





import time
from contextlib import contextmanager
from pathlib import Path

import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder


UpperCAmelCase     :     str							=	"""__DUMMY_TRANSFORMERS_USER__"""
UpperCAmelCase     :     int							=	"""Dummy User"""
UpperCAmelCase     :     str							=	"""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"""

UpperCAmelCase     :     Any							=	"""https://hub-ci.huggingface.co"""
UpperCAmelCase     :     List[Any]							=	CI_HUB_ENDPOINT + """/datasets/{repo_id}/resolve/{revision}/{path}"""
UpperCAmelCase     :     Any							=	CI_HUB_ENDPOINT + """/{repo_id}/resolve/{revision}/{filename}"""
UpperCAmelCase     :     List[Any]							=	Path("""~/.huggingface/hub_ci_token""").expanduser()
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       List[Any]						):





  """simple docstring"""



  monkeypatch.setattr(
      "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"	,	SCREAMING_SNAKE_CASE						)
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       Tuple						):





  """simple docstring"""



  monkeypatch.setattr("datasets.config.HF_ENDPOINT"	,	SCREAMING_SNAKE_CASE						)
  monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"	,	SCREAMING_SNAKE_CASE						)
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       Tuple						):





  """simple docstring"""



  monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"	,	SCREAMING_SNAKE_CASE						)
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       Dict	,	SCREAMING_SNAKE_CASE					:       int						):





  """simple docstring"""



  HfFolder.save_token(SCREAMING_SNAKE_CASE						)
  yield
  HfFolder.delete_token()
@pytest.fixture(scope="session"						)
def 					_A	(		):





  """simple docstring"""



  return HfApi(endpoint=SCREAMING_SNAKE_CASE						)
@pytest.fixture(scope="session"						)
def 					_A	(		SCREAMING_SNAKE_CASE					:       HfApi						):





  """simple docstring"""



  a__     : Optional[int]  =HfFolder.get_token()
  HfFolder.save_token(SCREAMING_SNAKE_CASE						)
  yield CI_HUB_USER_TOKEN
  if previous_token is not None:
    HfFolder.save_token(SCREAMING_SNAKE_CASE						)
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       Any						):





  """simple docstring"""



  def _cleanup_repo(SCREAMING_SNAKE_CASE					:       Optional[Any]						):
    hf_api.delete_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"						)

  return _cleanup_repo
@pytest.fixture
def 					_A	(		SCREAMING_SNAKE_CASE					:       Dict						):





  """simple docstring"""



  @contextmanager
  def _temporary_repo(SCREAMING_SNAKE_CASE					:       Any						):
    try:
      yield repo_id
    finally:
      cleanup_repo(SCREAMING_SNAKE_CASE						)

  return _temporary_repo
@pytest.fixture(scope="session"						)
def 					_A	(		SCREAMING_SNAKE_CASE					:       HfApi	,	SCREAMING_SNAKE_CASE					:       Union[str, Any]	,	SCREAMING_SNAKE_CASE					:       List[str]						):





  """simple docstring"""



  a__     : int  =f'''repo_txt_data-{int(time.time() * 10e3						)}'''
  a__     : Any  =f'''{CI_HUB_USER}/{repo_name}'''
  hf_api.create_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	private=SCREAMING_SNAKE_CASE						)
  hf_api.upload_file(
      token=SCREAMING_SNAKE_CASE	,	path_or_fileobj=str(SCREAMING_SNAKE_CASE						)	,	path_in_repo="data/text_data.txt"	,	repo_id=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	)
  yield repo_id
  try:
    hf_api.delete_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"						)
  except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
    pass
@pytest.fixture()
def 					_A	(		SCREAMING_SNAKE_CASE					:       List[str]	,	SCREAMING_SNAKE_CASE					:       Tuple	,	SCREAMING_SNAKE_CASE					:       Union[str, Any]						):





