



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					:					int      )   ->	Dict:
    _A      =       0

 @slow
 def     snake_case_      (    self					:					Tuple      )   ->	Any:

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

 def     snake_case_      (    self					:					Any      )   ->	str:
    _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )
    self.assertIsInstance(__lowerCAmelCase			,						(BertTokenizer, BertTokenizerFast)      )
    self.assertEqual(tokenizer.vocab_size			,						12      )

 def     snake_case_      (    self					:					Optional[Any]      )   ->	int:
    _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )
    self.assertIsInstance(__lowerCAmelCase			,						(RobertaTokenizer, RobertaTokenizerFast)      )
    self.assertEqual(tokenizer.vocab_size			,						20      )

 def     snake_case_      (    self					:					Any      )   ->	Union[str, Any]:
    _A      =       AutoConfig.from_pretrained(__lowerCAmelCase      )
    self.assertIsInstance(__lowerCAmelCase			,						__lowerCAmelCase      )
    # Check that tokenizer_type ≠ model_type
    _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase			,						config=__lowerCAmelCase      )
    self.assertIsInstance(__lowerCAmelCase			,						(BertTokenizer, BertTokenizerFast)      )
    self.assertEqual(tokenizer.vocab_size			,						12      )

 def     snake_case_      (    self					:					Dict      )   ->	List[Any]:

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

       _A      =       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'''      )      )

       _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase			,						tokenizer_type='''gpt2'''			,						use_fast=__lowerCAmelCase      )
       self.assertIsInstance(__lowerCAmelCase			,						__lowerCAmelCase      )

 @require_tokenizers
 def     snake_case_      (    self					:					Any      )   ->	Dict:

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

       _A      =       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'''      )      )

       _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase			,						tokenizer_type='''gpt2'''      )
       self.assertIsInstance(__lowerCAmelCase			,						__lowerCAmelCase      )

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

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

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

    for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
       _A      =       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			,						5_12      )

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

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

 def     snake_case_      (    self					:					Union[str, Any]      )   ->	List[str]:
    _A      =       TOKENIZER_MAPPING.values()
    _A      =       []

    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					:					List[Any]      )   ->	Any:
    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]      )   ->	Optional[int]:
    _A      =       AutoTokenizer.from_pretrained('''distilbert-base-uncased'''			,						do_lower_case=__lowerCAmelCase      )
    _A      =       "Hello, world. How are you?"
    _A      =       tokenizer.tokenize(__lowerCAmelCase      )
    self.assertEqual('''[UNK]'''			,						tokens[0]      )

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

 @require_tokenizers
 def     snake_case_      (    self					:					Union[str, Any]      )   ->	Optional[int]:
    _A      =       AutoTokenizer.from_pretrained('''robot-test/dummy-tokenizer-fast-with-model-config'''      )
    self.assertEqual(type(__lowerCAmelCase      )			,						__lowerCAmelCase      )
    self.assertEqual(tokenizer.model_max_length			,						5_12      )
    self.assertEqual(tokenizer.vocab_size			,						3_00_00      )
    self.assertEqual(tokenizer.unk_token			,						'''[UNK]'''      )
    self.assertEqual(tokenizer.padding_side			,						'''right'''      )
    self.assertEqual(tokenizer.truncation_side			,						'''right'''      )

 def     snake_case_      (    self					:					str      )   ->	List[Any]:
    _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )
    self.assertIsInstance(__lowerCAmelCase			,						(BertTokenizer, BertTokenizerFast)      )
    with tempfile.TemporaryDirectory() as tmp_dir:
       tokenizer.save_pretrained(__lowerCAmelCase      )
       _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )

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

 def     snake_case_      (    self					:					int      )   ->	Optional[Any]:
    _A      =       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					:					List[str]      )   ->	str:
    _A      =       get_tokenizer_config('''bert-base-cased'''      )
    _A      =       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.
    _A      =       get_tokenizer_config(__lowerCAmelCase      )
    self.assertDictEqual(__lowerCAmelCase			,						{}      )

    # A tokenizer saved with `save_pretrained` always creates a tokenizer config.
    _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )
    with tempfile.TemporaryDirectory() as tmp_dir:
       tokenizer.save_pretrained(__lowerCAmelCase      )
       _A      =       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					:					Any      )   ->	Optional[Any]:

    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      )

       _A      =       CustomTokenizer.from_pretrained(__lowerCAmelCase      )
       with tempfile.TemporaryDirectory() as tmp_dir:
          tokenizer.save_pretrained(__lowerCAmelCase      )

          _A      =       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					:					List[Any]      )   ->	Dict:

    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:
          _A      =       BertTokenizerFast.from_pretrained(__lowerCAmelCase      )
          bert_tokenizer.save_pretrained(__lowerCAmelCase      )
          _A      =       CustomTokenizerFast.from_pretrained(__lowerCAmelCase      )

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

          _A      =       AutoTokenizer.from_pretrained(__lowerCAmelCase      )
          self.assertIsInstance(__lowerCAmelCase			,						__lowerCAmelCase      )

          _A      =       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					:					Any      )   ->	Optional[Any]:

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

    _A      =       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      )
       _A      =       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
       _A      =       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      )
          _A      =       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					:					Dict      )   ->	Union[str, Any]:


    class 	lowerCamelCase__	(       _A):



     """simple docstring"""

     a__					: Tuple =  False


    class 	lowerCamelCase__	(       _A):



     """simple docstring"""

     a__					: Optional[int] =  NewTokenizer
     a__					: 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
       _A      =       AutoTokenizer.from_pretrained('''hf-internal-testing/test_dynamic_tokenizer'''      )
       self.assertEqual(tokenizer.__class__.__name__			,						'''NewTokenizerFast'''      )
       self.assertFalse(tokenizer.special_attribute_present      )
       _A      =       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.
       _A      =       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      )
       _A      =       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
       _A      =       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      )
       _A      =       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					:					Optional[int]      )   ->	int:
    _A      =       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
       _A      =       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					:					Tuple      )   ->	List[Any]:

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

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

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

 def     snake_case_      (    self					:					List[Any]      )   ->	int:
    _A      =       AutoTokenizer.from_pretrained('''hf-internal-testing/tiny-random-bert'''      )
    with RequestCounter() as counter:
       _A      =       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"""

def       SCREAMING_SNAKE_CASE							( lowercase__					,					lowercase__   )			->						float:
 if digit_amount > 0:
  return round(number - int(lowercase__   )					,					lowercase__   )
 return number - int(lowercase__   )


if __name__ == "__main__":
    print(decimal_isolate(1.53, 0))
    print(decimal_isolate(35.345, 1))
    print(decimal_isolate(35.345, 2))
    print(decimal_isolate(35.345, 3))
    print(decimal_isolate(-14.789, 3))
    print(decimal_isolate(0, 2))
    print(decimal_isolate(-14.123, 1))
    print(decimal_isolate(-14.123, 2))
    print(decimal_isolate(-14.123, 3))






