'''simple docstring'''





import time
from contextlib import contextmanager
from pathlib import Path

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


SCREAMING_SNAKE_CASE_:	Union[str, Any]    ='__DUMMY_TRANSFORMERS_USER__'
SCREAMING_SNAKE_CASE_:	Optional[Any]    ='Dummy User'
SCREAMING_SNAKE_CASE_:	Tuple    ='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'

SCREAMING_SNAKE_CASE_:	str    ='https://hub-ci.huggingface.co'
SCREAMING_SNAKE_CASE_:	Dict    =CI_HUB_ENDPOINT + '/datasets/{repo_id}/resolve/{revision}/{path}'
SCREAMING_SNAKE_CASE_:	List[Any]    =CI_HUB_ENDPOINT + '/{repo_id}/resolve/{revision}/{filename}'
SCREAMING_SNAKE_CASE_:	List[str]    =Path('~/.huggingface/hub_ci_token').expanduser()





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					int     )       -> int:


     '''simple docstring'''




     monkeypatch.setattr(
         "huggingface_hub.file_download.HUGGINGFACE_CO_URL_TEMPLATE"   ,       snake_case_     )





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					Optional[int]     )       -> List[str]:


     '''simple docstring'''




     monkeypatch.setattr("datasets.config.HF_ENDPOINT"   ,       snake_case_     )
     monkeypatch.setattr("datasets.config.HUB_DATASETS_URL"   ,       snake_case_     )





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					Dict     )       -> Optional[Any]:


     '''simple docstring'''




     monkeypatch.setattr("huggingface_hub.hf_api.HfFolder.path_token"   ,       snake_case_     )





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					Tuple   ,       snake_case_			:					Optional[int]     )       -> int:


     '''simple docstring'''




     HfFolder.save_token(snake_case_     )
     yield
     HfFolder.delete_token()





@pytest.fixture(scope="session"     )
def       lowerCAmelCase_							(   )       -> Any:


     '''simple docstring'''




     return HfApi(endpoint=snake_case_     )





@pytest.fixture(scope="session"     )
def       lowerCAmelCase_							(   snake_case_			:					HfApi     )       -> List[Any]:


     '''simple docstring'''




     UpperCAmelCase_			       =  HfFolder.get_token()
     HfFolder.save_token(snake_case_     )
     yield CI_HUB_USER_TOKEN
     if previous_token is not None:
          HfFolder.save_token(snake_case_     )





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					int     )       -> Dict:


     '''simple docstring'''




     def _cleanup_repo(snake_case_			:					str     ):
          hf_api.delete_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"     )

     return _cleanup_repo





@pytest.fixture
def       lowerCAmelCase_							(   snake_case_			:					Dict     )       -> Optional[Any]:


     '''simple docstring'''




     @contextmanager
     def _temporary_repo(snake_case_			:					Optional[Any]     ):
          try:
               yield repo_id
          finally:
               cleanup_repo(snake_case_     )

     return _temporary_repo





@pytest.fixture(scope="session"     )
def       lowerCAmelCase_							(   snake_case_			:					HfApi   ,       snake_case_			:					Optional[Any]   ,       snake_case_			:					Union[str, Any]     )       -> Tuple:


     '''simple docstring'''




     UpperCAmelCase_			       =  f"""repo_txt_data-{int(time.time() * 1_0E3     )}"""
     UpperCAmelCase_			       =  f"""{CI_HUB_USER}/{repo_name}"""
     hf_api.create_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"   ,       private=snake_case_     )
     hf_api.upload_file(
         token=snake_case_   ,       path_or_fileobj=str(snake_case_     )   ,       path_in_repo="data/text_data.txt"   ,       repo_id=snake_case_   ,       repo_type="dataset"   ,       )
     yield repo_id
     try:
          hf_api.delete_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"     )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass





