





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
      lowercase_					     =	"""pt"""
elif is_tf_available():
      lowercase_					     =	"""tf"""
else:
      lowercase_					     =	"""jax"""
class        SCREAMING_SNAKE_CASE     (__A    ,			unittest.TestCase   ):
   _UpperCamelCase					:	Union[str, Any]				      = ByTaTokenizer
   _UpperCamelCase					:	str				      = False


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





       """simple docstring"""







       super().setUp()
       lowercase__			    =						ByTaTokenizer()
       tokenizer.save_pretrained(self.tmpdirname )


   @cached_property
   def  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     List[Any]:





       """simple docstring"""







       return ByTaTokenizer.from_pretrained('google/byt5-small' )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any]    ,  **a    :       Optional[int] )->     List[str]:





       """simple docstring"""







       return self.tokenizer_class.from_pretrained(self.tmpdirname    ,  **UpperCamelCase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int]    ,  a    :       int    ,  a    :       Tuple=False    ,  a    :       Union[str, Any]=20    ,  a    :       Tuple=5 )->     Union[str, Any]:





       """simple docstring"""







       lowercase__			    =						[]
       for i in range(len(UpperCamelCase__ ) ):
           try:
               lowercase__			    =						tokenizer.decode([i]    ,  clean_up_tokenization_spaces=UpperCamelCase__ )
           except UnicodeDecodeError:
               pass
           toks.append((i, tok) )

       lowercase__			    =						list(filter(lambda a : re.match(R'^[ a-zA-Z]+$'    ,  t[1] )    ,  UpperCamelCase__ ) )
       lowercase__			    =						list(filter(lambda a : [t[0]] == tokenizer.encode(t[1]    ,  add_special_tokens=UpperCamelCase__ )    ,  UpperCamelCase__ ) )
       if max_length is not None and len(UpperCamelCase__ ) > max_length:
           lowercase__			    =						toks[:max_length]
       if min_length is not None and len(UpperCamelCase__ ) < min_length and len(UpperCamelCase__ ) > 0:
           while len(UpperCamelCase__ ) < min_length:
               lowercase__			    =						toks + toks
        # toks_str = [t[1] for t in toks]
       lowercase__			    =						[t[0] for t in toks]

       # Ensure consistency
       lowercase__			    =						tokenizer.decode(UpperCamelCase__    ,  clean_up_tokenization_spaces=UpperCamelCase__ )
       if " " not in output_txt and len(UpperCamelCase__ ) > 1:
           lowercase__			    =						(
               tokenizer.decode([toks_ids[0]]    ,  clean_up_tokenization_spaces=UpperCamelCase__ )
               + ' '
               + tokenizer.decode(toks_ids[1:]    ,  clean_up_tokenization_spaces=UpperCamelCase__ )
           )
       if with_prefix_space:
           lowercase__			    =						' ' + output_txt
       lowercase__			    =						tokenizer.encode(UpperCamelCase__    ,  add_special_tokens=UpperCamelCase__ )
       return output_txt, output_ids


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     str:





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						tokenizer(['hi</s>', 'I went to the gym</s>', '</s>'] )
       lowercase__			    =						tokenizer(['hi', 'I went to the gym', ''] )
       self.assertListEqual(batch_with_eos_added['input_ids']    ,  batch_without_eos_added['input_ids'] )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     int:





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						'Unicode €.'
       lowercase__			    =						tokenizer(UpperCamelCase__ )
       lowercase__			    =						[88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
       self.assertEqual(encoded['input_ids']    ,  UpperCamelCase__ )

       # decoding
       lowercase__			    =						tokenizer.decode(UpperCamelCase__ )
       self.assertEqual(UpperCamelCase__    ,  'Unicode €.</s>' )

       lowercase__			    =						tokenizer('e è é ê ë' )
       lowercase__			    =						[104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
       self.assertEqual(encoded['input_ids']    ,  UpperCamelCase__ )
       # decoding
       lowercase__			    =						tokenizer.decode(UpperCamelCase__ )
       self.assertEqual(UpperCamelCase__    ,  'e è é ê ë</s>' )

       # encode/decode, but with `encode` instead of `__call__`
       self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë' ) )    ,  'e è é ê ë</s>' )


