

"""simple docstring"""






import json
import os
import re
import unittest

from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 	__UpperCamelCase    (    a__							,							unittest.TestCase						):
  _UpperCAmelCase          =		CodeGenTokenizer
  _UpperCAmelCase          =		CodeGenTokenizerFast
  _UpperCAmelCase          =		True
  _UpperCAmelCase          =		{"add_prefix_space": True}
  _UpperCAmelCase          =		False

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      _lowerCAmelCase       :   Tuple  =    [
          'l',
          'o',
          'w',
          'e',
          'r',
          's',
          't',
          'i',
          'd',
          'n',
          '\u0120',
          '\u0120l',
          '\u0120n',
          '\u0120lo',
          '\u0120low',
          'er',
          '\u0120lowest',
          '\u0120newer',
          '\u0120wider',
          '<unk>',
          '<|endoftext|>',
      ]
      _lowerCAmelCase       :   Dict  =    dict(zip(_A    ,range(len(_A      )      )      )      )
      _lowerCAmelCase       :   Optional[Any]  =    ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
      _lowerCAmelCase       :   Union[str, Any]  =    {'unk_token': '<unk>'}

      _lowerCAmelCase       :   str  =    os.path.join(self.tmpdirname    ,VOCAB_FILES_NAMES['vocab_file']      )
      _lowerCAmelCase       :   Dict  =    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(_A      ) + '\n'      )
      with open(self.merges_file    ,'w'    ,encoding='utf-8'      ) as fp:
          fp.write('\n'.join(_A      )      )

  def __lowerCamelCase		(		self    ,**_A      ):
      '''simple docstring'''

      kwargs.update(self.special_tokens_map      )
      return CodeGenTokenizer.from_pretrained(self.tmpdirname    ,**_A      )

  def __lowerCamelCase		(		self    ,**_A      ):
      '''simple docstring'''

      kwargs.update(self.special_tokens_map      )
      return CodeGenTokenizerFast.from_pretrained(self.tmpdirname    ,**_A      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Union[str, Any]  =    'lower newer'
      _lowerCAmelCase       :   int  =    'lower newer'
      return input_text, output_text

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[Any]  =    CodeGenTokenizer(self.vocab_file    ,self.merges_file    ,**self.special_tokens_map      )
      _lowerCAmelCase       :   List[Any]  =    'lower newer'
      _lowerCAmelCase       :   Optional[int]  =    ['\u0120low', 'er', '\u0120', 'n', 'e', 'w', 'er']
      _lowerCAmelCase       :   Any  =    tokenizer.tokenize(_A    ,add_prefix_space=_A      )
      self.assertListEqual(_A    ,_A      )

      _lowerCAmelCase       :   Any  =    tokens + [tokenizer.unk_token]
      _lowerCAmelCase       :   Optional[int]  =    [14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(_A      )    ,_A      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      if not self.test_rust_tokenizer:
          return

      _lowerCAmelCase       :   str  =    self.get_tokenizer()
      _lowerCAmelCase       :   Dict  =    self.get_rust_tokenizer(add_prefix_space=_A      )

      _lowerCAmelCase       :   Dict  =    'lower newer'

      # Testing tokenization
      _lowerCAmelCase       :   Any  =    tokenizer.tokenize(_A    ,add_prefix_space=_A      )
      _lowerCAmelCase       :   Optional[int]  =    rust_tokenizer.tokenize(_A      )
      self.assertListEqual(_A    ,_A      )

      # Testing conversion to ids without special tokens
      _lowerCAmelCase       :   Union[str, Any]  =    tokenizer.encode(_A    ,add_special_tokens=_A    ,add_prefix_space=_A      )
      _lowerCAmelCase       :   Optional[Any]  =    rust_tokenizer.encode(_A    ,add_special_tokens=_A      )
      self.assertListEqual(_A    ,_A      )

      # Testing conversion to ids with special tokens
      _lowerCAmelCase       :   Tuple  =    self.get_rust_tokenizer(add_prefix_space=_A      )
      _lowerCAmelCase       :   Optional[int]  =    tokenizer.encode(_A    ,add_prefix_space=_A      )
      _lowerCAmelCase       :   Union[str, Any]  =    rust_tokenizer.encode(_A      )
      self.assertListEqual(_A    ,_A      )

