
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
						from test_module.custom_tokenization_fast import CustomTokenizerFast





class   UpperCamelCase_      (      unittest.TestCase		):







						'''simple docstring'''



						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->Any:
										lowercase         =      0





						@slow
						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->int:
										for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
														self.assertIsNotNone(lowerCAmelCase__     )
														self.assertIsInstance(lowerCAmelCase__		,    (BertTokenizer, BertTokenizerFast)     )
														self.assertGreater(len(lowerCAmelCase__     )		,    0     )

										for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
														self.assertIsNotNone(lowerCAmelCase__     )
														self.assertIsInstance(lowerCAmelCase__		,    (GPTaTokenizer, GPTaTokenizerFast)     )
														self.assertGreater(len(lowerCAmelCase__     )		,    0     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->List[Any]:
										lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
										self.assertIsInstance(lowerCAmelCase__		,    (BertTokenizer, BertTokenizerFast)     )
										self.assertEqual(tokenizer.vocab_size		,    12     )





						def        SCREAMING_SNAKE_CASE(			self							:int     )  ->int:
										lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
										self.assertIsInstance(lowerCAmelCase__		,    (RobertaTokenizer, RobertaTokenizerFast)     )
										self.assertEqual(tokenizer.vocab_size		,    20     )





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->List[str]:
										lowercase         =      AutoConfig.from_pretrained(lowerCAmelCase__     )
										self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )
										# Check that tokenizer_type ≠ model_type
										lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    config=lowerCAmelCase__     )
										self.assertIsInstance(lowerCAmelCase__		,    (BertTokenizer, BertTokenizerFast)     )
										self.assertEqual(tokenizer.vocab_size		,    12     )





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->Tuple:
										with tempfile.TemporaryDirectory() as tmp_dir:
														shutil.copy("./tests/fixtures/vocab.txt"		,    os.path.join(lowerCAmelCase__		,    "vocab.txt"     )     )

														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    tokenizer_type="bert"		,    use_fast=lowerCAmelCase__     )
														self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )

										with tempfile.TemporaryDirectory() as tmp_dir:
														shutil.copy("./tests/fixtures/vocab.json"		,    os.path.join(lowerCAmelCase__		,    "vocab.json"     )     )
														shutil.copy("./tests/fixtures/merges.txt"		,    os.path.join(lowerCAmelCase__		,    "merges.txt"     )     )

														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    tokenizer_type="gpt2"		,    use_fast=lowerCAmelCase__     )
														self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->List[str]:
										with tempfile.TemporaryDirectory() as tmp_dir:
														shutil.copy("./tests/fixtures/vocab.txt"		,    os.path.join(lowerCAmelCase__		,    "vocab.txt"     )     )

														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    tokenizer_type="bert"     )
														self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )

										with tempfile.TemporaryDirectory() as tmp_dir:
														shutil.copy("./tests/fixtures/vocab.json"		,    os.path.join(lowerCAmelCase__		,    "vocab.json"     )     )
														shutil.copy("./tests/fixtures/merges.txt"		,    os.path.join(lowerCAmelCase__		,    "merges.txt"     )     )

														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    tokenizer_type="gpt2"     )
														self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->int:
										with pytest.raises(lowerCAmelCase__     ):
														AutoTokenizer.from_pretrained("./"		,    tokenizer_type="xxx"     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->Optional[Any]:
										for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
														lowercase         =      tokenizer_class.from_pretrained("wietsedv/bert-base-dutch-cased"     )
														self.assertIsInstance(lowerCAmelCase__		,    (BertTokenizer, BertTokenizerFast)     )

														if isinstance(lowerCAmelCase__		,    lowerCAmelCase__     ):
																		self.assertEqual(tokenizer.basic_tokenizer.do_lower_case		,    lowerCAmelCase__     )
														else:
																		self.assertEqual(tokenizer.do_lower_case		,    lowerCAmelCase__     )

														self.assertEqual(tokenizer.model_max_length		,    512     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->List[str]:
										for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
														with self.assertRaisesRegex(
														    lowerCAmelCase__		,    "julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"		,    ):
																		lowercase         =      tokenizer_class.from_pretrained("julien-c/herlolip-not-exists"     )