@pytest.fixture()
def       lowerCAmelCase_							(   snake_case_			:					List[Any]   ,       snake_case_			:					Union[str, Any]   ,       snake_case_			:					Union[str, Any]     )       -> Any:


     '''simple docstring'''




     return hf_private_dataset_repo_txt_data_





@pytest.fixture(scope="session"     )
def       lowerCAmelCase_							(   snake_case_			:					HfApi   ,       snake_case_			:					Tuple   ,       snake_case_			:					List[Any]     )       -> Optional[int]:


     '''simple docstring'''




     UpperCAmelCase_			       =  f"""repo_zipped_txt_data-{int(time.time() * 1_0E3     )}"""
     UpperCAmelCase_			       =  f"""{CI_HUB_USER}/{repo_name}"""
     hf_api.create_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"   ,       private=snake_case_     )
     hf_api.upload_file(
         token=snake_case_   ,       path_or_fileobj=str(snake_case_     )   ,       path_in_repo="data.zip"   ,       repo_id=snake_case_   ,       repo_type="dataset"   ,       )
     yield repo_id
     try:
          hf_api.delete_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"     )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass





@pytest.fixture()
def       lowerCAmelCase_							(   snake_case_			:					Any   ,       snake_case_			:					Union[str, Any]   ,       snake_case_			:					List[str]     )       -> int:


     '''simple docstring'''




     return hf_private_dataset_repo_zipped_txt_data_





@pytest.fixture(scope="session"     )
def       lowerCAmelCase_							(   snake_case_			:					HfApi   ,       snake_case_			:					str   ,       snake_case_			:					Dict     )       -> Optional[Any]:


     '''simple docstring'''




     UpperCAmelCase_			       =  f"""repo_zipped_img_data-{int(time.time() * 1_0E3     )}"""
     UpperCAmelCase_			       =  f"""{CI_HUB_USER}/{repo_name}"""
     hf_api.create_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"   ,       private=snake_case_     )
     hf_api.upload_file(
         token=snake_case_   ,       path_or_fileobj=str(snake_case_     )   ,       path_in_repo="data.zip"   ,       repo_id=snake_case_   ,       repo_type="dataset"   ,       )
     yield repo_id
     try:
          hf_api.delete_repo(snake_case_   ,       token=snake_case_   ,       repo_type="dataset"     )
     except (requests.exceptions.HTTPError, ValueError):  # catch http error and token invalid error
          pass






@pytest.fixture()
def       lowerCAmelCase_							(   snake_case_			:					Union[str, Any]   ,       snake_case_			:					Optional[int]   ,       snake_case_			:					Union[str, Any]     )       -> List[str]:


     '''simple docstring'''




     return hf_private_dataset_repo_zipped_img_data_








'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase_			:  Any										=   {
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase_			:  Tuple										=   ['MaskFormerFeatureExtractor']
 UpperCAmelCase_			:  List[str]										=   ['MaskFormerImageProcessor']


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 UpperCAmelCase_			:  Optional[Any]										=   [
     'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MaskFormerForInstanceSegmentation',
     'MaskFormerModel',
     'MaskFormerPreTrainedModel',
 ]
 UpperCAmelCase_			:  Optional[int]										=   [
     'MaskFormerSwinBackbone',
     'MaskFormerSwinModel',
     'MaskFormerSwinPreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
 from .configuration_maskformer_swin import MaskFormerSwinConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_maskformer import MaskFormerFeatureExtractor
  from .image_processing_maskformer import MaskFormerImageProcessor
 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_maskformer import (
      MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      MaskFormerForInstanceSegmentation,
      MaskFormerModel,
      MaskFormerPreTrainedModel,
  )
  from .modeling_maskformer_swin import (
      MaskFormerSwinBackbone,
      MaskFormerSwinModel,
      MaskFormerSwinPreTrainedModel,
  )


else:
 import sys

 UpperCAmelCase_			:  Union[str, Any]										=   _LazyModule(__name__, globals()['__file__'], _import_structure)