  """simple docstring"""



  return hf_private_dataset_repo_txt_data_
@pytest.fixture(scope="session"						)
def 					_A	(		SCREAMING_SNAKE_CASE					:       HfApi	,	SCREAMING_SNAKE_CASE					:       Union[str, Any]	,	SCREAMING_SNAKE_CASE					:       str						):





  """simple docstring"""



  a__     : Optional[int]  =f'''repo_zipped_txt_data-{int(time.time() * 10e3						)}'''
  a__     : List[Any]  =f'''{CI_HUB_USER}/{repo_name}'''
  hf_api.create_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	private=SCREAMING_SNAKE_CASE						)
  hf_api.upload_file(
      token=SCREAMING_SNAKE_CASE	,	path_or_fileobj=str(SCREAMING_SNAKE_CASE						)	,	path_in_repo="data.zip"	,	repo_id=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	)
  yield repo_id
  try:
    hf_api.delete_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"						)
  except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
    pass
@pytest.fixture()
def 					_A	(		SCREAMING_SNAKE_CASE					:       List[str]	,	SCREAMING_SNAKE_CASE					:       Any	,	SCREAMING_SNAKE_CASE					:       Tuple						):





  """simple docstring"""



  return hf_private_dataset_repo_zipped_txt_data_
@pytest.fixture(scope="session"						)
def 					_A	(		SCREAMING_SNAKE_CASE					:       HfApi	,	SCREAMING_SNAKE_CASE					:       Union[str, Any]	,	SCREAMING_SNAKE_CASE					:       Optional[Any]						):





  """simple docstring"""



  a__     : int  =f'''repo_zipped_img_data-{int(time.time() * 10e3						)}'''
  a__     : Optional[int]  =f'''{CI_HUB_USER}/{repo_name}'''
  hf_api.create_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	private=SCREAMING_SNAKE_CASE						)
  hf_api.upload_file(
      token=SCREAMING_SNAKE_CASE	,	path_or_fileobj=str(SCREAMING_SNAKE_CASE						)	,	path_in_repo="data.zip"	,	repo_id=SCREAMING_SNAKE_CASE	,	repo_type="dataset"	,	)
  yield repo_id
  try:
    hf_api.delete_repo(SCREAMING_SNAKE_CASE	,	token=SCREAMING_SNAKE_CASE	,	repo_type="dataset"						)
  except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
    pass





@pytest.fixture()
def 					_A	(		SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       Tuple	,	SCREAMING_SNAKE_CASE					:       Optional[int]						):





  """simple docstring"""



  return hf_private_dataset_repo_zipped_img_data_













import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate







@dataclass(frozen=UpperCamelCase__)
class     __lowerCAmelCase	(   UpperCamelCase__):
      _lowercase    : str            =      field(default="""image-classification"""						,    metadata={"""include_in_asdict_even_if_is_default""": True})
      _lowercase    : ClassVar[Features]            =      Features({"""image""": Image()})
      _lowercase    : ClassVar[Features]            =      Features({"""labels""": ClassLabel})
      _lowercase    : str            =      "image"
      _lowercase    : str            =      "labels"







      def        _lowercase  (   self		,				lowerCAmelCase__							)       ->						List[Any]:



        '''simple docstring'''




        if self.label_column not in features:
          raise ValueError(F'''Column {self.label_column} is not present in features.'''							)
        if not isinstance(features[self.label_column]		,				lowerCAmelCase__							):
          raise ValueError(F'''Column {self.label_column} is not a ClassLabel.'''							)
        a__     : int  =copy.deepcopy(self							)
        a__     : Dict  =self.label_schema.copy()
        a__     : int  =features[self.label_column]
        a__     : str  =label_schema
        return task_template







      @property
      def        _lowercase  (   self							)       ->						Dict[str, str]:



        '''simple docstring'''




        return {
            self.image_column: "image",
            self.label_column: "labels",
        }






