
"""simple docstring"""






import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 				a__					(						A__   ,							unittest.TestCase       ):
     UpperCAmelCase__         =      LEDTokenizer
     UpperCAmelCase__         =      LEDTokenizerFast
     UpperCAmelCase__         =      True



     def  lowerCamelCase_						(							self :Any   ):







      '''simple docstring'''



      super().setUp()
      UpperCamelCase_     :					str   	=[
          'l',
          'o',
          'w',
          'e',
          'r',
          's',
          't',
          'i',
          'd',
          'n',
          '\u0120',
          '\u0120l',
          '\u0120n',
          '\u0120lo',
          '\u0120low',
          'er',
          '\u0120lowest',
          '\u0120newer',
          '\u0120wider',
          '<unk>',
      ]
      UpperCamelCase_     :					Any   	=dict(zip(_lowerCamelCase      ,  range(len(_lowerCamelCase   )   )   )   )
      UpperCamelCase_     :					Optional[int]   	=['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
      UpperCamelCase_     :					Any   	={'unk_token': '<unk>'}

      UpperCamelCase_     :					str   	=os.path.join(self.tmpdirname      ,  VOCAB_FILES_NAMES['vocab_file']   )
      UpperCamelCase_     :					List[str]   	=os.path.join(self.tmpdirname      ,  VOCAB_FILES_NAMES['merges_file']   )
      with open(self.vocab_file      ,  'w'      ,  encoding='utf-8'   ) as fp:
       fp.write(json.dumps(_lowerCamelCase   ) + '\n'   )
      with open(self.merges_file      ,  'w'      ,  encoding='utf-8'   ) as fp:
       fp.write('\n'.join(_lowerCamelCase   )   )



     def  lowerCamelCase_						(							self :Any      ,  **_lowerCamelCase :List[Any]   ):







      '''simple docstring'''



      kwargs.update(self.special_tokens_map   )
      return self.tokenizer_class.from_pretrained(self.tmpdirname      ,  **_lowerCamelCase   )



     def  lowerCamelCase_						(							self :Dict      ,  **_lowerCamelCase :Union[str, Any]   ):







      '''simple docstring'''



      kwargs.update(self.special_tokens_map   )
      return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,  **_lowerCamelCase   )



     def  lowerCamelCase_						(							self :Optional[int]      ,  _lowerCamelCase :Optional[Any]   ):







      '''simple docstring'''



      return "lower newer", "lower newer"



     @cached_property
     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      return LEDTokenizer.from_pretrained('allenai/led-base-16384'   )



     @cached_property
     def  lowerCamelCase_						(							self :List[Any]   ):







      '''simple docstring'''



      return LEDTokenizerFast.from_pretrained('allenai/led-base-16384'   )



     @require_torch
     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					Union[str, Any]   	=['A long paragraph for summarization.', 'Another paragraph for summarization.']
      UpperCamelCase_     :					List[str]   	=[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					Union[str, Any]   	=tokenizer(_lowerCamelCase      ,  max_length=len(_lowerCamelCase   )      ,  padding=_lowerCamelCase      ,  return_tensors='pt'   )
       self.assertIsInstance(_lowerCamelCase      ,  _lowerCamelCase   )

       self.assertEqual((2, 9)      ,  batch.input_ids.shape   )
       self.assertEqual((2, 9)      ,  batch.attention_mask.shape   )
       UpperCamelCase_     :					str   	=batch.input_ids.tolist()[0]
       self.assertListEqual(_lowerCamelCase      ,  _lowerCamelCase   )



     @require_torch
     def  lowerCamelCase_						(							self :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[str]   	=['A long paragraph for summarization.', 'Another paragraph for summarization.']
      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					List[Any]   	=tokenizer(_lowerCamelCase      ,  padding=_lowerCamelCase      ,  return_tensors='pt'   )
       self.assertIn('input_ids'      ,  _lowerCamelCase   )
       self.assertIn('attention_mask'      ,  _lowerCamelCase   )
       self.assertNotIn('labels'      ,  _lowerCamelCase   )
       self.assertNotIn('decoder_attention_mask'      ,  _lowerCamelCase   )



     @require_torch
     def  lowerCamelCase_						(							self :Optional[Any]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=[
          'Summary of the text.',
          'Another summary.',
      ]
      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					Optional[Any]   	=tokenizer(text_target=_lowerCamelCase      ,  max_length=32      ,  padding='max_length'      ,  return_tensors='pt'   )
       self.assertEqual(32      ,  targets['input_ids'].shape[1]   )



     @require_torch
     def  lowerCamelCase_						(							self :Union[str, Any]   ):







      '''simple docstring'''



