"""simple docstring"""


import concurrent.futures
import json
import os
import shutil
import tempfile
import unittest

from transformers import AutoTokenizer, PreTrainedTokenizerFast
from transformers.testing_utils import require_tokenizers

from ..test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class   UpperCAmelCase_	(				lowercase__,    unittest.TestCase   ):
    snake_case_											=      PreTrainedTokenizerFast
    snake_case_											=      False
    snake_case_											=      True
    snake_case_											=      """tokenizer_file"""
    def 		_lowerCamelCase      (	self			:       int		)						->    Optional[Any]:
       _lowercase							     =       False  # because we don't have pretrained_vocab_files_map
       super().setUp()
       _lowercase							     =       True

       _lowercase							     =       ["robot-test/dummy-tokenizer-fast", "robot-test/dummy-tokenizer-wordlevel"]
       _lowercase							     =       "SaulLu/dummy-tokenizer-bytelevel-bpe"

       # Inclusion of 2 tokenizers to test different types of models (Unigram and WordLevel for the moment)
       _lowercase							     =       [(PreTrainedTokenizerFast, model_path, {}) for model_path in model_paths]

       _lowercase							     =       PreTrainedTokenizerFast.from_pretrained(model_paths[0]		)
       tokenizer.save_pretrained(self.tmpdirname		)
    def 		_lowerCamelCase      (	self			:       int		)						->    List[str]:
       # We disable this test for PreTrainedTokenizerFast because it is the only tokenizer that is not linked to any
       # model
       pass
    def 		_lowerCamelCase      (	self			:       Union[str, Any]		)						->    Optional[Any]:
       # We disable this test for PreTrainedTokenizerFast because it is the only tokenizer that is not linked to any
       # model
       pass
    def 		_lowerCamelCase      (	self			:       Optional[int]		)						->    List[Any]:
       # We disable this test for PreTrainedTokenizerFast because it is the only tokenizer that is not linked to any
       # model
       pass
    def 		_lowerCamelCase      (	self			:       List[str]		)						->    Dict:
       # PreTrainedTokenizerFast doesn't have tokenizer_file in its signature
       pass
    def 		_lowerCamelCase      (	self			:       Any		)						->    Dict:
       _lowercase							     =       self.tmpdirname
       # Here we want to test the 2 available tokenizers that use 2 different types of models: Unigram and WordLevel.
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
             try:
                _lowercase							     =       tempfile.mkdtemp()
                _lowercase							     =       self.rust_tokenizer_class.from_pretrained(_lowercase   ,						**_lowercase		)

                tokenizer.save_pretrained(self.tmpdirname		)
                super().test_training_new_tokenizer()
             finally:
                # Even if the test fails, we must be sure that the folder is deleted and that the default tokenizer
                # is restored
                shutil.rmtree(self.tmpdirname		)
                _lowercase							     =       tmpdirname_orig
    def 		_lowerCamelCase      (	self			:       List[str]		)						->    Optional[int]:
       _lowercase							     =       self.tmpdirname
       # Here we want to test the 2 available tokenizers that use 2 different types of models: Unigram and WordLevel.
       for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""		):
             try:
                _lowercase							     =       tempfile.mkdtemp()
                _lowercase							     =       self.rust_tokenizer_class.from_pretrained(_lowercase   ,						**_lowercase		)

                tokenizer.save_pretrained(self.tmpdirname		)
                super().test_training_new_tokenizer_with_special_tokens_change()
             finally:
                # Even if the test fails, we must be sure that the folder is deleted and that the default tokenizer
                # is restored
                shutil.rmtree(self.tmpdirname		)
                _lowercase							     =       tmpdirname_orig




    def 		_lowerCamelCase      (	self			:       Tuple		)						->    Tuple:
       _lowercase							     =       self.rust_tokenizer_class.from_pretrained(self.bytelevel_bpe_model_name		)

       _lowercase							     =       ("a" for _ in range(1_0_0_0		))
       _lowercase							     =       tokenizer.train_new_from_iterator(text_iterator=_lowercase   ,						length=1_0_0_0   ,						vocab_size=5_0		)

