



'''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        UpperCAmelCase_			(			unittest.TestCase      ):
    """simple docstring"""







    def lowerCamelCase			(       self   :	List[str]		):
          snake_case__    :       Tuple       		= 0




    @slow
    def lowerCamelCase			(       self   :	Optional[Any]		):
          for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
                snake_case__    :       Dict       		= AutoTokenizer.from_pretrained(snake_case_		)
                self.assertIsNotNone(snake_case_		)
                self.assertIsInstance(snake_case_					,	(BertTokenizer, BertTokenizerFast)		)
                self.assertGreater(len(snake_case_		)					,	0		)

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




    def lowerCamelCase			(       self   :	Optional[int]		):
          snake_case__    :       Dict       		= AutoTokenizer.from_pretrained(snake_case_		)
          self.assertIsInstance(snake_case_					,	(BertTokenizer, BertTokenizerFast)		)
          self.assertEqual(tokenizer.vocab_size					,	12		)




    def lowerCamelCase			(       self   :	List[Any]		):
          snake_case__    :       List[str]       		= AutoTokenizer.from_pretrained(snake_case_		)
          self.assertIsInstance(snake_case_					,	(RobertaTokenizer, RobertaTokenizerFast)		)
          self.assertEqual(tokenizer.vocab_size					,	20		)




    def lowerCamelCase			(       self   :	Dict		):
          snake_case__    :       List[str]       		= AutoConfig.from_pretrained(snake_case_		)
          self.assertIsInstance(snake_case_					,	snake_case_		)
          # Check that tokenizer_type ≠ model_type
          snake_case__    :       int       		= AutoTokenizer.from_pretrained(snake_case_					,	config=snake_case_		)
          self.assertIsInstance(snake_case_					,	(BertTokenizer, BertTokenizerFast)		)
          self.assertEqual(tokenizer.vocab_size					,	12		)




    def lowerCamelCase			(       self   :	Optional[Any]		):
          with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("""./tests/fixtures/vocab.txt"""					,	os.path.join(snake_case_					,	"""vocab.txt"""		)		)

                snake_case__    :       int       		= AutoTokenizer.from_pretrained(snake_case_					,	tokenizer_type="""bert"""					,	use_fast=snake_case_		)
                self.assertIsInstance(snake_case_					,	snake_case_		)

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

                snake_case__    :       Optional[int]       		= AutoTokenizer.from_pretrained(snake_case_					,	tokenizer_type="""gpt2"""					,	use_fast=snake_case_		)
                self.assertIsInstance(snake_case_					,	snake_case_		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	Any		):
          with tempfile.TemporaryDirectory() as tmp_dir:
                shutil.copy("""./tests/fixtures/vocab.txt"""					,	os.path.join(snake_case_					,	"""vocab.txt"""		)		)

                snake_case__    :       Tuple       		= AutoTokenizer.from_pretrained(snake_case_					,	tokenizer_type="""bert"""		)
                self.assertIsInstance(snake_case_					,	snake_case_		)

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

                snake_case__    :       Dict       		= AutoTokenizer.from_pretrained(snake_case_					,	tokenizer_type="""gpt2"""		)
                self.assertIsInstance(snake_case_					,	snake_case_		)




    def lowerCamelCase			(       self   :	Dict		):
          with pytest.raises(snake_case_		):
                AutoTokenizer.from_pretrained("""./"""					,	tokenizer_type="""xxx"""		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	Any		):
          for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                snake_case__    :       List[Any]       		= tokenizer_class.from_pretrained("""wietsedv/bert-base-dutch-cased"""		)
                self.assertIsInstance(snake_case_					,	(BertTokenizer, BertTokenizerFast)		)

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

                self.assertEqual(tokenizer.model_max_length					,	512		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	int		):
          for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
                with self.assertRaisesRegex(
                    snake_case_					,	"""julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"""					,	):
                      snake_case__    :       Optional[int]       		= tokenizer_class.from_pretrained("""julien-c/herlolip-not-exists"""		)




    def lowerCamelCase			(       self   :	List[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
          snake_case__    :       Dict       		= TOKENIZER_MAPPING.values()
          snake_case__    :       str       		= []

