'''simple docstring'''


import warnings

from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum

from ...processing_utils import ProcessorMixin


if is_torch_available():
       import torch





class       _a    (		__snake_case      ):


  """simple docstring"""

  A_    							=						'''char'''
  A_    							=						'''bpe'''
  A_    							=						'''wp'''






__snake_case						  =		(DecodeType.CHARACTER, DecodeType.BPE, DecodeType.WORDPIECE)





class       _a    (		__snake_case      ):


  """simple docstring"""

  A_    							=						['''image_processor''', '''char_tokenizer''']
  A_    							=						'''ViTImageProcessor'''
  A_    							=						'''MgpstrTokenizer'''




  def __init__(		self      :       Optional[int]   ,				lowercase_      :       Tuple=None   ,				lowercase_      :       Dict=None   ,				**lowercase_      :       Optional[int]      ):







    '''simple docstring'''


    lowercase_     =       None
    if "feature_extractor" in kwargs:
      warnings.warn(
          """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
          """ instead."""   ,				snake_case_   ,				)
      lowercase_     =       kwargs.pop("""feature_extractor"""      )

    lowercase_     =       image_processor if image_processor is not None else feature_extractor
    if image_processor is None:
      raise ValueError("""You need to specify an `image_processor`."""      )
    if tokenizer is None:
      raise ValueError("""You need to specify a `tokenizer`."""      )

    lowercase_     =       tokenizer
    lowercase_     =       AutoTokenizer.from_pretrained("""gpt2"""      )
    lowercase_     =       AutoTokenizer.from_pretrained("""bert-base-uncased"""      )

    super().__init__(snake_case_   ,				snake_case_      )




  def __call__(		self      :       List[str]   ,				lowercase_      :       Dict=None   ,				lowercase_      :       Tuple=None   ,				lowercase_      :       Optional[Any]=None   ,				**lowercase_      :       List[str]      ):







    '''simple docstring'''


    if images is None and text is None:
      raise ValueError("""You need to specify either an `images` or `text` input to process."""      )

    if images is not None:
      lowercase_     =       self.image_processor(snake_case_   ,				return_tensors=snake_case_   ,				**snake_case_      )
    if text is not None:
      lowercase_     =       self.char_tokenizer(snake_case_   ,				return_tensors=snake_case_   ,				**snake_case_      )

    if text is None:
      return inputs
    elif images is None:
      return encodings
    else:
      lowercase_     =       encodings["""input_ids"""]
      return inputs




  def 		lowerCamelCase__  (		self      :       Tuple   ,				lowercase_      :       List[str]      ):







    '''simple docstring'''


    lowercase_     ,	lowercase_     ,	lowercase_     =       sequences
    lowercase_     =       char_preds.size(0      )

    lowercase_     ,	lowercase_     =       self._decode_helper(snake_case_   ,				"""char"""      )
    lowercase_     ,	lowercase_     =       self._decode_helper(snake_case_   ,				"""bpe"""      )
    lowercase_     ,	lowercase_     =       self._decode_helper(snake_case_   ,				"""wp"""      )

    lowercase_     =       []
    lowercase_     =       []
    for i in range(snake_case_      ):
      lowercase_     =       [char_scores[i], bpe_scores[i], wp_scores[i]]
      lowercase_     =       [char_strs[i], bpe_strs[i], wp_strs[i]]
      lowercase_     =       scores.index(max(snake_case_      )      )
      final_strs.append(strs[max_score_index]      )
      final_scores.append(scores[max_score_index]      )

    lowercase_     =       {}
    lowercase_     =       final_strs
    lowercase_     =       final_scores
    lowercase_     =       char_strs
    lowercase_     =       bpe_strs
    lowercase_     =       wp_strs
    return out




  def 		lowerCamelCase__  (		self      :       Tuple   ,				lowercase_      :       List[str]   ,				lowercase_      :       Optional[Any]      ):