      # Testing the unknown token
      _lowerCAmelCase       :   List[str]  =    tokens + [rust_tokenizer.unk_token]
      _lowerCAmelCase       :   Tuple  =    [14, 15, 10, 9, 3, 2, 15, 19]
      self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(_A      )    ,_A      )

  def __lowerCamelCase		(		self    ,*_A    ,**_A      ):
      '''simple docstring'''

      pass

  def __lowerCamelCase		(		self    ,_A=15      ):
      '''simple docstring'''

      for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""      ):
              _lowerCAmelCase       :   Tuple  =    self.rust_tokenizer_class.from_pretrained(_A    ,**_A      )

              # Simple input
              _lowerCAmelCase       :   Dict  =    'This is a simple input'
              _lowerCAmelCase       :   Dict  =    ['This is a simple input 1', 'This is a simple input 2']
              _lowerCAmelCase       :   Any  =    ('This is a simple input', 'This is a pair')
              _lowerCAmelCase       :   int  =    [
                  ('This is a simple input 1', 'This is a simple input 2'),
                  ('This is a simple pair 1', 'This is a simple pair 2'),
              ]

              # Simple input tests
              self.assertRaises(_A    ,tokenizer_r.encode    ,_A    ,max_length=_A    ,padding='max_length'      )

              # Simple input
              self.assertRaises(_A    ,tokenizer_r.encode_plus    ,_A    ,max_length=_A    ,padding='max_length'      )

              # Simple input
              self.assertRaises(
                  _A    ,tokenizer_r.batch_encode_plus    ,_A    ,max_length=_A    ,padding='max_length'    ,)

              # Pair input
              self.assertRaises(_A    ,tokenizer_r.encode    ,_A    ,max_length=_A    ,padding='max_length'      )

              # Pair input
              self.assertRaises(_A    ,tokenizer_r.encode_plus    ,_A    ,max_length=_A    ,padding='max_length'      )

              # Pair input
              self.assertRaises(
                  _A    ,tokenizer_r.batch_encode_plus    ,_A    ,max_length=_A    ,padding='max_length'    ,)

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[str]  =    CodeGenTokenizer.from_pretrained(self.tmpdirname    ,pad_token='<pad>'      )

      # Simple input
      _lowerCAmelCase       :   str  =    'This is a simple input'
      _lowerCAmelCase       :   List[Any]  =    ['This is a simple input looooooooong', 'This is a simple input']
      _lowerCAmelCase       :   Optional[Any]  =    ('This is a simple input', 'This is a pair')
      _lowerCAmelCase       :   List[Any]  =    [
          ('This is a simple input loooooong', 'This is a simple input'),
          ('This is a simple pair loooooong', 'This is a simple pair'),
      ]

      _lowerCAmelCase       :   Optional[int]  =    tokenizer.pad_token_id

      _lowerCAmelCase       :   List[str]  =    tokenizer(_A    ,padding='max_length'    ,max_length=30    ,return_tensors='np'      )
      _lowerCAmelCase       :   Optional[int]  =    tokenizer(_A    ,padding=_A    ,truncate=_A    ,return_tensors='np'      )
      _lowerCAmelCase       :   Dict  =    tokenizer(*_A    ,padding='max_length'    ,max_length=60    ,return_tensors='np'      )
      _lowerCAmelCase       :   Optional[Any]  =    tokenizer(_A    ,padding=_A    ,truncate=_A    ,return_tensors='np'      )

      # s
      # test single string max_length padding
      self.assertEqual(out_s['input_ids'].shape[-1]    ,30      )
      self.assertTrue(pad_token_id in out_s['input_ids']      )
      self.assertTrue(0 in out_s['attention_mask']      )

      # s2
      # test automatic padding
      self.assertEqual(out_sa['input_ids'].shape[-1]    ,33      )
      # long slice doesn't have padding
      self.assertFalse(pad_token_id in out_sa['input_ids'][0]      )
      self.assertFalse(0 in out_sa['attention_mask'][0]      )
      # short slice does have padding
      self.assertTrue(pad_token_id in out_sa['input_ids'][1]      )
      self.assertTrue(0 in out_sa['attention_mask'][1]      )

      # p
      # test single pair max_length padding
      self.assertEqual(out_p['input_ids'].shape[-1]    ,60      )
      self.assertTrue(pad_token_id in out_p['input_ids']      )
      self.assertTrue(0 in out_p['attention_mask']      )

