





'''simple docstring'''

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 							__lowerCAmelCase	(       unittest.TestCase					):






       """simple docstring"""





       def snake_case__		(				self  :						str	)       ->	Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			0





       @slow
       def snake_case__		(				self  :						List[Any]	)       ->	int:

            '''simple docstring'''




            for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
                 _UpperCamelCase							       =			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():
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
                 self.assertIsNotNone(lowerCAmelCase__	)
                 self.assertIsInstance(lowerCAmelCase__			,					(GPTaTokenizer, GPTaTokenizerFast)	)
                 self.assertGreater(len(lowerCAmelCase__	)			,					0	)





       def snake_case__		(				self  :						str	)       ->	Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
            self.assertIsInstance(lowerCAmelCase__			,					(BertTokenizer, BertTokenizerFast)	)
            self.assertEqual(tokenizer.vocab_size			,					12	)





       def snake_case__		(				self  :						Dict	)       ->	List[str]:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
            self.assertIsInstance(lowerCAmelCase__			,					(RobertaTokenizer, RobertaTokenizerFast)	)
            self.assertEqual(tokenizer.vocab_size			,					20	)





       def snake_case__		(				self  :						Optional[int]	)       ->	Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoConfig.from_pretrained(lowerCAmelCase__	)
            self.assertIsInstance(lowerCAmelCase__			,					lowerCAmelCase__	)
            # Check that tokenizer_type ≠ model_type
            _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__			,					config=lowerCAmelCase__	)
            self.assertIsInstance(lowerCAmelCase__			,					(BertTokenizer, BertTokenizerFast)	)
            self.assertEqual(tokenizer.vocab_size			,					12	)





       def snake_case__		(				self  :						str	)       ->	List[Any]:

            '''simple docstring'''




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

                 _UpperCamelCase							       =			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'''	)	)

                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__			,					tokenizer_type='''gpt2'''			,					use_fast=lowerCAmelCase__	)
                 self.assertIsInstance(lowerCAmelCase__			,					lowerCAmelCase__	)





       @require_tokenizers
       def snake_case__		(				self  :						Optional[int]	)       ->	Tuple:

            '''simple docstring'''




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

                 _UpperCamelCase							       =			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'''	)	)

                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__			,					tokenizer_type='''gpt2'''	)
                 self.assertIsInstance(lowerCAmelCase__			,					lowerCAmelCase__	)





       def snake_case__		(				self  :						str	)       ->	Optional[Any]:

            '''simple docstring'''




            with pytest.raises(lowerCAmelCase__	):
                 AutoTokenizer.from_pretrained('''./'''			,					tokenizer_type='''xxx'''	)





       @require_tokenizers
       def snake_case__		(				self  :						Tuple	)       ->	Optional[int]:

            '''simple docstring'''




            for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                 _UpperCamelCase							       =			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 snake_case__		(				self  :						Dict	)       ->	Optional[Any]:

            '''simple docstring'''




            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'''			,					):
                      _UpperCamelCase							       =			tokenizer_class.from_pretrained('''julien-c/herlolip-not-exists'''	)





       def snake_case__		(				self  :						Optional[Any]	)       ->	Union[str, Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			TOKENIZER_MAPPING.values()
            _UpperCamelCase							       =			[]

            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 snake_case__		(				self  :						Tuple	)       ->	str:

            '''simple docstring'''




            self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''			,					use_fast=lowerCAmelCase__	)			,					lowerCAmelCase__	)
            self.assertIsInstance(AutoTokenizer.from_pretrained('''bert-base-cased'''	)			,					lowerCAmelCase__	)





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

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''distilbert-base-uncased'''			,					do_lower_case=lowerCAmelCase__	)
            _UpperCamelCase							       =			'''Hello, world. How are you?'''
            _UpperCamelCase							       =			tokenizer.tokenize(lowerCAmelCase__	)
            self.assertEqual('''[UNK]'''			,					tokens[0]	)

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





       @require_tokenizers
       def snake_case__		(				self  :						Union[str, Any]	)       ->	Optional[int]:

            '''simple docstring'''




            _UpperCamelCase							       =			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 snake_case__		(				self  :						Optional[int]	)       ->	Tuple:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
            self.assertIsInstance(lowerCAmelCase__			,					(BertTokenizer, BertTokenizerFast)	)
            with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(lowerCAmelCase__	)
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)

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





       def snake_case__		(				self  :						str	)       ->	List[str]:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''ctrl'''	)
            # There is no fast CTRL so this always gives us a slow tokenizer.
            self.assertIsInstance(lowerCAmelCase__			,					lowerCAmelCase__	)





       def snake_case__		(				self  :						Optional[int]	)       ->	str:

            '''simple docstring'''




            _UpperCamelCase							       =			get_tokenizer_config('''bert-base-cased'''	)
            _UpperCamelCase							       =			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.
            _UpperCamelCase							       =			get_tokenizer_config(lowerCAmelCase__	)
            self.assertDictEqual(lowerCAmelCase__			,					{}	)

            # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
            _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
            with tempfile.TemporaryDirectory() as tmp_dir:
                 tokenizer.save_pretrained(lowerCAmelCase__	)
                 _UpperCamelCase							       =			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 snake_case__		(				self  :						Union[str, Any]	)       ->	List[str]:

            '''simple docstring'''




            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__	)

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

                      _UpperCamelCase							       =			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 snake_case__		(				self  :						Tuple	)       ->	str:

            '''simple docstring'''




            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:
                      _UpperCamelCase							       =			BertTokenizerFast.from_pretrained(lowerCAmelCase__	)
                      bert_tokenizer.save_pretrained(lowerCAmelCase__	)
                      _UpperCamelCase							       =			CustomTokenizerFast.from_pretrained(lowerCAmelCase__	)

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

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

                      _UpperCamelCase							       =			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 snake_case__		(				self  :						Union[str, Any]	)       ->	Union[str, Any]:

            '''simple docstring'''




            with self.assertRaises(lowerCAmelCase__	):
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''	)
            # If remote code is disabled, we can't load this config.
            with self.assertRaises(lowerCAmelCase__	):
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(
                     '''hf-internal-testing/test_dynamic_tokenizer'''			,					trust_remote_code=lowerCAmelCase__	)

            _UpperCamelCase							       =			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__	)
                 _UpperCamelCase							       =			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
                 _UpperCamelCase							       =			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__	)
                      _UpperCamelCase							       =			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 snake_case__		(				self  :						Optional[Any]	)       ->	Dict:

            '''simple docstring'''




            class 							__lowerCAmelCase	(       __magic_name__					):






                   """simple docstring"""
                   _snake_case      :	int									=       False

            class 							__lowerCAmelCase	(       __magic_name__					):






                   """simple docstring"""
                   _snake_case      :	List[Any]									=       NewTokenizer
                   _snake_case      :	str									=       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
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''	)
                 self.assertEqual(tokenizer.__class__.__name__			,					'''NewTokenizerFast'''	)
                 self.assertFalse(tokenizer.special_attribute_present	)
                 _UpperCamelCase							       =			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.
                 _UpperCamelCase							       =			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	)
                 _UpperCamelCase							       =			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
                 _UpperCamelCase							       =			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	)
                 _UpperCamelCase							       =			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 snake_case__		(				self  :						Union[str, Any]	)       ->	Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase							       =			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
                 _UpperCamelCase							       =			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 snake_case__		(				self  :						Dict	)       ->	List[Any]:

            '''simple docstring'''




            with self.assertRaisesRegex(
                lowerCAmelCase__			,					'''bert-base is not a local folder and is not a valid model identifier'''	):
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''bert-base'''	)





       def snake_case__		(				self  :						Optional[int]	)       ->	int:

            '''simple docstring'''




            with self.assertRaisesRegex(
                lowerCAmelCase__			,					r'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''	):
                 _UpperCamelCase							       =			AutoTokenizer.from_pretrained(lowerCAmelCase__			,					revision='''aaaaaa'''	)







       def snake_case__		(				self  :						List[str]	)       ->	Any:

            '''simple docstring'''




            _UpperCamelCase							       =			AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''	)
            with RequestCounter() as counter:
                 _UpperCamelCase							       =			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	)











"""simple docstring"""







import numpy as np


class      UpperCamelCase		:






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






						def __eq__(		self  :List[Any]			, __magic_name__  :Optional[Any]				)      ->Tuple:
										return self.position == cell.position






						def      __snake_case      (		self  :Any				)      ->List[Any]:
										print(self.position				)


class      UpperCamelCase		:






						def __init__(		self  :Any			, __magic_name__  :int=(5, 5)				)      ->Dict:
										lowercase    :      Tuple       = np.zeros(__magic_name__				)
										lowercase    :      List[str]       = world_size[0]
										lowercase    :      str       = world_size[1]






						def      __snake_case      (		self  :str				)      ->int:
										print(self.w				)






						def      __snake_case      (		self  :Any			, __magic_name__  :Any				)      ->Optional[int]:
										lowercase    :      Optional[Any]       = [
										    (-1, -1),
										    (-1, 0),
										    (-1, 1),
										    (0, -1),
										    (0, 1),
										    (1, -1),
										    (1, 0),
										    (1, 1),
										]
										lowercase    :      List[str]       = cell.position[0]
										lowercase    :      List[str]       = cell.position[1]
										lowercase    :      Optional[int]       = []
										for n in neughbour_cord:
														lowercase    :      List[Any]       = current_x + n[0]
														lowercase    :      List[Any]       = current_y + n[1]
														if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																		lowercase    :      Tuple       = Cell()
																		lowercase    :      Union[str, Any]       = (x, y)
																		lowercase    :      Dict       = cell
																		neighbours.append(__magic_name__				)
										return neighbours


def      UpperCamelCase       ( _A  ,				_A  ,				_A )     ->       Tuple:
				lowercase    :      Dict       = []
				lowercase    :      List[str]       = []
				_open.append(_A )

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

												for c in _open:
																if c == n and c.f < n.f:
																				continue
												_open.append(_A )
				lowercase    :      List[str]       = []
				while current.parent is not None:
								path.append(current.position )
								lowercase    :      int       = 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)
