		    =     self.convert_ids_to_tokens(self.suffix_tokens						)

							snake_case_		    =     processors.TemplateProcessing(
							    single=prefix_tokens_str + ["$A"] + suffix_tokens_str       ,	pair=prefix_tokens_str + ["$A", "$B"] + suffix_tokens_str       ,	special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str       ,	self.prefix_tokens + self.suffix_tokens						)						)       ,	)






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     str       ,	__lowercase							:     Optional[str] = None						):






							"""simple docstring"""






							if not self.can_save_slow_tokenizer:
								raise ValueError(
								    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
								    "tokenizer."						)

							if not os.path.isdir(__lowercase						):
								logger.error(f"Vocabulary path ({save_directory}) should be a directory."						)
								return
							snake_case_		    =     os.path.join(
							    __lowercase       ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

							if os.path.abspath(self.vocab_file						) != os.path.abspath(__lowercase						):
								copyfile(self.vocab_file       ,	__lowercase						)

							return (out_vocab_file,)






from __future__ import annotations

lowercase__				:     str 		=						[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A     ,	_A     ,	_A     ,	):







	'''simple docstring'''





	snake_case_		    =     [
	    [0 for col in range(len(grid[0]							)							)] for row in range(len(_A							)							)
	]  # the reference grid
	snake_case_		    =     1
	snake_case_		    =     [
	    [0 for col in range(len(grid[0]							)							)] for row in range(len(_A							)							)
	]  # the action grid

	snake_case_		    =     init[0]
	snake_case_		    =     init[1]
	snake_case_		    =     0
	snake_case_		    =     g + heuristic[x][y]  # cost from starting cell to destination cell
	snake_case_		    =     [[f, g, x, y]]

	snake_case_		    =     False  # flag that is set when search is complete
	snake_case_		    =     False  # flag set if we can't find expand

	while not found and not resign:
		if len(_A							) == 0:
			raise ValueError("Algorithm is unable to find solution"							)
		else:  # to choose the least costliest action so as to move closer to the goal
			cell.sort()
			cell.reverse()
			snake_case_		    =     cell.pop()
			snake_case_		    =     next_cell[2]
			snake_case_		    =     next_cell[3]
			snake_case_		    =     next_cell[1]

			if x == goal[0] and y == goal[1]:
				snake_case_		    =     True
			else:
				for i in range(len(_A							)							):  # to try out different valid actions
					snake_case_		    =     x + DIRECTIONS[i][0]
					snake_case_		    =     y + DIRECTIONS[i][1]
					if xa >= 0 and xa < len(_A							) and ya >= 0 and ya < len(grid[0]							):
						if closed[xa][ya] == 0 and grid[xa][ya] == 0:
							snake_case_		    =     g + cost
							snake_case_		    =     ga + heuristic[xa][ya]
							cell.append([fa, ga, xa, ya]							)
							snake_case_		    =     1
							snake_case_		    =     i
	snake_case_		    =     []
	snake_case_		    =     goal[0]
	snake_case_		    =     goal[1]
	invpath.append([x, y]							)  # we get the reverse path from here
	while x != init[0] or y != init[1]:
		snake_case_		    =     x - DIRECTIONS[action[x][y]][0]
		snake_case_		    =     y - DIRECTIONS[action[x][y]][1]
		snake_case_		    =     xa
		snake_case_		    =     ya
		invpath.append([x, y]							)

	snake_case_		    =     []
	for i in range(len(_A							)							):
		path.append(invpath[len(_A							) - 1 - i]							)
	return path, action


if __name__ == "__main__":
		lowercase__				:     Union[str, Any] 		=						[
		    [0, 1, 0, 0, 0, 0],
		    [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
		    [0, 1, 0, 0, 0, 0],
		    [0, 1, 0, 0, 1, 0],
		    [0, 0, 0, 0, 1, 0],
		]

		lowercase__				:     Optional[Any] 		=						[0, 0]
		# all coordinates are given in format [y,x]
		lowercase__				:     Tuple 		=						[len(grid) - 1, len(grid[0]) - 1]
		lowercase__				:     Dict 		=						1

		# the cost map which pushes the path closer to the goal
		lowercase__				:     Any 		=						[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
		for i in range(len(grid)):
				for j in range(len(grid[0])):
						lowercase__				:     Union[str, Any] 		=						abs(i - goal[0]) + abs(j - goal[1])
						if grid[i][j] == 1:
								# added extra penalty in the heuristic map
								lowercase__				:     int 		=						99

		lowercase__		,       lowercase__				:     Tuple 		=						search(grid, init, goal, cost, heuristic)

		print("ACTION MAP")
		for i in range(len(action)):
				print(action[i])

		for i in range(len(path)):
				print(path[i])