          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(snake_case_		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	str		):
          self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""					,	use_fast=snake_case_		)					,	snake_case_		)
          self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""		)					,	snake_case_		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	Optional[int]		):
          snake_case__    :       Optional[int]       		= AutoTokenizer.from_pretrained("""distilbert-base-uncased"""					,	do_lower_case=snake_case_		)
          snake_case__    :       int       		= """Hello, world. How are you?"""
          snake_case__    :       Union[str, Any]       		= tokenizer.tokenize(snake_case_		)
          self.assertEqual("""[UNK]"""					,	tokens[0]		)

          snake_case__    :       Optional[int]       		= AutoTokenizer.from_pretrained("""microsoft/mpnet-base"""					,	do_lower_case=snake_case_		)
          snake_case__    :       List[Any]       		= tokenizer.tokenize(snake_case_		)
          self.assertEqual("""[UNK]"""					,	tokens[0]		)




    @require_tokenizers
    def lowerCamelCase			(       self   :	List[Any]		):
          snake_case__    :       int       		= AutoTokenizer.from_pretrained("""robot-test/dummy-tokenizer-fast-with-model-config"""		)
          self.assertEqual(type(snake_case_		)					,	snake_case_		)
          self.assertEqual(tokenizer.model_max_length					,	512		)
          self.assertEqual(tokenizer.vocab_size					,	30_000		)
          self.assertEqual(tokenizer.unk_token					,	"""[UNK]"""		)
          self.assertEqual(tokenizer.padding_side					,	"""right"""		)
          self.assertEqual(tokenizer.truncation_side					,	"""right"""		)




    def lowerCamelCase			(       self   :	Optional[Any]		):
          snake_case__    :       Any       		= AutoTokenizer.from_pretrained(snake_case_		)
          self.assertIsInstance(snake_case_					,	(BertTokenizer, BertTokenizerFast)		)
          with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(snake_case_		)
                snake_case__    :       str       		= AutoTokenizer.from_pretrained(snake_case_		)

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




    def lowerCamelCase			(       self   :	Union[str, Any]		):
          snake_case__    :       Optional[Any]       		= AutoTokenizer.from_pretrained("""ctrl"""		)
          # There is no fast CTRL so this always gives us a slow tokenizer.
          self.assertIsInstance(snake_case_					,	snake_case_		)




    def lowerCamelCase			(       self   :	Dict		):
          # Check we can load the tokenizer config of an online model.
          snake_case__    :       Tuple       		= get_tokenizer_config("""bert-base-cased"""		)
          snake_case__    :       Dict       		= config.pop("""_commit_hash"""					,	snake_case_		)
          # If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
          self.assertEqual(snake_case_					,	{"""do_lower_case""": False}		)

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

          # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
          snake_case__    :       Optional[int]       		= AutoTokenizer.from_pretrained(snake_case_		)
          with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(snake_case_		)
                snake_case__    :       List[Any]       		= get_tokenizer_config(snake_case_		)

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




    def lowerCamelCase			(       self   :	Union[str, Any]		):
          try:
                AutoConfig.register("""custom"""					,	snake_case_		)

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

                snake_case__    :       str       		= CustomTokenizer.from_pretrained(snake_case_		)
                with tempfile.TemporaryDirectory() as tmp_dir:
                      tokenizer.save_pretrained(snake_case_		)

                      snake_case__    :       Any       		= AutoTokenizer.from_pretrained(snake_case_		)
                      self.assertIsInstance(snake_case_					,	snake_case_		)

          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 lowerCamelCase			(       self   :	List[Any]		):
          try:
                AutoConfig.register("""custom"""					,	snake_case_		)

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

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

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

                # 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:
                      snake_case__    :       Union[str, Any]       		= BertTokenizerFast.from_pretrained(snake_case_		)
                      bert_tokenizer.save_pretrained(snake_case_		)
                      snake_case__    :       Optional[Any]       		= CustomTokenizerFast.from_pretrained(snake_case_		)

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

                      snake_case__    :       Any       		= AutoTokenizer.from_pretrained(snake_case_		)
                      self.assertIsInstance(snake_case_					,	snake_case_		)

                      snake_case__    :       Tuple       		= AutoTokenizer.from_pretrained(snake_case_					,	use_fast=snake_case_		)
                      self.assertIsInstance(snake_case_					,	snake_case_		)

