





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
				UpperCamelCase__   : Optional[int]					  = """pt"""
elif is_tf_available():
				UpperCamelCase__   : Dict					  = """tf"""
else:
				UpperCamelCase__   : Tuple					  = """jax"""







class   _UpperCamelCase  (       A_						,       unittest.TestCase  ):







					'''simple docstring'''

					lowerCamelCase     :     Any			    =       PerceiverTokenizer
					lowerCamelCase     :     Any			    =       False





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						super().setUp()
						UpperCAmelCase_								=     PerceiverTokenizer()
						tokenizer.save_pretrained(self.tmpdirname		)





					@cached_property
					def        SCREAMING_SNAKE_CASE							(						self    :  List[str]		):






						'''simple docstring'''







						return PerceiverTokenizer.from_pretrained("""deepmind/language-perceiver"""		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict ,					**__lowercase    :  Dict		):






						'''simple docstring'''







						return self.tokenizer_class.from_pretrained(self.tmpdirname ,					**__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  List[str] ,					__lowercase    :  str ,					__lowercase    :  Union[str, Any]=False ,					__lowercase    :  Dict=20 ,					__lowercase    :  Any=5		):






						'''simple docstring'''







						UpperCAmelCase_								=     []
						for i in range(len(__lowercase		)		):
							try:
								UpperCAmelCase_								=     tokenizer.decode([i] ,					clean_up_tokenization_spaces=__lowercase		)
							except UnicodeDecodeError:
								pass
							toks.append((i, tok)		)

						UpperCAmelCase_								=     list(filter(lambda __lowercase		: re.match(R"""^[ a-zA-Z]+$""" ,					t[1]		) ,					__lowercase		)		)
						UpperCAmelCase_								=     list(filter(lambda __lowercase		: [t[0]] == tokenizer.encode(t[1] ,					add_special_tokens=__lowercase		) ,					__lowercase		)		)
						if max_length is not None and len(__lowercase		) > max_length:
							UpperCAmelCase_								=     toks[:max_length]
						if min_length is not None and len(__lowercase		) < min_length and len(__lowercase		) > 0:
							while len(__lowercase		) < min_length:
								UpperCAmelCase_								=     toks + toks
        # toks_str = [t[1] for t in toks]
						UpperCAmelCase_								=     [t[0] for t in toks]

						# Ensure consistency
						UpperCAmelCase_								=     tokenizer.decode(__lowercase ,					clean_up_tokenization_spaces=__lowercase		)
						if " " not in output_txt and len(__lowercase		) > 1:
							UpperCAmelCase_								=     (
							    tokenizer.decode([toks_ids[0]] ,					clean_up_tokenization_spaces=__lowercase		)
							    + """ """
							    + tokenizer.decode(toks_ids[1:] ,					clean_up_tokenization_spaces=__lowercase		)
							)
						if with_prefix_space:
							UpperCAmelCase_								=     """ """ + output_txt
						UpperCAmelCase_								=     tokenizer.encode(__lowercase ,					add_special_tokens=__lowercase		)
						return output_txt, output_ids





					def        SCREAMING_SNAKE_CASE							(						self    :  List[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.perceiver_tokenizer
						UpperCAmelCase_								=     """Unicode €."""
						UpperCAmelCase_								=     tokenizer(__lowercase		)
						UpperCAmelCase_								=     [4, 91, 1_16, 1_11, 1_05, 1_17, 1_06, 1_07, 38, 2_32, 1_36, 1_78, 52, 5]
						self.assertEqual(encoded["""input_ids"""] ,					__lowercase		)

						# decoding
						UpperCAmelCase_								=     tokenizer.decode(__lowercase		)
						self.assertEqual(__lowercase ,					"""[CLS]Unicode €.[SEP]"""		)

						UpperCAmelCase_								=     tokenizer("""e è é ê ë"""		)
						UpperCAmelCase_								=     [4, 1_07, 38, 2_01, 1_74, 38, 2_01, 1_75, 38, 2_01, 1_76, 38, 2_01, 1_77, 5]
						self.assertEqual(encoded["""input_ids"""] ,					__lowercase		)
						# decoding
						UpperCAmelCase_								=     tokenizer.decode(__lowercase		)
						self.assertEqual(__lowercase ,					"""[CLS]e è é ê ë[SEP]"""		)

