


import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin






class      UpperCamelCase					(		lowercase__						,      unittest.TestCase     ):


   '''simple docstring'''







   lowercase					:	Optional[int]									=CanineTokenizer
   lowercase					:	Union[str, Any]									=False
   def 		UpperCamelCase  (     self		):
        super().setUp()
        lowercase_       :Union[str, Any]     =       CanineTokenizer()
        tokenizer.save_pretrained(self.tmpdirname		)
   @cached_property
   def 		UpperCamelCase  (     self		):
        return CanineTokenizer.from_pretrained('''google/canine-s'''		)
   def 		UpperCamelCase  (     self   ,							**UpperCamelCase_		):
        lowercase_       :int     =       self.tokenizer_class.from_pretrained(self.tmpdirname   ,							**UpperCamelCase_		)
        lowercase_       :int     =       1024
        return tokenizer
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Optional[Any]     =       self.canine_tokenizer
        lowercase_       :int     =       ['''Life is like a box of chocolates.''', '''You never know what you\'re gonna get.''']
        # fmt: off
        lowercase_       :str     =       [5_7344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 5_7345, 0, 0, 0, 0]
        # fmt: on
        lowercase_       :List[Any]     =       tokenizer(UpperCamelCase_   ,							padding=UpperCamelCase_   ,							return_tensors='''pt'''		)
        self.assertIsInstance(UpperCamelCase_   ,							UpperCamelCase_		)

        lowercase_       :List[Any]     =       list(batch.input_ids.numpy()[0]		)

        self.assertListEqual(UpperCamelCase_   ,							UpperCamelCase_		)

        self.assertEqual((2, 39)   ,							batch.input_ids.shape		)
        self.assertEqual((2, 39)   ,							batch.attention_mask.shape		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :List[Any]     =       self.canine_tokenizer
        lowercase_       :Dict     =       ['''Once there was a man.''', '''He wrote a test in HuggingFace Tranformers.''']
        lowercase_       :Tuple     =       tokenizer(UpperCamelCase_   ,							padding=UpperCamelCase_   ,							return_tensors='''pt'''		)
        # check if input_ids, attention_mask and token_type_ids are returned
        self.assertIn('''input_ids'''   ,							UpperCamelCase_		)
        self.assertIn('''attention_mask'''   ,							UpperCamelCase_		)
        self.assertIn('''token_type_ids'''   ,							UpperCamelCase_		)
   @require_torch
   def 		UpperCamelCase  (     self		):
        lowercase_       :Optional[Any]     =       self.canine_tokenizer
        lowercase_       :str     =       [
            '''What\'s the weater?''',
            '''It\'s about 25 degrees.''',
        ]
        lowercase_       :Tuple     =       tokenizer(
            text_target=UpperCamelCase_   ,							max_length=32   ,							padding='''max_length'''   ,							truncation=UpperCamelCase_   ,							return_tensors='''pt'''		)
        self.assertEqual(32   ,							targets['''input_ids'''].shape[1]		)
   def 		UpperCamelCase  (     self		):
        # safety check on max_len default value so we are sure the test works
        lowercase_       :str     =       self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  self.assertNotEqual(tokenizer.model_max_length   ,							42		)

        # Now let's start the test
        lowercase_       :int     =       self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  # Isolate this from the other tests because we save additional tokens/etc
                  lowercase_       :int     =       tempfile.mkdtemp()

                  lowercase_       :str     =       ''' He is very happy, UNwant\u00E9d,running'''
                  lowercase_       :str     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  tokenizer.save_pretrained(UpperCamelCase_		)

                  lowercase_       :Tuple     =       tokenizer.__class__.from_pretrained(UpperCamelCase_		)
                  lowercase_       :List[Any]     =       after_tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  self.assertListEqual(UpperCamelCase_   ,							UpperCamelCase_		)

                  shutil.rmtree(UpperCamelCase_		)

        lowercase_       :Union[str, Any]     =       self.get_tokenizers(model_max_length=42		)
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  # Isolate this from the other tests because we save additional tokens/etc
                  lowercase_       :List[Any]     =       tempfile.mkdtemp()

                  lowercase_       :List[Any]     =       ''' He is very happy, UNwant\u00E9d,running'''

                  lowercase_       :List[str]     =       tokenizer.additional_special_tokens

                  # We can add a new special token for Canine as follows:
                  lowercase_       :Optional[int]     =       chr(0XE007		)
                  additional_special_tokens.append(UpperCamelCase_		)
                  tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}		)
                  lowercase_       :List[Any]     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  tokenizer.save_pretrained(UpperCamelCase_		)

                  lowercase_       :Dict     =       tokenizer.__class__.from_pretrained(UpperCamelCase_		)
                  lowercase_       :Optional[int]     =       after_tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  self.assertListEqual(UpperCamelCase_   ,							UpperCamelCase_		)
                  self.assertIn(UpperCamelCase_   ,							after_tokenizer.additional_special_tokens		)
                  self.assertEqual(after_tokenizer.model_max_length   ,							42		)

                  lowercase_       :Any     =       tokenizer.__class__.from_pretrained(UpperCamelCase_   ,							model_max_length=43		)
                  self.assertEqual(tokenizer.model_max_length   ,							43		)

                  shutil.rmtree(UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :int     =       self.get_tokenizers(do_lower_case=UpperCamelCase_		)
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  lowercase_    ,      lowercase_       :Optional[int]     =       self.get_clean_sequence(UpperCamelCase_		)

