



'''simple docstring'''



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():
		lowerCamelCase	 =       """pt"""
elif is_tf_available():
		lowerCamelCase	 =       """tf"""
else:
		lowerCamelCase	 =       """jax"""





class _UpperCamelCase		(     A      ,       unittest.TestCase		):





				'''simple docstring'''





				lowerCAmelCase__					    =    PerceiverTokenizer
				lowerCAmelCase__					    =    False

				def 				__lowerCamelCase     (							self  :  Any):







											'''simple docstring'''

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

				@cached_property
				def 				__lowerCamelCase     (							self  :  int):







											'''simple docstring'''

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

				def 				__lowerCamelCase     (							self  :  Optional[int]  ,       **_lowerCAmelCase  :  Optional[int]):







											'''simple docstring'''

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

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  int  ,       _lowerCAmelCase  :  Union[str, Any]=False  ,       _lowerCAmelCase  :  Optional[int]=2_0  ,       _lowerCAmelCase  :  int=5):







											'''simple docstring'''

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

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

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

				def 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											__lowercase       	=    self.perceiver_tokenizer
											__lowercase       	=    'Unicode €.'
											__lowercase       	=    tokenizer(__UpperCamelCase)
											__lowercase       	=    [4, 9_1, 1_1_6, 1_1_1, 1_0_5, 1_1_7, 1_0_6, 1_0_7, 3_8, 2_3_2, 1_3_6, 1_7_8, 5_2, 5]
											self.assertEqual(encoded['input_ids']  ,       __UpperCamelCase)

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

											__lowercase       	=    tokenizer('e è é ê ë')
											__lowercase       	=    [4, 1_0_7, 3_8, 2_0_1, 1_7_4, 3_8, 2_0_1, 1_7_5, 3_8, 2_0_1, 1_7_6, 3_8, 2_0_1, 1_7_7, 5]
											self.assertEqual(encoded['input_ids']  ,       __UpperCamelCase)
											# decoding
											__lowercase       	=    tokenizer.decode(__UpperCamelCase)
											self.assertEqual(__UpperCamelCase  ,       '[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 				__lowerCamelCase     (							self  :  str):







											'''simple docstring'''

											__lowercase       	=    self.perceiver_tokenizer
											__lowercase       	=    ['A long paragraph for summarization.', 'Another paragraph for summarization.']
											# fmt: off
											__lowercase       	=    [4, 7_1, 3_8, 1_1_4, 1_1_7, 1_1_6, 1_0_9, 3_8, 1_1_8, 1_0_3, 1_2_0, 1_0_3, 1_0_9, 1_2_0, 1_0_3, 1_1_8, 1_1_0, 3_8, 1_0_8, 1_1_7, 1_2_0, 3_8, 1_2_1, 1_2_3, 1_1_5, 1_1_5, 1_0_3, 1_2_0, 1_1_1, 1_2_8, 1_0_3, 1_2_2, 1_1_1, 1_1_7, 1_1_6, 5_2, 5, 0]
											# fmt: on
											__lowercase       	=    tokenizer(__UpperCamelCase  ,       padding=__UpperCamelCase  ,       return_tensors=__UpperCamelCase)
											self.assertIsInstance(__UpperCamelCase  ,       __UpperCamelCase)

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

											self.assertListEqual(__UpperCamelCase  ,       __UpperCamelCase)

											self.assertEqual((2, 3_8)  ,       batch.input_ids.shape)
											self.assertEqual((2, 3_8)  ,       batch.attention_mask.shape)

				def 				__lowerCamelCase     (							self  :  List[Any]):







											'''simple docstring'''

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

				def 				__lowerCamelCase     (							self  :  int):







											'''simple docstring'''

											__lowercase       	=    self.perceiver_tokenizer
											__lowercase       	=    [
											    'Summary of the text.',
											    'Another summary.',
											]
											__lowercase       	=    tokenizer(
											    text_target=__UpperCamelCase  ,       max_length=3_2  ,       padding='max_length'  ,       truncation=__UpperCamelCase  ,       return_tensors=__UpperCamelCase)
											self.assertEqual(3_2  ,       targets['input_ids'].shape[1])

				def 				__lowerCamelCase     (							self  :  Tuple):







											'''simple docstring'''

											__lowercase       	=    self.get_tokenizers()
											for tokenizer in tokenizers:
																		with self.subTest(f"""{tokenizer.__class__.__name__}"""):
																									self.assertNotEqual(tokenizer.model_max_length  ,       4_2)

        # Now let's start the test
											__lowercase       	=    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
																									__lowercase       	=    tempfile.mkdtemp()

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

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

																									shutil.rmtree(__UpperCamelCase)