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Any:
										# tests: https://github.com/huggingface/transformers/pull/13251
										# 1. models with `-`, e.g. xlm-roberta -> xlm_roberta
										# 2. models that don't remap 1-1 from model-name to model file, e.g., openai-gpt -> openai
										lowercase         =      TOKENIZER_MAPPING.values()
										lowercase         =      []

										for slow_tok, fast_tok in tokenizers:
														if slow_tok is not None:
																		tokenizer_names.append(slow_tok.__name__     )

														if fast_tok is not None:
																		tokenizer_names.append(fast_tok.__name__     )

										for tokenizer_name in tokenizer_names:
														# must find the right class
														tokenizer_class_from_name(lowerCAmelCase__     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:List[str]     )  ->List[str]:
										self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"		,    use_fast=lowerCAmelCase__     )		,    lowerCAmelCase__     )
										self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"     )		,    lowerCAmelCase__     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->Any:
										lowercase         =      AutoTokenizer.from_pretrained("distilbert-base-uncased"		,    do_lower_case=lowerCAmelCase__     )
										lowercase         =      "Hello, world. How are you?"
										lowercase         =      tokenizer.tokenize(lowerCAmelCase__     )
										self.assertEqual("[UNK]"		,    tokens[0]     )

										lowercase         =      AutoTokenizer.from_pretrained("microsoft/mpnet-base"		,    do_lower_case=lowerCAmelCase__     )
										lowercase         =      tokenizer.tokenize(lowerCAmelCase__     )
										self.assertEqual("[UNK]"		,    tokens[0]     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->str:
										lowercase         =      AutoTokenizer.from_pretrained("robot-test/dummy-tokenizer-fast-with-model-config"     )
										self.assertEqual(type(lowerCAmelCase__     )		,    lowerCAmelCase__     )
										self.assertEqual(tokenizer.model_max_length		,    512     )
										self.assertEqual(tokenizer.vocab_size		,    30000     )
										self.assertEqual(tokenizer.unk_token		,    "[UNK]"     )
										self.assertEqual(tokenizer.padding_side		,    "right"     )
										self.assertEqual(tokenizer.truncation_side		,    "right"     )





						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->List[Any]:
										lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
										self.assertIsInstance(lowerCAmelCase__		,    (BertTokenizer, BertTokenizerFast)     )
										with tempfile.TemporaryDirectory() as tmp_dir:
														tokenizer.save_pretrained(lowerCAmelCase__     )
														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )

										self.assertIsInstance(lowerCAmelCase__		,    tokenizer.__class__     )
										self.assertEqual(tokenizera.vocab_size		,    12     )





						def        SCREAMING_SNAKE_CASE(			self							:str     )  ->int:
										lowercase         =      AutoTokenizer.from_pretrained("ctrl"     )
										# There is no fast CTRL so this always gives us a slow tokenizer.
										self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Any:
										# Check we can load the tokenizer config of an online model.
										lowercase         =      get_tokenizer_config("bert-base-cased"     )
										lowercase         =      config.pop("_commit_hash"		,    lowerCAmelCase__     )
										# If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
										self.assertEqual(lowerCAmelCase__		,    {"do_lower_case": False}     )

										# This model does not have a tokenizer_config so we get back an empty dict.
										lowercase         =      get_tokenizer_config(lowerCAmelCase__     )
										self.assertDictEqual(lowerCAmelCase__		,    {}     )

										# A tokenizer saved with `save_pretrained` always creates a tokenizer config.
										lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
										with tempfile.TemporaryDirectory() as tmp_dir:
														tokenizer.save_pretrained(lowerCAmelCase__     )
														lowercase         =      get_tokenizer_config(lowerCAmelCase__     )

										# Check the class of the tokenizer was properly saved (note that it always saves the slow class).
										self.assertEqual(config["tokenizer_class"]		,    "BertTokenizer"     )





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->Dict:
										try:
														AutoConfig.register("custom"		,    lowerCAmelCase__     )

														AutoTokenizer.register(lowerCAmelCase__		,    slow_tokenizer_class=lowerCAmelCase__     )
														# Trying to register something existing in the Transformers library will raise an error
														with self.assertRaises(lowerCAmelCase__     ):
																		AutoTokenizer.register(lowerCAmelCase__		,    slow_tokenizer_class=lowerCAmelCase__     )

														lowercase         =      CustomTokenizer.from_pretrained(lowerCAmelCase__     )
														with tempfile.TemporaryDirectory() as tmp_dir:
																		tokenizer.save_pretrained(lowerCAmelCase__     )

																		lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
																		self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )

										finally:
														if "custom" in CONFIG_MAPPING._extra_content:
																		del CONFIG_MAPPING._extra_content["custom"]
														if CustomConfig in TOKENIZER_MAPPING._extra_content:
																		del TOKENIZER_MAPPING._extra_content[CustomConfig]





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->List[str]:
										try:
														AutoConfig.register("custom"		,    lowerCAmelCase__     )