    '''simple docstring'''


    if format == DecodeType.CHARACTER:
      lowercase_     =       self.char_decode
      lowercase_     =       1
      lowercase_     =       """[s]"""
    elif format == DecodeType.BPE:
      lowercase_     =       self.bpe_decode
      lowercase_     =       2
      lowercase_     =       """#"""
    elif format == DecodeType.WORDPIECE:
      lowercase_     =       self.wp_decode
      lowercase_     =       102
      lowercase_     =       """[SEP]"""
    else:
      raise ValueError(F"""Format {format} is not supported."""      )

    lowercase_     ,	lowercase_     =       [], []
    lowercase_     =       pred_logits.size(0      )
    lowercase_     =       pred_logits.size(1      )
    lowercase_     ,	lowercase_     =       pred_logits.topk(1   ,				dim=-1   ,				largest=snake_case_   ,				sorted=snake_case_      )
    lowercase_     =       preds_index.view(-1   ,				snake_case_      )[:, 1:]
    lowercase_     =       decoder(snake_case_      )
    lowercase_     ,	lowercase_     =       torch.nn.functional.softmax(snake_case_   ,				dim=2      ).max(dim=2      )
    lowercase_     =       preds_max_prob[:, 1:]

    for index in range(snake_case_      ):
      lowercase_     =       preds_str[index].find(snake_case_      )
      lowercase_     =       preds_str[index][:pred_eos]
      lowercase_     =       preds_index[index].cpu().tolist()
      lowercase_     =       pred_index.index(snake_case_      ) if eos_token in pred_index else -1
      lowercase_     =       preds_max_prob[index][: pred_eos_index + 1]
      lowercase_     =       pred_max_prob.cumprod(dim=0      )[-1] if pred_max_prob.nelement() != 0 else 0.0
      dec_strs.append(snake_case_      )
      conf_scores.append(snake_case_      )

    return dec_strs, conf_scores




  def 		lowerCamelCase__  (		self      :       List[Any]   ,				lowercase_      :       Tuple      ):







    '''simple docstring'''


    lowercase_     =       [seq.replace(""" """   ,				""""""      ) for seq in self.char_tokenizer.batch_decode(snake_case_      )]
    return decode_strs




  def 		lowerCamelCase__  (		self      :       int   ,				lowercase_      :       List[Any]      ):







    '''simple docstring'''


    return self.bpe_tokenizer.batch_decode(snake_case_      )





  def 		lowerCamelCase__  (		self      :       Tuple   ,				lowercase_      :       Dict      ):







    '''simple docstring'''


    lowercase_     =       [seq.replace(""" """   ,				""""""      ) for seq in self.wp_tokenizer.batch_decode(snake_case_      )]
    return decode_strs








import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


__A							:			List[Any]         =			"http://www.mocksite.com/file1.txt"
__A							:			List[Any]         =			"\"text\": [\"foo\", \"foo\"]"
__A							:			Dict         =			"6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"







class      lowerCamelCase:
     '''simple docstring'''


     __magic_name__   =			200
     __magic_name__   =			{'Content-Length': '100'}
     __magic_name__   =			{}




     def        lowerCAmelCase__		(    self				,     **snake_case_							):
         return [bytes(snake_case_				,     'utf-8'							)]





def 				__lowerCAmelCase(       *_SCREAMING_SNAKE_CASE							,     **_SCREAMING_SNAKE_CASE				)							-> Optional[Any]:




    """simple docstring"""




    return MockResponse()





@pytest.mark.parametrize('urls_type'							,     [str, list, dict]				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> str:




    """simple docstring"""




    import requests

    monkeypatch.setattr(_SCREAMING_SNAKE_CASE							,     'request'							,     _SCREAMING_SNAKE_CASE				)

    _A     =							URL
    if issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							url
    elif issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							[url]
    elif issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							{'train': url}
    _A     =							'dummy'
    _A     =							'downloads'
    _A     =							tmp_path
    _A     =							DownloadConfig(
        cache_dir=os.path.join(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							,     use_etag=_SCREAMING_SNAKE_CASE							,     )
    _A     =							DownloadManager(dataset_name=_SCREAMING_SNAKE_CASE							,     download_config=_SCREAMING_SNAKE_CASE				)
    _A     =							dl_manager.download(_SCREAMING_SNAKE_CASE				)
    _A     =							urls
    for downloaded_paths in [downloaded_paths]:
        if isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            _A     =							[downloaded_paths]
            _A     =							[urls]
        elif isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            assert "train" in downloaded_paths.keys()
            _A     =							downloaded_paths.values()
            _A     =							urls.values()
        assert downloaded_paths
        for downloaded_path, input_url in zip(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            assert downloaded_path == dl_manager.downloaded_paths[input_url]
            _A     =							Path(_SCREAMING_SNAKE_CASE				)
            _A     =							downloaded_path.parts
            assert parts[-1] == HASH
            assert parts[-2] == cache_subdir
            assert downloaded_path.exists()
            _A     =							downloaded_path.read_text()
            assert content == CONTENT
            _A     =							downloaded_path.with_suffix('.json'				)
            assert metadata_downloaded_path.exists()
            _A     =							json.loads(metadata_downloaded_path.read_text()				)
            assert metadata_content == {"url": URL, "etag": None}