      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					Tuple   	=tokenizer(
           ['I am a small frog' * 1_024, 'I am a small frog']      ,  padding=_lowerCamelCase      ,  truncation=_lowerCamelCase      ,  return_tensors='pt'   )
       self.assertIsInstance(_lowerCamelCase      ,  _lowerCamelCase   )
       self.assertEqual(batch.input_ids.shape      ,  (2, 5_122)   )



     @require_torch
     def  lowerCamelCase_						(							self :Any   ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=['A long paragraph for summarization.']
      UpperCamelCase_     :					List[Any]   	=[
          'Summary of the text.',
      ]
      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					Tuple   	=tokenizer(_lowerCamelCase      ,  return_tensors='pt'   )
       UpperCamelCase_     :					Dict   	=tokenizer(text_target=_lowerCamelCase      ,  return_tensors='pt'   )
       UpperCamelCase_     :					Optional[Any]   	=inputs['input_ids']
       UpperCamelCase_     :					Any   	=targets['input_ids']
       self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()   )
       self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()   )
       self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()   )
       self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()   )



     @require_torch
     def  lowerCamelCase_						(							self :str   ):







      '''simple docstring'''



      for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
       UpperCamelCase_     :					Any   	=['Summary of the text.', 'Another summary.']
       UpperCamelCase_     :					Optional[int]   	=[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

       UpperCamelCase_     :					Dict   	=tokenizer(_lowerCamelCase      ,  padding=_lowerCamelCase   )
       UpperCamelCase_     :					Dict   	=[[0] * len(_lowerCamelCase   ) for x in encoded_output['input_ids']]
       UpperCamelCase_     :					int   	=tokenizer.pad(_lowerCamelCase   )
       self.assertSequenceEqual(outputs['global_attention_mask']      ,  _lowerCamelCase   )



     def  lowerCamelCase_						(							self :Tuple   ):







      '''simple docstring'''



      pass




     def  lowerCamelCase_						(							self :str   ):







      '''simple docstring'''



      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''   ):
        UpperCamelCase_     :					Any   	=self.rust_tokenizer_class.from_pretrained(_lowerCamelCase      ,  **_lowerCamelCase   )
        UpperCamelCase_     :					Tuple   	=self.tokenizer_class.from_pretrained(_lowerCamelCase      ,  **_lowerCamelCase   )
        UpperCamelCase_     :					Optional[int]   	='A, <mask> AllenNLP sentence.'
        UpperCamelCase_     :					Union[str, Any]   	=tokenizer_r.encode_plus(_lowerCamelCase      ,  add_special_tokens=_lowerCamelCase      ,  return_token_type_ids=_lowerCamelCase   )
        UpperCamelCase_     :					Any   	=tokenizer_p.encode_plus(_lowerCamelCase      ,  add_special_tokens=_lowerCamelCase      ,  return_token_type_ids=_lowerCamelCase   )
        self.assertEqual(sum(tokens_r['token_type_ids']   )      ,  sum(tokens_p['token_type_ids']   )   )
        self.assertEqual(
            sum(tokens_r['attention_mask']   ) / len(tokens_r['attention_mask']   )      ,  sum(tokens_p['attention_mask']   ) / len(tokens_p['attention_mask']   )      ,  )

        UpperCamelCase_     :					Dict   	=tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']   )
        UpperCamelCase_     :					Optional[int]   	=tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']   )
        self.assertSequenceEqual(tokens_p['input_ids']      ,  [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )
        self.assertSequenceEqual(tokens_r['input_ids']      ,  [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]   )

        self.assertSequenceEqual(
            _lowerCamelCase      ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )
        self.assertSequenceEqual(
            _lowerCamelCase      ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']   )


"""simple docstring"""






from typing import Dict, List, Optional

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__SCREAMING_SNAKE_CASE							=     logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE							=     {
    'nielsr/canine-s': 2_048,
}

# Unicode defines 1,114,112 total “codepoints”
__SCREAMING_SNAKE_CASE							=     1_114_112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
__SCREAMING_SNAKE_CASE							=     0

__SCREAMING_SNAKE_CASE							=     0XE_0_0_0
__SCREAMING_SNAKE_CASE							=     0XE_0_0_1
__SCREAMING_SNAKE_CASE							=     0XE_0_0_2
__SCREAMING_SNAKE_CASE							=     0XE_0_0_3
__SCREAMING_SNAKE_CASE							=     0XE_0_0_4