      # p2
      # test automatic padding pair
      self.assertEqual(out_pa['input_ids'].shape[-1]    ,52      )
      # long slice pair doesn't have padding
      self.assertFalse(pad_token_id in out_pa['input_ids'][0]      )
      self.assertFalse(0 in out_pa['attention_mask'][0]      )
      # short slice pair does have padding
      self.assertTrue(pad_token_id in out_pa['input_ids'][1]      )
      self.assertTrue(0 in out_pa['attention_mask'][1]      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Dict  =    '$$$'
      _lowerCAmelCase       :   List[Any]  =    CodeGenTokenizer.from_pretrained(self.tmpdirname    ,bos_token=_A    ,add_bos_token=_A      )

      _lowerCAmelCase       :   List[Any]  =    'This is a simple input'
      _lowerCAmelCase       :   int  =    ['This is a simple input 1', 'This is a simple input 2']

      _lowerCAmelCase       :   Dict  =    tokenizer.bos_token_id

      _lowerCAmelCase       :   Any  =    tokenizer(_A      )
      _lowerCAmelCase       :   List[Any]  =    tokenizer(_A      )

      self.assertEqual(out_s.input_ids[0]    ,_A      )
      self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids      )      )

      _lowerCAmelCase       :   Any  =    tokenizer.decode(out_s.input_ids      )
      _lowerCAmelCase       :   int  =    tokenizer.batch_decode(out_sa.input_ids      )

      self.assertEqual(decode_s.split()[0]    ,_A      )
      self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa      )      )

  @slow
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Dict  =    CodeGenTokenizer.from_pretrained('Salesforce/codegen-350M-mono'      )

      _lowerCAmelCase       :   Union[str, Any]  =    '\nif len_a > len_b:\n    result = a\nelse:\n    result = b\n\n\n\n#'
      _lowerCAmelCase       :   str  =    '\nif len_a > len_b:      result = a\nelse:      result = b'

      _lowerCAmelCase       :   Optional[Any]  =    tokenizer.encode(_A      )
      _lowerCAmelCase       :   str  =    ['^#', re.escape('<|endoftext|>'      ), '^\'\'\'', '^"""', '\n\n\n']
      _lowerCAmelCase       :   List[Any]  =    tokenizer.decode(_A    ,truncate_before_pattern=_A      )
      self.assertEqual(_A    ,_A      )







  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      pass








"""simple docstring"""






import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_lowerCAmelCase						=		logging.get_logger(__name__)


_lowerCAmelCase						=		{
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

_lowerCAmelCase						=		{
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

_lowerCAmelCase						=		"""</w>"""
_lowerCAmelCase						=		"""@@ """

def 		lowerCamelCase__		(					_lowerCamelCase   ):

    '''simple docstring'''



    _lowerCAmelCase       :   List[str]  =    set()
    _lowerCAmelCase       :   Dict  =    word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)   )
        _lowerCAmelCase       :   Any  =    char
    return pairs


# Speech2Text2 has no max input length
_lowerCAmelCase						=		{"""facebook/s2t-wav2vec2-large-en-de""": 1_0_2_4}







class 	__UpperCamelCase    (    a__						):
  _UpperCAmelCase          =		VOCAB_FILES_NAMES
  _UpperCAmelCase          =		PRETRAINED_VOCAB_FILES_MAP
  _UpperCAmelCase          =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _UpperCAmelCase          =		["input_ids", "attention_mask"]

  def __init__(		self    ,_A    ,_A="<s>"    ,_A="<pad>"    ,_A="</s>"    ,_A="<unk>"    ,_A=False    ,_A=None    ,**_A    ,):
      '''simple docstring'''

      super().__init__(
          unk_token=_A    ,bos_token=_A    ,eos_token=_A    ,pad_token=_A    ,do_lower_case=_A    ,**_A    ,)

      _lowerCAmelCase       :   List[Any]  =    do_lower_case

      with open(_A    ,encoding='utf-8'      ) as vocab_handle:
          _lowerCAmelCase       :   Optional[int]  =    json.load(_A      )
      _lowerCAmelCase       :   Tuple  =    {v: k for k, v in self.encoder.items()}

      if merges_file is None:
          logger.info(F"""No merges files provided. {self.__class__.__name__} can only be used for decoding."""      )

          _lowerCAmelCase       :   Optional[Any]  =    None
          _lowerCAmelCase       :   Tuple  =    None
      else:
          with open(_A    ,encoding='utf-8'      ) as merges_handle:
              _lowerCAmelCase       :   Optional[Any]  =    merges_handle.read().split('\n'      )[:-1]

          _lowerCAmelCase       :   List[str]  =    [tuple(merge.split()[:2]      ) for merge in merges]
          _lowerCAmelCase       :   List[Any]  =    dict(zip(_A    ,range(len(_A      )      )      )      )
          _lowerCAmelCase       :   Union[str, Any]  =    {}