@pytest.mark.parametrize('paths_type'							,     [str, list, dict]				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Optional[Any]:




    """simple docstring"""




    _A     =							str(_SCREAMING_SNAKE_CASE				)
    if issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							filename
    elif issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							[filename]
    elif issubclass(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
        _A     =							{'train': filename}
    _A     =							'dummy'
    _A     =							xz_file.parent
    _A     =							'extracted'
    _A     =							DownloadConfig(
        cache_dir=_SCREAMING_SNAKE_CASE							,     use_etag=_SCREAMING_SNAKE_CASE							,     )
    _A     =							DownloadManager(dataset_name=_SCREAMING_SNAKE_CASE							,     download_config=_SCREAMING_SNAKE_CASE				)
    _A     =							dl_manager.extract(_SCREAMING_SNAKE_CASE				)
    _A     =							paths
    for extracted_paths in [extracted_paths]:
        if isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            _A     =							[extracted_paths]
            _A     =							[paths]
        elif isinstance(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            assert "train" in extracted_paths.keys()
            _A     =							extracted_paths.values()
            _A     =							paths.values()
        assert extracted_paths
        for extracted_path, input_path in zip(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				):
            assert extracted_path == dl_manager.extracted_paths[input_path]
            _A     =							Path(_SCREAMING_SNAKE_CASE				)
            _A     =							extracted_path.parts
            assert parts[-1] == hash_url_to_filename(_SCREAMING_SNAKE_CASE							,     etag=_SCREAMING_SNAKE_CASE				)
            assert parts[-2] == extracted_subdir
            assert extracted_path.exists()
            _A     =							extracted_path.read_text()
            _A     =							text_file.read_text()
            assert extracted_file_content == expected_file_content





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Dict:




    """simple docstring"""




    assert path.endswith('.jsonl'				)
    for num_items, line in enumerate(_SCREAMING_SNAKE_CASE							,     start=1				):
        _A     =							json.loads(line.decode('utf-8'				)				)
        assert item.keys() == {"col_1", "col_2", "col_3"}
    assert num_items == 4





@pytest.mark.parametrize('archive_jsonl'							,     ['tar_jsonl_path', 'zip_jsonl_path']				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Optional[int]:




    """simple docstring"""




    _A     =							request.getfixturevalue(_SCREAMING_SNAKE_CASE				)
    _A     =							DownloadManager()
    for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(_SCREAMING_SNAKE_CASE				)							,     start=1				):
        _test_jsonl(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
    assert num_jsonl == 2





@pytest.mark.parametrize('archive_nested_jsonl'							,     ['tar_nested_jsonl_path', 'zip_nested_jsonl_path']				)
def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> Any:




    """simple docstring"""




    _A     =							request.getfixturevalue(_SCREAMING_SNAKE_CASE				)
    _A     =							DownloadManager()
    for num_tar, (path, file) in enumerate(dl_manager.iter_archive(_SCREAMING_SNAKE_CASE				)							,     start=1				):
        for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(_SCREAMING_SNAKE_CASE				)							,     start=1				):
            _test_jsonl(_SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)
    assert num_tar == 1
    assert num_jsonl == 2





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> int:




    """simple docstring"""




    _A     =							DownloadManager()
    for num_file, file in enumerate(dl_manager.iter_files(_SCREAMING_SNAKE_CASE				)							,     start=1				):
        assert os.path.basename(_SCREAMING_SNAKE_CASE				) == ("test.txt" if num_file == 1 else "train.txt")
    assert num_file == 2