                  # a special token for Canine can be defined as follows:
                  lowercase_       :List[Any]     =       0XE005
                  lowercase_       :Any     =       chr(UpperCamelCase_		)

                  tokenizer.add_special_tokens({'''cls_token''': special_token}		)
                  lowercase_       :Tuple     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  self.assertEqual(len(UpperCamelCase_		)   ,							1		)

                  lowercase_       :Tuple     =       tokenizer.decode(ids + encoded_special_token   ,							clean_up_tokenization_spaces=UpperCamelCase_		)
                  lowercase_       :Tuple     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)

                  lowercase_       :Any     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  lowercase_       :Optional[Any]     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  self.assertEqual(UpperCamelCase_   ,							input_encoded + special_token_id		)

                  lowercase_       :int     =       tokenizer.decode(UpperCamelCase_   ,							skip_special_tokens=UpperCamelCase_		)
                  self.assertTrue(special_token not in decoded		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :str     =       self.get_tokenizers(do_lower_case=UpperCamelCase_		)
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  lowercase_       :Optional[int]     =       chr(0XE005		)
                  lowercase_       :Tuple     =       chr(0XE006		)

                  # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
                  tokenizer.add_tokens([SPECIAL_TOKEN_1]   ,							special_tokens=UpperCamelCase_		)
                  # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
                  # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
                  tokenizer.add_special_tokens({'''additional_special_tokens''': [SPECIAL_TOKEN_2]}		)

                  lowercase_       :Any     =       tokenizer.tokenize(UpperCamelCase_		)
                  lowercase_       :str     =       tokenizer.tokenize(UpperCamelCase_		)

                  self.assertEqual(len(UpperCamelCase_		)   ,							1		)
                  self.assertEqual(len(UpperCamelCase_		)   ,							1		)
                  self.assertEqual(token_a[0]   ,							UpperCamelCase_		)
                  self.assertEqual(token_a[0]   ,							UpperCamelCase_		)
   @require_tokenizers
   def 		UpperCamelCase  (     self		):
        lowercase_       :Optional[int]     =       self.get_tokenizers(do_lower_case=UpperCamelCase_		)
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  # a special token for Canine can be defined as follows:
                  lowercase_       :int     =       0XE006
                  lowercase_       :Optional[Any]     =       chr(UpperCamelCase_		)

                  lowercase_       :Optional[int]     =       AddedToken(UpperCamelCase_   ,							lstrip=UpperCamelCase_		)
                  tokenizer.add_special_tokens({'''additional_special_tokens''': [new_token]}		)

                  with tempfile.TemporaryDirectory() as tmp_dir_name:
                       tokenizer.save_pretrained(UpperCamelCase_		)
                       tokenizer.from_pretrained(UpperCamelCase_		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Dict     =       []
        if self.test_slow_tokenizer:
             tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())		)

        if self.test_rust_tokenizer:
             tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())		)

        for tokenizer_class, tokenizer_utils in tokenizer_list:
             with tempfile.TemporaryDirectory() as tmp_dir:
                  tokenizer_utils.save_pretrained(UpperCamelCase_		)

                  with open(os.path.join(UpperCamelCase_   ,							'''special_tokens_map.json'''		)   ,							encoding='''utf-8'''		) as json_file:
                       lowercase_       :Dict     =       json.load(UpperCamelCase_		)

                  with open(os.path.join(UpperCamelCase_   ,							'''tokenizer_config.json'''		)   ,							encoding='''utf-8'''		) as json_file:
                       lowercase_       :int     =       json.load(UpperCamelCase_		)

                  # a special token for Canine can be defined as follows:
                  lowercase_       :List[Any]     =       0XE006
                  lowercase_       :List[str]     =       chr(UpperCamelCase_		)

                  lowercase_       :List[Any]     =       [new_token_a]
                  lowercase_       :List[str]     =       [new_token_a]

                  with open(os.path.join(UpperCamelCase_   ,							'''special_tokens_map.json'''		)   ,							'''w'''   ,							encoding='''utf-8'''		) as outfile:
                       json.dump(UpperCamelCase_   ,							UpperCamelCase_		)
                  with open(os.path.join(UpperCamelCase_   ,							'''tokenizer_config.json'''		)   ,							'''w'''   ,							encoding='''utf-8'''		) as outfile:
                       json.dump(UpperCamelCase_   ,							UpperCamelCase_		)

