





"""simple docstring"""


# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


lowerCamelCase__						= get_logger(__name__)



class   __SCREAMING_SNAKE_CASE     :







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:Optional[Any]						  =       "dummy_data"
  SCREAMING_SNAKE_CASE__				:Optional[int]						  =       "datasets"
  SCREAMING_SNAKE_CASE__				:List[Any]						  =       False

  def __init__(		self :							Optional[int]       , __a :							str       , __a :							str       , __a :							Union[Version, str]       , __a :							Optional[str] = None       , __a :							bool = False       , __a :							bool = True       , __a :							Optional[List[Callable]] = None       , )		->					List[str]:
        _UpperCamelCase   :						List[Any]    =							0
        _UpperCamelCase   :						int    =							dataset_name
        _UpperCamelCase   :						int    =							cache_dir
        _UpperCamelCase   :						Union[str, Any]    =							use_local_dummy_data
        _UpperCamelCase   :						Optional[int]    =							config
        # download_callbacks take a single url as input
        _UpperCamelCase   :						List[Callable]    =							download_callbacks or []
        # if False, it doesn't load existing files and it returns the paths of the dummy files relative
        # to the dummy_data zip file root
        _UpperCamelCase   :						Optional[Any]    =							load_existing_dummy_data

        # TODO(PVP, QL) might need to make this more general
        _UpperCamelCase   :						str    =							str(__a						)
        # to be downloaded
        _UpperCamelCase   :						Union[str, Any]    =							None
        _UpperCamelCase   :						Dict    =							None

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[Any]						)		->					Tuple:
        if self._dummy_file is None:
              _UpperCamelCase   :						Optional[Any]    =							self.download_dummy_data()
        return self._dummy_file

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							List[Any]						)		->					Tuple:
        if self.config is not None:
              # structure is dummy / config_name / version_name
              return os.path.join("dummy"       , self.config.name       , self.version_name						)
        # structure is dummy / version_name
        return os.path.join("dummy"       , self.version_name						)

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]						)		->					Dict:
        return os.path.join(self.dummy_data_folder       , "dummy_data.zip"						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Union[str, Any]						)		->					Optional[Any]:
        _UpperCamelCase   :						Optional[Any]    =							(
            self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
        )

        _UpperCamelCase   :						Tuple    =							cached_path(
            __a       , cache_dir=self.cache_dir       , extract_compressed_file=__a       , force_extract=__a						)

        return os.path.join(__a       , self.dummy_file_name						)

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							List[Any]						)		->					Dict:
        return os.path.join(self.datasets_scripts_dir       , self.dataset_name       , self.dummy_zip_file						)

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]						)		->					int:
        if self._bucket_url is None:
              _UpperCamelCase   :						Any    =							hf_github_url(self.dataset_name       , self.dummy_zip_file.replace(os.sep       , "/"						)						)
        return self._bucket_url

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Any						)		->					Optional[Any]:
        # return full path if its a dir
        if os.path.isdir(self.dummy_file						):
              return self.dummy_file
        # else cut off path to file -> example `xsum`.
        return "/".join(self.dummy_file.replace(os.sep       , "/"						).split("/"						)[:-1]						)

  def  __SCREAMING_SNAKE_CASE					(		self :							List[str]       , __a :							Optional[Any]       , *__a :							Tuple						)		->					List[str]:
        if self.load_existing_dummy_data:
              # dummy data is downloaded and tested
              _UpperCamelCase   :						str    =							self.dummy_file
        else:
              # dummy data cannot be downloaded and only the path to dummy file is returned
              _UpperCamelCase   :						Any    =							self.dummy_file_name

        # special case when data_url is a dict
        if isinstance(__a       , __a						):
              return self.create_dummy_data_dict(__a       , __a						)
        elif isinstance(__a       , (list, tuple)						):
              return self.create_dummy_data_list(__a       , __a						)
        else:
              return self.create_dummy_data_single(__a       , __a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple       , __a :							str       , *__a :							Union[str, Any]						)		->					int:
        return self.download_and_extract(__a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							List[Any]       , __a :							List[Any]       , __a :							List[str]						)		->					Any:
        return self.download_and_extract(__a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Union[str, Any]       , __a :							int       , *__a :							Union[str, Any]       , **__a :							Union[str, Any]						)		->					int:
        return path

  def  __SCREAMING_SNAKE_CASE					(		self :							str						)		->					Union[str, Any]:
        return {}

  def  __SCREAMING_SNAKE_CASE					(		self :							str       , __a :							Union[str, Any]       , __a :							Union[str, Any]						)		->					List[str]:
        _UpperCamelCase   :						List[Any]    =							{}
        for key, single_urls in data_url.items():
              for download_callback in self.download_callbacks:
                    if isinstance(__a       , __a						):
                          for single_url in single_urls:
                                download_callback(__a						)
                    else:
                          _UpperCamelCase   :						Optional[Any]    =							single_urls
                          download_callback(__a						)
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
              if isinstance(__a       , __a						):
                    _UpperCamelCase   :						List[Any]    =							[os.path.join(__a       , urllib.parse.quote_plus(Path(__a						).name						)						) for x in single_urls]
              else:
                    _UpperCamelCase   :						Union[str, Any]    =							single_urls
                    _UpperCamelCase   :						List[str]    =							os.path.join(__a       , urllib.parse.quote_plus(Path(__a						).name						)						)
              _UpperCamelCase   :						Union[str, Any]    =							value