       _lowercase							     =       new_tokenizer.encode("a🤗"		)
       self.assertEqual(_lowercase   ,						[6_4, 1_7_2, 2_5_3, 9_7, 2_4_5]		)
@require_tokenizers
class   UpperCAmelCase_	(				unittest.TestCase   ):
    def 		_lowerCamelCase      (	self			:       Dict		)						->    Optional[Any]:
       _lowercase							     =       AutoTokenizer.from_pretrained("bert-base-cased"		)
       _lowercase							     =       json.loads(tokenizer._tokenizer.to_str()		)
       _lowercase							     =       len(_lowercase		)

       with tempfile.TemporaryDirectory() as tmp_dir:
          # Hack to save this in the tokenizer_config.json
          _lowercase							     =       ["tokenizer.4.0.0.json"]
          tokenizer.save_pretrained(_lowercase		)
          json.dump(_lowercase   ,						open(os.path.join(_lowercase   ,						"tokenizer.4.0.0.json"		)   ,						"w"		)		)

          # This should pick the new tokenizer file as the version of Transformers is > 4.0.0
          _lowercase							     =       AutoTokenizer.from_pretrained(_lowercase		)
          self.assertEqual(len(_lowercase		)   ,						len(_lowercase		) + 1		)
          _lowercase							     =       json.loads(new_tokenizer._tokenizer.to_str()		)
          self.assertIn("huggingface"   ,						json_tokenizer["model"]["vocab"]		)

          # Will need to be adjusted if we reach v42 and this test is still here.
          # Should pick the old tokenizer file as the version of Transformers is < 4.0.0
          shutil.move(os.path.join(_lowercase   ,						"tokenizer.4.0.0.json"		)   ,						os.path.join(_lowercase   ,						"tokenizer.42.0.0.json"		)		)
          _lowercase							     =       ["tokenizer.42.0.0.json"]
          tokenizer.save_pretrained(_lowercase		)
          _lowercase							     =       AutoTokenizer.from_pretrained(_lowercase		)
          self.assertEqual(len(_lowercase		)   ,						len(_lowercase		)		)
          _lowercase							     =       json.loads(new_tokenizer._tokenizer.to_str()		)
          self.assertNotIn("huggingface"   ,						json_tokenizer["model"]["vocab"]		)




    def 		_lowerCamelCase      (	self			:       Tuple		)						->    str:
       # This repo has two tokenizer files, one for v4.0.0 and above with an added token, one for versions lower.
       _lowercase							     =       "hf-internal-testing/test-two-tokenizers"

       # This should pick the new tokenizer file as the version of Transformers is > 4.0.0
       _lowercase							     =       AutoTokenizer.from_pretrained(_lowercase		)
       self.assertEqual(len(_lowercase		)   ,						2_8_9_9_7		)
       _lowercase							     =       json.loads(tokenizer._tokenizer.to_str()		)
       self.assertIn("huggingface"   ,						json_tokenizer["model"]["vocab"]		)

       # Testing an older version by monkey-patching the version in the module it's used.
       import transformers as old_transformers

       _lowercase							     =       "3.0.0"
       _lowercase							     =       old_transformers.models.auto.AutoTokenizer.from_pretrained(_lowercase		)
       self.assertEqual(len(_lowercase		)   ,						2_8_9_9_6		)
       _lowercase							     =       json.loads(old_tokenizer._tokenizer.to_str()		)
       self.assertNotIn("huggingface"   ,						json_tokenizer["model"]["vocab"]		)
@require_tokenizers
class   UpperCAmelCase_	(				unittest.TestCase   ):
    def 		_lowerCamelCase      (	self			:       Optional[int]		)						->    Optional[Any]:
       # See https://github.com/huggingface/transformers/pull/12550
       # and https://github.com/huggingface/tokenizers/issues/537
       _lowercase							     =       PreTrainedTokenizerFast.from_pretrained("robot-test/dummy-tokenizer-wordlevel"		)
       _lowercase							     =       "The Matrix is a 1999 science fiction action film."