											__lowercase       	=    self.get_tokenizers(model_max_length=4_2)
											for tokenizer in tokenizers:
																		with self.subTest(f"""{tokenizer.__class__.__name__}"""):
																									# Isolate this from the other tests because we save additional tokens/etc
																									__lowercase       	=    tempfile.mkdtemp()

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

																									__lowercase       	=    tokenizer.__class__.from_pretrained(__UpperCamelCase)
																									__lowercase       	=    after_tokenizer.encode(__UpperCamelCase  ,       add_special_tokens=__UpperCamelCase)
																									self.assertListEqual(__UpperCamelCase  ,       __UpperCamelCase)
																									self.assertIn('new_additional_special_token'  ,       after_tokenizer.additional_special_tokens)
																									self.assertEqual(after_tokenizer.model_max_length  ,       4_2)

																									__lowercase       	=    tokenizer.__class__.from_pretrained(__UpperCamelCase  ,       model_max_length=4_3)
																									self.assertEqual(tokenizer.model_max_length  ,       4_3)

																									shutil.rmtree(__UpperCamelCase)

				def 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											__lowercase       	=    []
											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(__UpperCamelCase)

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

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

																									__lowercase       	=    [f"""<extra_id_{i}>""" for i in range(1_2_5)]

																									__lowercase       	=    added_tokens_extra_ids + [
																									    'an_additional_special_token'
																									]
																									__lowercase       	=    added_tokens_extra_ids + [
																									    'an_additional_special_token'
																									]

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

																									# 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
																									__lowercase       	=    tokenizer_class.from_pretrained(
																									    __UpperCamelCase  ,       )
																									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
																									__lowercase       	=    added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'  ,       lstrip=__UpperCamelCase)]
																									__lowercase       	=    tokenizer_class.from_pretrained(
																									    __UpperCamelCase  ,       additional_special_tokens=__UpperCamelCase  ,       )

																									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 				__lowerCamelCase     (							self  :  int):







											'''simple docstring'''

											__lowercase       	=    self.perceiver_tokenizer
											self.assertEqual(tokenizer.decode([1_7_8])  ,       '�')

				def 				__lowerCamelCase     (							self  :  List[str]):







											'''simple docstring'''

											pass

				def 				__lowerCamelCase     (							self  :  Tuple):







											'''simple docstring'''

											pass

				def 				__lowerCamelCase     (							self  :  Tuple):







											'''simple docstring'''

											pass

				def 				__lowerCamelCase     (							self  :  Optional[Any]):







											'''simple docstring'''

											pass

				def 				__lowerCamelCase     (							self  :  int):







											'''simple docstring'''

											__lowercase       	=    self.get_tokenizers(fast=__UpperCamelCase  ,       do_lower_case=__UpperCamelCase)
											for tokenizer in tokenizers:
																		with self.subTest(f"""{tokenizer.__class__.__name__}"""):
																									__lowercase       	=    ['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
																									__lowercase       	=    tokenizer.convert_tokens_to_string(__UpperCamelCase)

																									self.assertIsInstance(__UpperCamelCase  ,       __UpperCamelCase)








'''simple docstring'''



import numpy as np





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Dict):







											'''simple docstring'''

											__lowercase       	=(0, 0)
											__lowercase       	=None
											__lowercase       	=0
											__lowercase       	=0
											__lowercase       	=0

				def __eq__(							self  :  List[str]  ,       _lowerCAmelCase  :  Optional[Any]):







											'''simple docstring'''

											return self.position == cell.position

				def 				__lowerCamelCase     (							self  :  Dict):







											'''simple docstring'''

											print(self.position)





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Any  ,       _lowerCAmelCase  :  List[str]=(5, 5)):







											'''simple docstring'''

											__lowercase       	=np.zeros(_lowerCAmelCase)
											__lowercase       	=world_size[0]
											__lowercase       	=world_size[1]

				def 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											print(self.w)

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  List[str]):







											'''simple docstring'''

											__lowercase       	=[
											    (-1, -1),
											    (-1, 0),
											    (-1, 1),
											    (0, -1),
											    (0, 1),
											    (1, -1),
											    (1, 0),
											    (1, 1),
											]
											__lowercase       	=cell.position[0]
											__lowercase       	=cell.position[1]
											__lowercase       	=[]
											for n in neughbour_cord:
																		__lowercase       	=current_x + n[0]
																		__lowercase       	=current_y + n[1]
																		if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																									__lowercase       	=Cell()
																									__lowercase       	=(x, y)
																									__lowercase       	=cell
																									neighbours.append(_lowerCAmelCase)
											return neighbours



def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=[]
							__lowercase       	=[]
							_open.append(_lowerCAmelCase					)

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

																					for c in _open:
																												if c == n and c.f < n.f:
																																			continue
																					_open.append(_lowerCAmelCase					)
							__lowercase       	=[]
							while current.parent is not None:
														path.append(current.position					)
														__lowercase       	=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)