                  # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                  # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                  # "special_tokens_map.json" files
                  lowercase_       :Optional[int]     =       tokenizer_class.from_pretrained(UpperCamelCase_   ,							extra_ids=0		)
                  self.assertIn(UpperCamelCase_   ,							tokenizer_without_change_in_init.additional_special_tokens		)
                  # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                  self.assertEqual(
                      [new_token_a]   ,							tokenizer_without_change_in_init.convert_ids_to_tokens(
                          tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]		)		)   ,							)

                  lowercase_       :str     =       0XE007
                  lowercase_       :Any     =       chr(UpperCamelCase_		)
                  # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                  lowercase_       :Optional[Any]     =       [AddedToken(UpperCamelCase_   ,							lstrip=UpperCamelCase_		)]
                  lowercase_       :Union[str, Any]     =       tokenizer_class.from_pretrained(
                      UpperCamelCase_   ,							additional_special_tokens=UpperCamelCase_   ,							extra_ids=0		)

                  self.assertIn(UpperCamelCase_   ,							tokenizer.additional_special_tokens		)
                  # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
                  self.assertEqual(
                      [new_token_a]   ,							tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]		)		)		)
   @require_tokenizers
   def 		UpperCamelCase  (     self		):
        lowercase_       :Dict     =       self.get_tokenizers(do_lower_case=UpperCamelCase_		)
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  lowercase_       :str     =       '''hello world'''
                  if self.space_between_special_tokens:
                       lowercase_       :Tuple     =       '''[CLS] hello world [SEP]'''
                  else:
                       lowercase_       :Optional[int]     =       input
                  lowercase_       :Tuple     =       tokenizer.encode(UpperCamelCase_   ,							add_special_tokens=UpperCamelCase_		)
                  lowercase_       :int     =       tokenizer.decode(UpperCamelCase_   ,							spaces_between_special_tokens=self.space_between_special_tokens		)
                  self.assertIn(UpperCamelCase_   ,							[output, output.lower()]		)
   def 		UpperCamelCase  (     self		):
        lowercase_       :Dict     =       self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(f"{tokenizer.__class__.__name__}"		):
                  lowercase_       :int     =       [
                      '''bos_token''',
                      '''eos_token''',
                      '''unk_token''',
                      '''sep_token''',
                      '''pad_token''',
                      '''cls_token''',
                      '''mask_token''',
                  ]

        lowercase_       :int     =       '''a'''
        lowercase_       :Union[str, Any]     =       ord(UpperCamelCase_		)

        for attr in attributes_list:
             setattr(UpperCamelCase_   ,							attr + '''_id'''   ,							UpperCamelCase_		)
             self.assertEqual(getattr(UpperCamelCase_   ,							UpperCamelCase_		)   ,							UpperCamelCase_		)
             self.assertEqual(getattr(UpperCamelCase_   ,							attr + '''_id'''		)   ,							UpperCamelCase_		)

             setattr(UpperCamelCase_   ,							attr + '''_id'''   ,							UpperCamelCase_		)
             self.assertEqual(getattr(UpperCamelCase_   ,							UpperCamelCase_		)   ,							UpperCamelCase_		)
             self.assertEqual(getattr(UpperCamelCase_   ,							attr + '''_id'''		)   ,							UpperCamelCase_		)

        setattr(UpperCamelCase_   ,							'''additional_special_tokens_ids'''   ,							[]		)
        self.assertListEqual(getattr(UpperCamelCase_   ,							'''additional_special_tokens'''		)   ,							[]		)
        self.assertListEqual(getattr(UpperCamelCase_   ,							'''additional_special_tokens_ids'''		)   ,							[]		)

        lowercase_       :Union[str, Any]     =       0XE006
        lowercase_       :Dict     =       chr(UpperCamelCase_		)
        setattr(UpperCamelCase_   ,							'''additional_special_tokens_ids'''   ,							[additional_special_token_id]		)
        self.assertListEqual(getattr(UpperCamelCase_   ,							'''additional_special_tokens'''		)   ,							[additional_special_token]		)
        self.assertListEqual(getattr(UpperCamelCase_   ,							'''additional_special_tokens_ids'''		)   ,							[additional_special_token_id]		)
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass
   def 		UpperCamelCase  (     self		):
        pass




   def 		UpperCamelCase  (     self		):
        pass





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE       :		str         =				{
    "configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
    "tokenization_tapas": ["TapasTokenizer"],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE       :		Dict         =				[
       "TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TapasForMaskedLM",
       "TapasForQuestionAnswering",
       "TapasForSequenceClassification",
       "TapasModel",
       "TapasPreTrainedModel",
       "load_tf_weights_in_tapas",
   ]
try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   SCREAMING_SNAKE_CASE       :		str         =				[
       "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
       "TFTapasForMaskedLM",
       "TFTapasForQuestionAnswering",
       "TFTapasForSequenceClassification",
       "TFTapasModel",
       "TFTapasPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
   from .tokenization_tapas import TapasTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tapas import (
          TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
          TapasForMaskedLM,
          TapasForQuestionAnswering,
          TapasForSequenceClassification,
          TapasModel,
          TapasPreTrainedModel,
          load_tf_weights_in_tapas,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_tapas import (
          TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFTapasForMaskedLM,
          TFTapasForQuestionAnswering,
          TFTapasForSequenceClassification,
          TFTapasModel,
          TFTapasPreTrainedModel,
      )


else:
   import sys

   SCREAMING_SNAKE_CASE       :		Union[str, Any]         =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

