"""simple docstring"""




import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict





@pytest.mark.parametrize(
    """files"""    ,[
        ["""full:README.md""", """dataset_infos.json"""],
        ["""empty:README.md""", """dataset_infos.json"""],
        ["""dataset_infos.json"""],
        ["""full:README.md"""],
    ]    ,)
def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: str    ,_lowerCamelCase		: List[Any]			) ->   List[Any]:
  _lowerCAmelCase		: Optional[int]						    =  tmp_path_factory.mktemp("""dset_infos_dir"""			)
  if "full:README.md" in files:
    with open(dataset_infos_dir / """README.md"""    ,"""w"""			) as f:
      f.write("""---\ndataset_info:\n  dataset_size: 42\n---"""			)
  if "empty:README.md" in files:
    with open(dataset_infos_dir / """README.md"""    ,"""w"""			) as f:
      f.write(""""""			)
    # we want to support dataset_infos.json for backward compatibility
  if "dataset_infos.json" in files:
    with open(dataset_infos_dir / """dataset_infos.json"""    ,"""w"""			) as f:
      f.write("""{\"default\": {\"dataset_size\": 42}}"""			)
  _lowerCAmelCase		: Any						    =  DatasetInfosDict.from_directory(_lowerCamelCase			)
  assert dataset_infos
  assert dataset_infos["default"].dataset_size == 42





@pytest.mark.parametrize(
    """dataset_info"""    ,[
        DatasetInfo(),
        DatasetInfo(
            description="""foo"""    ,features=Features({"""a""": Value("""int32"""			)}			)    ,builder_name="""builder"""    ,config_name="""config"""    ,version="""1.0.0"""    ,splits=[{"""name""": """train"""}]    ,download_size=42    ,),
    ]    ,)
def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Any    ,_lowerCamelCase		: DatasetInfo			) ->   Any:
  _lowerCAmelCase		: List[str]						    =  str(_lowerCamelCase			)
  dataset_info.write_to_directory(_lowerCamelCase			)
  _lowerCAmelCase		: Any						    =  DatasetInfo.from_directory(_lowerCamelCase			)
  assert dataset_info == reloaded
  assert os.path.exists(os.path.join(_lowerCamelCase    ,"""dataset_info.json"""			)			)





def 							SCREAMING_SNAKE_CASE  (    ) ->   Optional[int]:
  _lowerCAmelCase		: Union[str, Any]						    =  DatasetInfo(
      description="""foo"""    ,citation="""bar"""    ,homepage="""https://foo.bar"""    ,license="""CC0"""    ,features=Features({"""a""": Value("""int32"""			)}			)    ,post_processed={}    ,supervised_keys=()    ,task_templates=[]    ,builder_name="""builder"""    ,config_name="""config"""    ,version="""1.0.0"""    ,splits=[{"""name""": """train""", """num_examples""": 42}]    ,download_checksums={}    ,download_size=1337    ,post_processing_size=442    ,dataset_size=1234    ,size_in_bytes=1337 + 442 + 1234    ,)
  _lowerCAmelCase		: Dict						    =  dataset_info._to_yaml_dict()
  assert sorted(_lowerCamelCase			) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML			)
  for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
    assert key in dataset_info_yaml_dict
    assert isinstance(dataset_info_yaml_dict[key]    ,(list, dict, int, str)			)
  _lowerCAmelCase		: List[str]						    =  yaml.safe_dump(_lowerCamelCase			)
  _lowerCAmelCase		: Optional[Any]						    =  yaml.safe_load(_lowerCamelCase			)
  assert dataset_info_yaml_dict == reloaded





def 							SCREAMING_SNAKE_CASE  (    ) ->   Optional[int]:
  _lowerCAmelCase		: Tuple						    =  DatasetInfo()
  _lowerCAmelCase		: int						    =  dataset_info._to_yaml_dict()
  assert dataset_info_yaml_dict == {}






@pytest.mark.parametrize(
    """dataset_infos_dict"""    ,[
        DatasetInfosDict(),
        DatasetInfosDict({"""default""": DatasetInfo()}			),
        DatasetInfosDict({"""my_config_name""": DatasetInfo()}			),
        DatasetInfosDict(
            {
                """default""": DatasetInfo(
                    description="""foo"""    ,features=Features({"""a""": Value("""int32"""			)}			)    ,builder_name="""builder"""    ,config_name="""config"""    ,version="""1.0.0"""    ,splits=[{"""name""": """train"""}]    ,download_size=42    ,)
            }			),
        DatasetInfosDict(
            {
                """v1""": DatasetInfo(dataset_size=42			),
                """v2""": DatasetInfo(dataset_size=1337			),
            }			),
    ]    ,)
def 							SCREAMING_SNAKE_CASE  (    _lowerCamelCase		: Dict    ,_lowerCamelCase		: DatasetInfosDict			) ->   List[str]:
  _lowerCAmelCase		: Dict						    =  str(_lowerCamelCase			)
  dataset_infos_dict.write_to_directory(_lowerCamelCase			)
  _lowerCAmelCase		: Optional[int]						    =  DatasetInfosDict.from_directory(_lowerCamelCase			)

  # the config_name of the dataset_infos_dict take over the attribute
  for config_name, dataset_info in dataset_infos_dict.items():
    _lowerCAmelCase		: List[Any]						    =  config_name
    # the yaml representation doesn't include fields like description or citation
    # so we just test that we can recover what we can from the yaml
    _lowerCAmelCase		: Union[str, Any]						    =  DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()			)
  assert dataset_infos_dict == reloaded

  if dataset_infos_dict:
    assert os.path.exists(os.path.join(_lowerCamelCase    ,"""README.md"""			)			)





"""simple docstring"""




import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
    ' StableDiffusionInpaintPipeline` instead.'
)




