





'''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       :		List[Any]					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	0





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

            '''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       :		Dict					)   ->					Dict:

            '''simple docstring'''




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





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

            '''simple docstring'''




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





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

            '''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[Any]					)   ->					str:

            '''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       :		Tuple					)   ->					Optional[Any]:

            '''simple docstring'''




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





       @require_tokenizers
       def snake_case__						(							self       :		str					)   ->					Any:

            '''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       :		Optional[int]					)   ->					Dict:

            '''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[int]					)   ->					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       :		int					)   ->					List[Any]:

            '''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]					)   ->					str:

            '''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       :		Optional[int]					)   ->					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       :		str					)   ->					Optional[Any]:

            '''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					)   ->					Tuple:

            '''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       :		Any					)   ->					Union[str, Any]:

            '''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       :		List[Any]					)   ->					Union[str, Any]:

            '''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					)   ->					List[Any]:

            '''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       :		int					)   ->					Dict:

            '''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       :		Union[str, Any]					)   ->					List[str]:

            '''simple docstring'''




            class     __lowerCAmelCase					(   __magic_name__			):






                   """simple docstring"""
                   _snake_case     :					Dict						    =   False

            class     __lowerCAmelCase					(   __magic_name__			):






                   """simple docstring"""
                   _snake_case     :					int						    =   NewTokenizer
                   _snake_case     :					Union[str, 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
                 _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       :		Any					)   ->					Union[str, 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       :		Any					)   ->					int:

            '''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       :		int					)   ->					List[Any]:

            '''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       :		Dict					)   ->					List[str]:

            '''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 math







def  a__    (    lowercase :					float, lowercase :					float				)		->		float:





     """simple docstring"""

     if initial_intensity < 0:
          raise ValueError('''The value of intensity cannot be negative'''				)
          # handling of negative values of initial intensity
     if angle < 0 or angle > 360:
          raise ValueError('''In Malus Law, the angle is in the range 0-360 degrees'''				)
          # handling of values out of allowed range
     return initial_intensity * (math.cos(math.radians(lowercase				)				) ** 2)


if __name__ == "__main__":
   import doctest

   doctest.testmod(name='malus_law')