														# Can register in two steps
														AutoTokenizer.register(lowerCAmelCase__		,    slow_tokenizer_class=lowerCAmelCase__     )
														self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,    (CustomTokenizer, None)     )
														AutoTokenizer.register(lowerCAmelCase__		,    fast_tokenizer_class=lowerCAmelCase__     )
														self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,    (CustomTokenizer, CustomTokenizerFast)     )

														del TOKENIZER_MAPPING._extra_content[CustomConfig]
														# Can register in one step
														AutoTokenizer.register(
														    lowerCAmelCase__		,    slow_tokenizer_class=lowerCAmelCase__		,    fast_tokenizer_class=lowerCAmelCase__     )
														self.assertEqual(TOKENIZER_MAPPING[CustomConfig]		,    (CustomTokenizer, CustomTokenizerFast)     )

														# Trying to register something existing in the Transformers library will raise an error
														with self.assertRaises(lowerCAmelCase__     ):
																		AutoTokenizer.register(lowerCAmelCase__		,    fast_tokenizer_class=lowerCAmelCase__     )

														# We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
														# and that model does not have a tokenizer.json
														with tempfile.TemporaryDirectory() as tmp_dir:
																		lowercase         =      BertTokenizerFast.from_pretrained(lowerCAmelCase__     )
																		bert_tokenizer.save_pretrained(lowerCAmelCase__     )
																		lowercase         =      CustomTokenizerFast.from_pretrained(lowerCAmelCase__     )

														with tempfile.TemporaryDirectory() as tmp_dir:
																		tokenizer.save_pretrained(lowerCAmelCase__     )

																		lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__     )
																		self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )

																		lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
																		self.assertIsInstance(lowerCAmelCase__		,    lowerCAmelCase__     )

										finally:
														if "custom" in CONFIG_MAPPING._extra_content:
																		del CONFIG_MAPPING._extra_content["custom"]
														if CustomConfig in TOKENIZER_MAPPING._extra_content:
																		del TOKENIZER_MAPPING._extra_content[CustomConfig]





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Dict:
										# If remote code is not set, we will time out when asking whether to load the model.
										with self.assertRaises(lowerCAmelCase__     ):
														lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"     )
										# If remote code is disabled, we can't load this config.
										with self.assertRaises(lowerCAmelCase__     ):
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__     )

										lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__     )
										self.assertTrue(tokenizer.special_attribute_present     )
										# Test tokenizer can be reloaded.
										with tempfile.TemporaryDirectory() as tmp_dir:
														tokenizer.save_pretrained(lowerCAmelCase__     )
														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    trust_remote_code=lowerCAmelCase__     )
										self.assertTrue(reloaded_tokenizer.special_attribute_present     )

										if is_tokenizers_available():
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizerFast"     )
														self.assertEqual(reloaded_tokenizer.__class__.__name__		,    "NewTokenizerFast"     )

														# Test we can also load the slow version
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
														self.assertTrue(tokenizer.special_attribute_present     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
														# Test tokenizer can be reloaded.
														with tempfile.TemporaryDirectory() as tmp_dir:
																		tokenizer.save_pretrained(lowerCAmelCase__     )
																		lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    trust_remote_code=lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
														self.assertEqual(reloaded_tokenizer.__class__.__name__		,    "NewTokenizer"     )
														self.assertTrue(reloaded_tokenizer.special_attribute_present     )
										else:
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
														self.assertEqual(reloaded_tokenizer.__class__.__name__		,    "NewTokenizer"     )





						@require_tokenizers
						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]     )  ->Any:





										class   UpperCamelCase_      (      __a		):







																'''simple docstring'''



																UpperCamelCase      :  List[str]				   =					False





										class   UpperCamelCase_      (      __a		):







																'''simple docstring'''



																UpperCamelCase      :  Tuple				   =					NewTokenizer
																UpperCamelCase      :  List[Any]				   =					False

										try:
														AutoConfig.register("custom"		,    lowerCAmelCase__     )
														AutoTokenizer.register(lowerCAmelCase__		,    slow_tokenizer_class=lowerCAmelCase__     )
														AutoTokenizer.register(lowerCAmelCase__		,    fast_tokenizer_class=lowerCAmelCase__     )
														# If remote code is not set, the default is to use local
														lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizerFast"     )
														self.assertFalse(tokenizer.special_attribute_present     )
														lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/test_dynamic_tokenizer"		,    use_fast=lowerCAmelCase__     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
														self.assertFalse(tokenizer.special_attribute_present     )

														# If remote code is disabled, we load the local one.
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizerFast"     )
														self.assertFalse(tokenizer.special_attribute_present     )
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
														self.assertFalse(tokenizer.special_attribute_present     )