        # make sure that values are unique
        if all(isinstance(__a       , __a						) for i in dummy_data_dict.values()						) and len(set(dummy_data_dict.values()						)						) < len(
            dummy_data_dict.values()						):
              # append key to value to make its name unique
              _UpperCamelCase   :						int    =							{key: value + key for key, value in dummy_data_dict.items()}

        return dummy_data_dict

  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple       , __a :							str       , __a :							Union[str, Any]						)		->					int:
        _UpperCamelCase   :						Union[str, Any]    =							[]
        # trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
        _UpperCamelCase   :						str    =							all(bool(re.findall("[0-9]{3,}-of-[0-9]{3,}"       , __a						)						) for url in data_url						)
        _UpperCamelCase   :						List[str]    =							all(
            url.startswith("https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed"						) for url in data_url						)
        if data_url and (is_tf_records or is_pubmed_records):
              _UpperCamelCase   :						Tuple    =							[data_url[0]] * len(__a						)
        for single_url in data_url:
              for download_callback in self.download_callbacks:
                    download_callback(__a						)
              # we force the name of each key to be the last file / folder name of the url path
              # if the url has arguments, we need to encode them with urllib.parse.quote_plus
              _UpperCamelCase   :						Any    =							os.path.join(__a       , urllib.parse.quote_plus(single_url.split("/"						)[-1]						)						)
              dummy_data_list.append(__a						)
        return dummy_data_list

  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]       , __a :							Union[str, Any]       , __a :							int						)		->					List[str]:
        for download_callback in self.download_callbacks:
              download_callback(__a						)
        # we force the name of each key to be the last file / folder name of the url path
        # if the url has arguments, we need to encode them with urllib.parse.quote_plus
        _UpperCamelCase   :						Optional[Any]    =							os.path.join(__a       , urllib.parse.quote_plus(data_url.split("/"						)[-1]						)						)
        if os.path.exists(__a						) or not self.load_existing_dummy_data:
              return value
        else:
              # Backward compatibility, maybe deprecate at one point.
              # For many datasets with single url calls to dl_manager.download_and_extract,
              # the dummy_data.zip file is actually the zipped downloaded file
              # while now we expected the dummy_data.zip file to be a directory containing
              # the downloaded file.
              return path_to_dummy_data

  def  __SCREAMING_SNAKE_CASE					(		self :							int						)		->					int:
        pass

  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple						)		->					Optional[Any]:
        pass

  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[Any]       , __a :							Dict						)		->					Any:
        def _iter_archive_members(__a :							List[str]						):
              # this preserves the order of the members inside the ZIP archive
              _UpperCamelCase   :						List[Any]    =							Path(self.dummy_file						).parent
              _UpperCamelCase   :						List[str]    =							path.relative_to(__a						)
              with ZipFile(self.local_path_to_dummy_data						) as zip_file:
                    _UpperCamelCase   :						str    =							zip_file.namelist()
              for member in members:
                    if member.startswith(relative_path.as_posix()						):
                          yield dummy_parent_path.joinpath(__a						)

        _UpperCamelCase   :						Any    =							Path(__a						)
        _UpperCamelCase   :						Union[str, Any]    =							_iter_archive_members(__a						) if self.use_local_dummy_data else path.rglob("*"						)
        for file_path in file_paths:
              if file_path.is_file() and not file_path.name.startswith((".", "__")						):
                    yield file_path.relative_to(__a						).as_posix(), file_path.open("rb"						)


  def  __SCREAMING_SNAKE_CASE					(		self :							Dict       , __a :							Any						)		->					Any:
        if not isinstance(__a       , __a						):
              _UpperCamelCase   :						List[str]    =							[paths]
        for path in paths:
              if os.path.isfile(__a						):
                    if os.path.basename(__a						).startswith((".", "__")						):
                          return
                    yield path
              else:
                    for dirpath, dirnames, filenames in os.walk(__a						):
                          if os.path.basename(__a						).startswith((".", "__")						):
                                continue
                          dirnames.sort()
                          for filename in sorted(__a						):
                                if filename.startswith((".", "__")						):
                                      continue
                                yield os.path.join(__a       , __a						)







"""simple docstring"""


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding



class   __SCREAMING_SNAKE_CASE     (    _UpperCamelCase ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:Optional[Any]						  =       ["image_processor", "tokenizer"]
  SCREAMING_SNAKE_CASE__				:Dict						  =       "AutoImageProcessor"
  SCREAMING_SNAKE_CASE__				:Optional[int]						  =       "AutoTokenizer"

  def __init__(		self :							Dict       , __a :							Tuple       , __a :							str						)		->					Optional[Any]:
        super().__init__(__a       , __a						)
        _UpperCamelCase   :						Tuple    =							self.image_processor

  def __call__(		self :							Tuple       , __a :							Tuple=None       , __a :							str=None       , __a :							Any=None       , **__a :							Optional[Any]						)		->					Union[str, Any]:

        if text is None and images is None:
              raise ValueError("You have to specify either text or images. Both cannot be none."						)

        if text is not None:
              _UpperCamelCase   :						List[str]    =							self.tokenizer(__a       , return_tensors=__a       , **__a						)

        if images is not None:
              _UpperCamelCase   :						str    =							self.image_processor(__a       , return_tensors=__a       , **__a						)

        if text is not None and images is not None:
              _UpperCamelCase   :						Optional[int]    =							image_features.pixel_values
              return encoding
        elif text is not None:
              return encoding
        else:
              return BatchEncoding(data=dict(**__a						)       , tensor_type=__a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]       , *__a :							Optional[int]       , **__a :							Optional[int]						)		->					List[Any]:
        return self.tokenizer.batch_decode(*__a       , **__a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , *__a :							Any       , **__a :							List[Any]						)		->					Tuple:
        return self.tokenizer.decode(*__a       , **__a						)


  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							str						)		->					Any:
        return ["input_ids", "attention_mask", "pixel_values"]