# Maps special codepoints to human-readable names.
__SCREAMING_SNAKE_CASE							=     {
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
__SCREAMING_SNAKE_CASE							=     {name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}





class 				a__					(						A__       ):
     UpperCAmelCase__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



     def __init__(							self :List[str]      ,  _lowerCamelCase :Optional[Any]=chr(_lowerCamelCase   )      ,  _lowerCamelCase :List[str]=chr(_lowerCamelCase   )      ,  _lowerCamelCase :Any=chr(_lowerCamelCase   )      ,  _lowerCamelCase :Optional[int]=chr(_lowerCamelCase   )      ,  _lowerCamelCase :Tuple=chr(_lowerCamelCase   )      ,  _lowerCamelCase :Union[str, Any]=chr(_lowerCamelCase   )      ,  _lowerCamelCase :str=False      ,  _lowerCamelCase :Union[str, Any]=2_048      ,  **_lowerCamelCase :Tuple      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else bos_token
      UpperCamelCase_     :					List[str]   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else eos_token
      UpperCamelCase_     :					List[str]   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else sep_token
      UpperCamelCase_     :					Tuple   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else cls_token
      UpperCamelCase_     :					Optional[int]   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      UpperCamelCase_     :					Dict   	=AddedToken(_lowerCamelCase      ,  lstrip=_lowerCamelCase      ,  rstrip=_lowerCamelCase   ) if isinstance(_lowerCamelCase      ,  _lowerCamelCase   ) else mask_token

      super().__init__(
          bos_token=_lowerCamelCase      ,  eos_token=_lowerCamelCase      ,  sep_token=_lowerCamelCase      ,  cls_token=_lowerCamelCase      ,  pad_token=_lowerCamelCase      ,  mask_token=_lowerCamelCase      ,  add_prefix_space=_lowerCamelCase      ,  model_max_length=_lowerCamelCase      ,  **_lowerCamelCase      ,  )

      # Creates a mapping for looking up the IDs of special symbols.
      UpperCamelCase_     :					Dict[str, int]   	={}
      for codepoint, name in SPECIAL_CODEPOINTS.items():
       UpperCamelCase_     :					List[str]   	=codepoint

      # Creates a mapping for looking up the string forms of special symbol IDs.
      UpperCamelCase_     :					Dict[int, str]   	={
          codepoint: name for name, codepoint in self._special_codepoints.items()
      }

      UpperCamelCase_     :					str   	=UNICODE_VOCAB_SIZE
      UpperCamelCase_     :					Any   	=len(self._special_codepoints   )



     @property
     def  lowerCamelCase_						(							self :List[Any]   ):







      '''simple docstring'''



      return self._unicode_vocab_size



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      return list(_lowerCamelCase   )



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      try:
       return ord(_lowerCamelCase   )
      except TypeError:
       raise ValueError(f'''invalid token: \'{token}\''''   )



     def  lowerCamelCase_						(							self :str      ,  _lowerCamelCase :int   ):







      '''simple docstring'''



      try:
       if index in SPECIAL_CODEPOINTS:
        return SPECIAL_CODEPOINTS[index]
       return chr(_lowerCamelCase   )
      except TypeError:
       raise ValueError(f'''invalid id: {index}'''   )



     def  lowerCamelCase_						(							self :List[Any]      ,  _lowerCamelCase :str   ):







      '''simple docstring'''



      return "".join(_lowerCamelCase   )



     def  lowerCamelCase_						(							self :Tuple      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=[self.sep_token_id]
      UpperCamelCase_     :					Tuple   	=[self.cls_token_id]

      UpperCamelCase_     :					List[str]   	=cls + token_ids_a + sep
      if token_ids_a is not None:
       result += token_ids_a + sep
      return result



     def  lowerCamelCase_						(							self :Union[str, Any]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None      ,  _lowerCamelCase :bool = False   ):







      '''simple docstring'''



      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=_lowerCamelCase      ,  token_ids_a=_lowerCamelCase      ,  already_has_special_tokens=_lowerCamelCase   )

      UpperCamelCase_     :					int   	=[1] + ([0] * len(_lowerCamelCase   )) + [1]
      if token_ids_a is not None:
       result += ([0] * len(_lowerCamelCase   )) + [1]
      return result



     def  lowerCamelCase_						(							self :List[str]      ,  _lowerCamelCase :List[int]      ,  _lowerCamelCase :Optional[List[int]] = None   ):







      '''simple docstring'''



      UpperCamelCase_     :					Dict   	=[self.sep_token_id]
      UpperCamelCase_     :					Optional[int]   	=[self.cls_token_id]

      UpperCamelCase_     :					Dict   	=len(cls + token_ids_a + sep   ) * [0]
      if token_ids_a is not None:
       result += len(token_ids_a + sep   ) * [1]
      return result




     def  lowerCamelCase_						(							self :Tuple      ,  _lowerCamelCase :str      ,  _lowerCamelCase :Optional[str] = None   ):







      '''simple docstring'''



      return ()