						# encode/decode, but with `encode` instead of `__call__`
						self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë"""		)		) ,					"""[CLS]e è é ê ë[SEP]"""		)





					def        SCREAMING_SNAKE_CASE							(						self    :  int		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.perceiver_tokenizer
						UpperCAmelCase_								=     ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
						# fmt: off
						UpperCAmelCase_								=     [4, 71, 38, 1_14, 1_17, 1_16, 1_09, 38, 1_18, 1_03, 1_20, 1_03, 1_09, 1_20, 1_03, 1_18, 1_10, 38, 1_08, 1_17, 1_20, 38, 1_21, 1_23, 1_15, 1_15, 1_03, 1_20, 1_11, 1_28, 1_03, 1_22, 1_11, 1_17, 1_16, 52, 5, 0]
						# fmt: on
						UpperCAmelCase_								=     tokenizer(__lowercase ,					padding=__lowercase ,					return_tensors=__lowercase		)
						self.assertIsInstance(__lowercase ,					__lowercase		)

						if FRAMEWORK != "jax":
							UpperCAmelCase_								=     list(batch.input_ids.numpy()[0]		)
						else:
							UpperCAmelCase_								=     list(batch.input_ids.tolist()[0]		)

						self.assertListEqual(__lowercase ,					__lowercase		)

						self.assertEqual((2, 38) ,					batch.input_ids.shape		)
						self.assertEqual((2, 38) ,					batch.attention_mask.shape		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.perceiver_tokenizer
						UpperCAmelCase_								=     ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
						UpperCAmelCase_								=     tokenizer(__lowercase ,					padding=__lowercase ,					return_tensors=__lowercase		)
						# check if input_ids are returned and no decoder_input_ids
						self.assertIn("""input_ids""" ,					__lowercase		)
						self.assertIn("""attention_mask""" ,					__lowercase		)
						self.assertNotIn("""decoder_input_ids""" ,					__lowercase		)
						self.assertNotIn("""decoder_attention_mask""" ,					__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.perceiver_tokenizer
						UpperCAmelCase_								=     [
						    """Summary of the text.""",
						    """Another summary.""",
						]
						UpperCAmelCase_								=     tokenizer(
						    text_target=__lowercase ,					max_length=32 ,					padding="""max_length""" ,					truncation=__lowercase ,					return_tensors=__lowercase		)
						self.assertEqual(32 ,					targets["""input_ids"""].shape[1]		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_tokenizers()
						for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""		):
								self.assertNotEqual(tokenizer.model_max_length ,					42		)

        # Now let's start the test
						UpperCAmelCase_								=     self.get_tokenizers()
						for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""		):
								# Isolate this from the other tests because we save additional tokens/etc
								UpperCAmelCase_								=     tempfile.mkdtemp()

								UpperCAmelCase_								=     """ He is very happy, UNwant\u00E9d,running"""
								UpperCAmelCase_								=     tokenizer.encode(__lowercase ,					add_special_tokens=__lowercase		)
								tokenizer.save_pretrained(__lowercase		)

								UpperCAmelCase_								=     tokenizer.__class__.from_pretrained(__lowercase		)
								UpperCAmelCase_								=     after_tokenizer.encode(__lowercase ,					add_special_tokens=__lowercase		)
								self.assertListEqual(__lowercase ,					__lowercase		)

								shutil.rmtree(__lowercase		)

						UpperCAmelCase_								=     self.get_tokenizers(model_max_length=42		)
						for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""		):
								# Isolate this from the other tests because we save additional tokens/etc
								UpperCAmelCase_								=     tempfile.mkdtemp()

								UpperCAmelCase_								=     """ He is very happy, UNwant\u00E9d,running"""
								tokenizer.add_tokens(["""bim""", """bambam"""]		)
								UpperCAmelCase_								=     tokenizer.additional_special_tokens
								additional_special_tokens.append("""new_additional_special_token"""		)
								tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}		)
								UpperCAmelCase_								=     tokenizer.encode(__lowercase ,					add_special_tokens=__lowercase		)
								tokenizer.save_pretrained(__lowercase		)

								UpperCAmelCase_								=     tokenizer.__class__.from_pretrained(__lowercase		)
								UpperCAmelCase_								=     after_tokenizer.encode(__lowercase ,					add_special_tokens=__lowercase		)
								self.assertListEqual(__lowercase ,					__lowercase		)
								self.assertIn("""new_additional_special_token""" ,					after_tokenizer.additional_special_tokens		)
								self.assertEqual(after_tokenizer.model_max_length ,					42		)