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





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						['A long paragraph for summarization.', 'Another paragraph for summarization.']
       # fmt: off
       lowercase__			    =						[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
       # fmt: on
       lowercase__			    =						tokenizer(UpperCamelCase__    ,  padding=UpperCamelCase__    ,  return_tensors=UpperCamelCase__ )
       self.assertIsInstance(UpperCamelCase__    ,  UpperCamelCase__ )

       if FRAMEWORK != "jax":
           lowercase__			    =						list(batch.input_ids.numpy()[0] )
       else:
           lowercase__			    =						list(batch.input_ids.tolist()[0] )

       self.assertListEqual(UpperCamelCase__    ,  UpperCamelCase__ )

       self.assertEqual((2, 37)    ,  batch.input_ids.shape )
       self.assertEqual((2, 37)    ,  batch.attention_mask.shape )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[int] )->     Any:





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						['A long paragraph for summarization.', 'Another paragraph for summarization.']
       lowercase__			    =						tokenizer(UpperCamelCase__    ,  padding=UpperCamelCase__    ,  return_tensors=UpperCamelCase__ )
       # check if input_ids are returned and no decoder_input_ids
       self.assertIn('input_ids'    ,  UpperCamelCase__ )
       self.assertIn('attention_mask'    ,  UpperCamelCase__ )
       self.assertNotIn('decoder_input_ids'    ,  UpperCamelCase__ )
       self.assertNotIn('decoder_attention_mask'    ,  UpperCamelCase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       str )->     Dict:





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						[
           'Summary of the text.',
           'Another summary.',
       ]
       lowercase__			    =						tokenizer(
           text_target=UpperCamelCase__    ,  max_length=32    ,  padding='max_length'    ,  truncation=UpperCamelCase__    ,  return_tensors=UpperCamelCase__ )
       self.assertEqual(32    ,  targets['input_ids'].shape[1] )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Tuple )->     Union[str, Any]:





       """simple docstring"""







       lowercase__			    =						self.ta_base_tokenizer
       lowercase__			    =						['A long paragraph for summarization. </s>']
       lowercase__			    =						['Summary of the text. </s>']
       # fmt: off
       lowercase__			    =						[68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
       lowercase__			    =						[86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
       # fmt: on

       lowercase__			    =						tokenizer(UpperCamelCase__    ,  text_target=UpperCamelCase__ )

       self.assertEqual(UpperCamelCase__    ,  batch['input_ids'][0] )
       self.assertEqual(UpperCamelCase__    ,  batch['labels'][0] )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Any )->     int:





       """simple docstring"""







       lowercase__			    =						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__			    =						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__			    =						tempfile.mkdtemp()

               lowercase__			    =						' He is very happy, UNwant\u00E9d,running'
               lowercase__			    =						tokenizer.encode(UpperCamelCase__    ,  add_special_tokens=UpperCamelCase__ )
               tokenizer.save_pretrained(UpperCamelCase__ )

               lowercase__			    =						tokenizer.__class__.from_pretrained(UpperCamelCase__ )
               lowercase__			    =						after_tokenizer.encode(UpperCamelCase__    ,  add_special_tokens=UpperCamelCase__ )
               self.assertListEqual(UpperCamelCase__    ,  UpperCamelCase__ )

               shutil.rmtree(UpperCamelCase__ )

       lowercase__			    =						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__			    =						tempfile.mkdtemp()

               lowercase__			    =						' He is very happy, UNwant\u00E9d,running'
               tokenizer.add_tokens(['bim', 'bambam'] )
               lowercase__			    =						tokenizer.additional_special_tokens
               additional_special_tokens.append('new_additional_special_token' )
               tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens} )
               lowercase__			    =						tokenizer.encode(UpperCamelCase__    ,  add_special_tokens=UpperCamelCase__ )
               tokenizer.save_pretrained(UpperCamelCase__ )

               lowercase__			    =						tokenizer.__class__.from_pretrained(UpperCamelCase__ )
               lowercase__			    =						after_tokenizer.encode(UpperCamelCase__    ,  add_special_tokens=UpperCamelCase__ )
               self.assertListEqual(UpperCamelCase__    ,  UpperCamelCase__ )
               self.assertIn('new_additional_special_token'    ,  after_tokenizer.additional_special_tokens )
               self.assertEqual(after_tokenizer.model_max_length    ,  42 )

               lowercase__			    =						tokenizer.__class__.from_pretrained(UpperCamelCase__    ,  model_max_length=43 )
               self.assertEqual(tokenizer.model_max_length    ,  43 )

               shutil.rmtree(UpperCamelCase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Tuple )->     Any:





       """simple docstring"""







       lowercase__			    =						[]
       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__			    =						json.load(UpperCamelCase__ )

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

               lowercase__			    =						[f"""<extra_id_{i}>""" for i in range(125 )]

               lowercase__			    =						added_tokens_extra_ids + [
                   'an_additional_special_token'
               ]
               lowercase__			    =						added_tokens_extra_ids + [
                   'an_additional_special_token'
               ]