       with concurrent.futures.ThreadPoolExecutor() as executor:
          _lowercase							     =       [executor.submit(self.fetch   ,						_lowercase   ,						_lowercase		) for i in range(1_0		)]
          _lowercase							     =       [future.result() for future in futures]
          self.assertEqual(_lowercase   ,						[[1, 1_0, 0, 8, 0, 1_8, 0, 0, 0, 2] for i in range(1_0		)]		)




    def 		_lowerCamelCase      (	self			:       Optional[int]   ,						_lowercase			:       List[Any]   ,						_lowercase			:       List[Any]		)						->    int:
       return tokenizer.encode(_lowercase   ,						truncation="longest_first"   ,						padding="longest"		)
"""simple docstring"""


from .number_theory.prime_numbers import next_prime
class   UpperCAmelCase_	:
    def __init__(	self			:       str   ,						_lowercase			:       int   ,						_lowercase			:       int | None = None   ,						_lowercase			:       float | None = None   ,						)						->    None:
       _lowercase							     =       size_table
       _lowercase							     =       [None] * self.size_table
       _lowercase							     =       0.75 if lim_charge is None else lim_charge
       _lowercase							     =       1 if charge_factor is None else charge_factor
       _lowercase							     =       []
       _lowercase							     =       {}
    def 		_lowerCamelCase      (	self			:       Any		)						->    Optional[Any]:
       return self._keys
    def 		_lowerCamelCase      (	self			:       Dict		)						->    Dict:
       return sum(1 for slot in self.values if slot is not None		) / (
           self.size_table * self.charge_factor
       )
    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       List[str]		)						->    str:
       return key % self.size_table
    def 		_lowerCamelCase      (	self			:       Any   ,						_lowercase			:       Union[str, Any]		)						->    Optional[Any]:
       print(f"""step {step_ord}"""		)
       print(list(range(len(self.values		)		)		)		)
       print(self.values		)
    def 		_lowerCamelCase      (	self			:       str   ,						_lowercase			:       List[Any]		)						->    List[Any]:
       _lowercase							     =       1
       _lowercase							     =       values
       for value in values:
          self.insert_data(_lowercase		)
          self._step_by_step(_lowercase		)
          i += 1
    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       Optional[int]   ,						_lowercase			:       Union[str, Any]		)						->    List[Any]:
       _lowercase							     =       data
       _lowercase							     =       data
    def 		_lowerCamelCase      (	self			:       int   ,						_lowercase			:       Optional[Any]   ,						_lowercase			:       Tuple=None		)						->    Any:
       _lowercase							     =       self.hash_function(key + 1		)

       while self.values[new_key] is not None and self.values[new_key] != key:
          if self.values.count(_lowercase		) > 0:
             _lowercase							     =       self.hash_function(new_key + 1		)
          else:
             _lowercase							     =       None
             break

       return new_key
    def 		_lowerCamelCase      (	self			:       str		)						->    Any:
       _lowercase							     =       [value for value in self.values if value is not None]
       _lowercase							     =       next_prime(self.size_table   ,						factor=2		)
       self._keys.clear()
       _lowercase							     =       [None] * self.size_table  # hell's pointers D: don't DRY ;/
       for value in survivor_values:
          self.insert_data(_lowercase		)




    def 		_lowerCamelCase      (	self			:       Union[str, Any]   ,						_lowercase			:       Tuple		)						->    Optional[int]:
       _lowercase							     =       self.hash_function(_lowercase		)

       if self.values[key] is None:
          self._set_value(_lowercase   ,						_lowercase		)

       elif self.values[key] == data:
          pass

       else:
          _lowercase							     =       self._collision_resolution(_lowercase   ,						_lowercase		)
          if collision_resolution is not None:
             self._set_value(_lowercase   ,						_lowercase		)
          else:
             self.rehashing()
             self.insert_data(_lowercase		)