														# If remote is enabled, we load from the Hub
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizerFast"     )
														self.assertTrue(tokenizer.special_attribute_present     )
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer"		,    trust_remote_code=lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
														self.assertTrue(tokenizer.special_attribute_present     )

										finally:
														if "custom" in CONFIG_MAPPING._extra_content:
																		del CONFIG_MAPPING._extra_content["custom"]
														if CustomConfig in TOKENIZER_MAPPING._extra_content:
																		del TOKENIZER_MAPPING._extra_content[CustomConfig]





						def        SCREAMING_SNAKE_CASE(			self							:Any     )  ->str:
										lowercase         =      AutoTokenizer.from_pretrained(
										    "hf-internal-testing/test_dynamic_tokenizer_legacy"		,    trust_remote_code=lowerCAmelCase__     )
										self.assertTrue(tokenizer.special_attribute_present     )
										if is_tokenizers_available():
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizerFast"     )

														# Test we can also load the slow version
														lowercase         =      AutoTokenizer.from_pretrained(
														    "hf-internal-testing/test_dynamic_tokenizer_legacy"		,    trust_remote_code=lowerCAmelCase__		,    use_fast=lowerCAmelCase__     )
														self.assertTrue(tokenizer.special_attribute_present     )
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )
										else:
														self.assertEqual(tokenizer.__class__.__name__		,    "NewTokenizer"     )





						def        SCREAMING_SNAKE_CASE(			self							:Union[str, Any]     )  ->List[Any]:
										with self.assertRaisesRegex(
										    lowerCAmelCase__		,    "bert-base is not a local folder and is not a valid model identifier"     ):
														lowercase         =      AutoTokenizer.from_pretrained("bert-base"     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->Dict:
										with self.assertRaisesRegex(
										    lowerCAmelCase__		,    r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"     ):
														lowercase         =      AutoTokenizer.from_pretrained(lowerCAmelCase__		,    revision="aaaaaa"     )





						def        SCREAMING_SNAKE_CASE(			self							:Tuple     )  ->List[str]:
										# Make sure we have cached the tokenizer.
										lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"     )
										with RequestCounter() as counter:
														lowercase         =      AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-bert"     )
														self.assertEqual(counter.get_request_count		,    0     )
														self.assertEqual(counter.head_request_count		,    1     )
														self.assertEqual(counter.other_request_count		,    0     )


import numpy as np





class   UpperCamelCase_      :







						'''simple docstring'''



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





						def __eq__(			self							:Optional[int]		,    lowerCAmelCase__							:Any     )  ->Optional[int]:
										return self.position == cell.position





						def        SCREAMING_SNAKE_CASE(			self							:Optional[Any]     )  ->Optional[Any]:
										print(self.position     )





class   UpperCamelCase_      :







						'''simple docstring'''



						def __init__(			self							:Optional[Any]		,    lowerCAmelCase__							:Tuple=(5, 5)     )  ->str:
										lowercase         =      np.zeros(lowerCAmelCase__     )
										lowercase         =      world_size[0]
										lowercase         =      world_size[1]





						def        SCREAMING_SNAKE_CASE(			self							:List[Any]     )  ->Optional[int]:
										print(self.w     )





						def        SCREAMING_SNAKE_CASE(			self							:Optional[int]		,    lowerCAmelCase__							:Optional[Any]     )  ->Optional[Any]:
										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  __snake_case							(	__magic_name__		,    __magic_name__		,    __magic_name__						):







				'''simple docstring'''


				lowercase         =      []
				lowercase         =      []
				_open.append(__magic_name__						)

				while _open:
								lowercase         =      np.argmin([n.f for n in _open]						)
								lowercase         =      _open[min_f]
								_closed.append(_open.pop(__magic_name__						)						)
								if current == goal:
												break
								for n in world.get_neigbours(__magic_name__						):
												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(__magic_name__						)
				lowercase         =      []
				while current.parent is not None:
								path.append(current.position						)
								lowercase         =      current.parent
				path.append(current.position						)
				return path[::-1]


if __name__ == "__main__":
						_snake_case      :							Optional[int]     	=    Gridworld()
						# Start position and goal
						_snake_case      :							Dict     	=    Cell()
						_snake_case      :							List[str]     	=    (0, 0)
						_snake_case      :							Union[str, Any]     	=    Cell()
						_snake_case      :							List[Any]     	=    (4, 4)
						print(F"path from {start.position} to {goal.position}")
						_snake_case      :							str     	=    astar(world, start, goal)
						#   Just for visual reasons.
						for i in s:
												_snake_case      :							List[Any]     	=    1
						print(world.w)