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

          snake_case__    :       Optional[Any]       		= AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_		)
          self.assertTrue(tokenizer.special_attribute_present		)
          # Test tokenizer can be reloaded.
          with tempfile.TemporaryDirectory() as tmp_dir:
                tokenizer.save_pretrained(snake_case_		)
                snake_case__    :       List[Any]       		= AutoTokenizer.from_pretrained(snake_case_					,	trust_remote_code=snake_case_		)
          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
                snake_case__    :       Optional[Any]       		= AutoTokenizer.from_pretrained(
                    """hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_					,	use_fast=snake_case_		)
                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(snake_case_		)
                      snake_case__    :       str       		= AutoTokenizer.from_pretrained(snake_case_					,	trust_remote_code=snake_case_					,	use_fast=snake_case_		)
                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 lowerCamelCase			(       self   :	Any		):







          class        UpperCAmelCase_			(			_a      ):
              """simple docstring"""







              lowercase   =						False







          class        UpperCAmelCase_			(			_a      ):
              """simple docstring"""







              lowercase   =						NewTokenizer
              lowercase   =						False

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

                # If remote code is disabled, we load the local one.
                snake_case__    :       Union[str, Any]       		= AutoTokenizer.from_pretrained(
                    """hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_		)
                self.assertEqual(tokenizer.__class__.__name__					,	"""NewTokenizerFast"""		)
                self.assertFalse(tokenizer.special_attribute_present		)
                snake_case__    :       str       		= AutoTokenizer.from_pretrained(
                    """hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_					,	use_fast=snake_case_		)
                self.assertEqual(tokenizer.__class__.__name__					,	"""NewTokenizer"""		)
                self.assertFalse(tokenizer.special_attribute_present		)

                # If remote is enabled, we load from the Hub
                snake_case__    :       List[Any]       		= AutoTokenizer.from_pretrained(
                    """hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_		)
                self.assertEqual(tokenizer.__class__.__name__					,	"""NewTokenizerFast"""		)
                self.assertTrue(tokenizer.special_attribute_present		)
                snake_case__    :       int       		= AutoTokenizer.from_pretrained(
                    """hf-internal-testing/test_dynamic_tokenizer"""					,	trust_remote_code=snake_case_					,	use_fast=snake_case_		)
                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 lowerCamelCase			(       self   :	Optional[int]		):
          snake_case__    :       Dict       		= AutoTokenizer.from_pretrained(
              """hf-internal-testing/test_dynamic_tokenizer_legacy"""					,	trust_remote_code=snake_case_		)
          self.assertTrue(tokenizer.special_attribute_present		)
          if is_tokenizers_available():
                self.assertEqual(tokenizer.__class__.__name__					,	"""NewTokenizerFast"""		)

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




    def lowerCamelCase			(       self   :	Tuple		):
          with self.assertRaisesRegex(
              snake_case_					,	"""bert-base is not a local folder and is not a valid model identifier"""		):
                snake_case__    :       List[Any]       		= AutoTokenizer.from_pretrained("""bert-base"""		)




    def lowerCamelCase			(       self   :	str		):
          with self.assertRaisesRegex(
              snake_case_					,	r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""		):
                snake_case__    :       Dict       		= AutoTokenizer.from_pretrained(snake_case_					,	revision="""aaaaaa"""		)




    def lowerCamelCase			(       self   :	str		):
          # Make sure we have cached the tokenizer.
          snake_case__    :       Optional[Any]       		= AutoTokenizer.from_pretrained("""hf-internal-testing/tiny-random-bert"""		)
          with RequestCounter() as counter:
                snake_case__    :       List[Any]       		= 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'''





__a  			=						"Alexander Joslin"

import operator as op

from .stack import Stack





def 		__snake_case(							_lowerCAmelCase						)						->					int:
      snake_case__    :       str       		= {"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-""": op.sub}

      snake_case__    :       Stack[int]       		= Stack()
      snake_case__    :       Stack[str]       		= Stack()

      for i in equation:
            if i.isdigit():
                  # RULE 1
                  operand_stack.push(int(_lowerCAmelCase						)						)
            elif i in operators:
                  # RULE 2
                  operator_stack.push(_lowerCAmelCase						)
            elif i == ")":
                  # RULE 4
                  snake_case__    :       Union[str, Any]       		= operator_stack.peek()
                  operator_stack.pop()
                  snake_case__    :       Any       		= operand_stack.peek()
                  operand_stack.pop()
                  snake_case__    :       str       		= operand_stack.peek()
                  operand_stack.pop()

                  snake_case__    :       Optional[Any]       		= operators[opr](_lowerCAmelCase	,  _lowerCAmelCase						)
                  operand_stack.push(_lowerCAmelCase						)

    # RULE 5
      return operand_stack.peek()


if __name__ == "__main__":
       __a  			=						"(5 + ((4 * 2) * (2 + 3)))"
       # answer = 45
       print(F"{equation} = {dijkstras_two_stack_algorithm(equation)}")