								UpperCAmelCase_								=     tokenizer.__class__.from_pretrained(__lowercase ,					model_max_length=43		)
								self.assertEqual(tokenizer.model_max_length ,					43		)

								shutil.rmtree(__lowercase		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						UpperCAmelCase_								=     []
						if self.test_slow_tokenizer:
							tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())		)

						if self.test_rust_tokenizer:
							tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())		)

						for tokenizer_class, tokenizer_utils in tokenizer_list:
							with tempfile.TemporaryDirectory() as tmp_dir:
								tokenizer_utils.save_pretrained(__lowercase		)

								with open(os.path.join(__lowercase ,					"""special_tokens_map.json"""		) ,					encoding="""utf-8"""		) as json_file:
									UpperCAmelCase_								=     json.load(__lowercase		)

								with open(os.path.join(__lowercase ,					"""tokenizer_config.json"""		) ,					encoding="""utf-8"""		) as json_file:
									UpperCAmelCase_								=     json.load(__lowercase		)

								UpperCAmelCase_								=     [F"""<extra_id_{i}>""" for i in range(1_25		)]

								UpperCAmelCase_								=     added_tokens_extra_ids + [
								    """an_additional_special_token"""
								]
								UpperCAmelCase_								=     added_tokens_extra_ids + [
								    """an_additional_special_token"""
								]

								with open(os.path.join(__lowercase ,					"""special_tokens_map.json"""		) ,					"""w""" ,					encoding="""utf-8"""		) as outfile:
									json.dump(__lowercase ,					__lowercase		)
								with open(os.path.join(__lowercase ,					"""tokenizer_config.json"""		) ,					"""w""" ,					encoding="""utf-8"""		) as outfile:
									json.dump(__lowercase ,					__lowercase		)

								# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
								# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
								# "special_tokens_map.json" files
								UpperCAmelCase_								=     tokenizer_class.from_pretrained(
								    __lowercase ,					)
								self.assertIn(
								    """an_additional_special_token""" ,					tokenizer_without_change_in_init.additional_special_tokens		)
								self.assertEqual(
								    ["""an_additional_special_token"""] ,					tokenizer_without_change_in_init.convert_ids_to_tokens(
								        tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""]		)		) ,					)

								# Now we test that we can change the value of additional_special_tokens in the from_pretrained
								UpperCAmelCase_								=     added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token""" ,					lstrip=__lowercase		)]
								UpperCAmelCase_								=     tokenizer_class.from_pretrained(
								    __lowercase ,					additional_special_tokens=__lowercase ,					)

								self.assertIn("""a_new_additional_special_token""" ,					tokenizer.additional_special_tokens		)
								self.assertEqual(
								    ["""a_new_additional_special_token"""] ,					tokenizer.convert_ids_to_tokens(
								        tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""]		)		) ,					)





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






						'''simple docstring'''







						UpperCAmelCase_								=     self.perceiver_tokenizer
						self.assertEqual(tokenizer.decode([1_78]		) ,					"""�"""		)





					def        SCREAMING_SNAKE_CASE							(						self    :  Dict		):






						'''simple docstring'''







						pass





					def        SCREAMING_SNAKE_CASE							(						self    :  Tuple		):






						'''simple docstring'''







						pass





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						pass





					def        SCREAMING_SNAKE_CASE							(						self    :  Any		):






						'''simple docstring'''







						pass





					def        SCREAMING_SNAKE_CASE							(						self    :  Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_								=     self.get_tokenizers(fast=__lowercase ,					do_lower_case=__lowercase		)
						for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""		):
								UpperCAmelCase_								=     ["""[CLS]""", """t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """s""", """t""", """[SEP]"""]
								UpperCAmelCase_								=     tokenizer.convert_tokens_to_string(__lowercase		)

								self.assertIsInstance(__lowercase ,					__lowercase		)









from __future__ import annotations

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




def    A_(			A				,      A				,      A				,      A				,      A				,      ):
	UpperCAmelCase_								=     [
	    [0 for col in range(len(grid[0]   )   )] for row in range(len(A   )   )
	]  # the reference grid
	UpperCAmelCase_								=     1
	UpperCAmelCase_								=     [
	    [0 for col in range(len(grid[0]   )   )] for row in range(len(A   )   )
	]  # the action grid

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

	UpperCAmelCase_								=     False  # flag that is set when search is complete
	UpperCAmelCase_								=     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()
			UpperCAmelCase_								=     cell.pop()
			UpperCAmelCase_								=     next_cell[2]
			UpperCAmelCase_								=     next_cell[3]
			UpperCAmelCase_								=     next_cell[1]

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

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


if __name__ == "__main__":
				UpperCamelCase__   : Tuple					  = [
				    [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],
				]

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

				# the cost map which pushes the path closer to the goal
				UpperCamelCase__   : 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])):
												UpperCamelCase__   : Any					  = abs(i - goal[0]) + abs(j - goal[1])
												if grid[i][j] == 1:
																# added extra penalty in the heuristic map
																UpperCamelCase__   : Dict					  = 99

				UpperCamelCase__  ,			UpperCamelCase__   : Dict					  = 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])