               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__			    =						tokenizer_class.from_pretrained(
                   UpperCamelCase__    ,  )
               self.assertIn(
                   'an_additional_special_token'    ,  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(
                   ['an_additional_special_token']    ,  tokenizer_without_change_in_init.convert_ids_to_tokens(
                       tokenizer_without_change_in_init.convert_tokens_to_ids(['an_additional_special_token'] ) )    ,  )

               # Now we test that we can change the value of additional_special_tokens in the from_pretrained
               lowercase__			    =						added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'    ,  lstrip=UpperCamelCase__ )]
               lowercase__			    =						tokenizer_class.from_pretrained(
                   UpperCamelCase__    ,  additional_special_tokens=UpperCamelCase__    ,  )

               self.assertIn('a_new_additional_special_token'    ,  tokenizer.additional_special_tokens )
               self.assertEqual(
                   ['a_new_additional_special_token']    ,  tokenizer.convert_ids_to_tokens(
                       tokenizer.convert_tokens_to_ids(['a_new_additional_special_token'] ) )    ,  )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Union[str, Any] )->     int:





       """simple docstring"""







       lowercase__			    =						[]
       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__ )

               lowercase__			    =						tokenizer_class.from_pretrained(UpperCamelCase__ )

               self.assertTrue(tokenizer.decode([255] ) == '' )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     str:





       """simple docstring"""







       pass


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





       """simple docstring"""







       pass


   def  SCREAMING_SNAKE_CASE_							(					self    :       Dict )->     Tuple:





       """simple docstring"""







       pass


   def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     List[str]:





       """simple docstring"""







       pass


   def  SCREAMING_SNAKE_CASE_							(					self    :       int )->     Optional[Any]:





       """simple docstring"""







       lowercase__			    =						self.get_tokenizers(fast=UpperCamelCase__    ,  do_lower_case=UpperCamelCase__ )
       for tokenizer in tokenizers:
           with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
               lowercase__			    =						['t', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 'x', 't', '</s>']
               lowercase__			    =						tokenizer.convert_tokens_to_string(UpperCamelCase__ )

               self.assertIsInstance(UpperCamelCase__    ,  UpperCamelCase__ )


   def  SCREAMING_SNAKE_CASE_							(					self    :       Optional[Any] )->     Dict:





       """simple docstring"""







       lowercase__			    =						self.get_tokenizers()
       for tokenizer in tokenizers:
           with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
               lowercase__			    =						[
                   'bos_token',
                   'eos_token',
                   'unk_token',
                   'sep_token',
                   'pad_token',
                   'cls_token',
                   'mask_token',
               ]

               lowercase__			    =						0
               lowercase__			    =						tokenizer.convert_ids_to_tokens(
                   UpperCamelCase__    ,  skip_special_tokens=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' )    ,  [] )

               setattr(UpperCamelCase__    ,  'additional_special_tokens_ids'    ,  [token_id_to_test_setters] )
               self.assertListEqual(getattr(UpperCamelCase__    ,  'additional_special_tokens' )    ,  [token_to_test_setters] )
               self.assertListEqual(getattr(UpperCamelCase__    ,  'additional_special_tokens_ids' )    ,  [token_id_to_test_setters] )









from typing import TYPE_CHECKING

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


lowercase_					     =	{
    """configuration_squeezebert""": [
        """SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SqueezeBertConfig""",
        """SqueezeBertOnnxConfig""",
    ],
    """tokenization_squeezebert""": ["""SqueezeBertTokenizer"""],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_					     =	["""SqueezeBertTokenizerFast"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_					     =	[
          """SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """SqueezeBertForMaskedLM""",
          """SqueezeBertForMultipleChoice""",
          """SqueezeBertForQuestionAnswering""",
          """SqueezeBertForSequenceClassification""",
          """SqueezeBertForTokenClassification""",
          """SqueezeBertModel""",
          """SqueezeBertModule""",
          """SqueezeBertPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_squeezebert import (
          SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
          SqueezeBertConfig,
          SqueezeBertOnnxConfig,
      )
      from .tokenization_squeezebert import SqueezeBertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_squeezebert import (
                SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                SqueezeBertForMaskedLM,
                SqueezeBertForMultipleChoice,
                SqueezeBertForQuestionAnswering,
                SqueezeBertForSequenceClassification,
                SqueezeBertForTokenClassification,
                SqueezeBertModel,
                SqueezeBertModule,
                SqueezeBertPreTrainedModel,
            )

else:
      import sys

      lowercase_					     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