  @property
  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return len(self.decoder      )

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      return dict(self.encoder    ,**self.added_tokens_encoder      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   str  =    tuple(token[:-1]      ) + (token[-1] + BPE_TOKEN_MERGES,)
      if token in self.cache:
          return self.cache[token]
      _lowerCAmelCase       :   str  =    get_pairs(_A      )

      if not pairs:
          return token

      while True:
          _lowerCAmelCase       :   List[str]  =    min(_A    ,key=lambda _A      : self.bpe_ranks.get(_A    ,float('inf'      )      )      )
          if bigram not in self.bpe_ranks:
              break
          _lowerCAmelCase,					_lowerCAmelCase       :   Optional[int]  =    bigram
          _lowerCAmelCase       :   Union[str, Any]  =    []
          _lowerCAmelCase       :   Dict  =    0
          while i < len(_A      ):
              try:
                  _lowerCAmelCase       :   Dict  =    word.index(_A    ,_A      )
              except ValueError:
                  new_word.extend(word[i:]      )
                  break
              else:
                  new_word.extend(word[i:j]      )
                  _lowerCAmelCase       :   Optional[Any]  =    j

              if word[i] == first and i < len(_A      ) - 1 and word[i + 1] == second:
                  new_word.append(first + second      )
                  i += 2
              else:
                  new_word.append(word[i]      )
                  i += 1
          _lowerCAmelCase       :   Optional[Any]  =    tuple(_A      )
          _lowerCAmelCase       :   List[str]  =    new_word
          if len(_A      ) == 1:
              break
          else:
              _lowerCAmelCase       :   List[str]  =    get_pairs(_A      )
      _lowerCAmelCase       :   Any  =    ' '.join(_A      )
      if word == "\n  " + BPE_TOKEN_MERGES:
          _lowerCAmelCase       :   str  =    '\n' + BPE_TOKEN_MERGES

      if word.endswith(_A      ):
          _lowerCAmelCase       :   Dict  =    word.replace(_A    ,''      )

      _lowerCAmelCase       :   str  =    word.replace(' '    ,_A      )
      _lowerCAmelCase       :   str  =    word
      return word

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      if self.bpe_ranks is None:
          raise ValueError(
              'This tokenizer was instantiated without a `merges.txt` file, so'
              ' that it can only be used for decoding, not for encoding.'
              'Make sure to provide `merges.txt` file at instantiation to enable '
              'encoding.'      )

      if self.do_lower_case:
          _lowerCAmelCase       :   Optional[Any]  =    text.lower()

      _lowerCAmelCase       :   Tuple  =    text.split()

      _lowerCAmelCase       :   Union[str, Any]  =    []
      for token in text:
          if token:
              split_tokens.extend(list(self.bpe(_A      ).split(' '      )      )      )

      return split_tokens

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      return self.encoder.get(_A    ,self.encoder.get(self.unk_token      )      )

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    self.decoder.get(_A    ,self.unk_token      )
      return result

  def __lowerCamelCase		(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[Any]  =    ' '.join(_A      )

      # make sure @@ tokens are concatenated
      _lowerCAmelCase       :   int  =    ''.join(string.split(_A      )      )

      return string







  def __lowerCamelCase		(		self    ,_A    ,_A = None      ):
      '''simple docstring'''

      if not os.path.isdir(_A      ):
          logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""      )
          return
      _lowerCAmelCase       :   List[Any]  =    os.path.join(
          _A    ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']      )
      _lowerCAmelCase       :   str  =    os.path.join(
          _A    ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']      )

      with open(_A    ,'w'    ,encoding='utf-8'      ) as f:
          f.write(json.dumps(self.encoder    ,indent=2    ,sort_keys=_A    ,ensure_ascii=_A      ) + '\n'      )

      _lowerCAmelCase       :   str  =    0
      if self.bpe_ranks is None:
          return (vocab_file,)

      with open(_A    ,'w'    ,encoding='utf-8'      ) as writer:
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,key=lambda _A      : kv[1]      ):
              if index != token_index:
                  logger.warning(
                      F"""Saving vocabulary to {merges_file}: BPE merge indices are not consecutive."""
                      ' Please check that the tokenizer is not corrupted!'      )
                  _lowerCAmelCase       :   Dict  =    token_index
              writer.write(' '.join(_A      ) + '\n'      )
              index += 1

      return (vocab_file, merges_file)





