
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 							a		(				snake_case__:   Dict		,  snake_case__:   Optional[int]   ):


				'''simple docstring'''
				lowercase_	    =   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}}'''   )
				lowercase_	    =   DatasetInfosDict.from_directory(snake_case__   )
				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 							a		(				snake_case__:   Optional[Any]		,  snake_case__:   DatasetInfo   ):


				'''simple docstring'''
				lowercase_	    =   str(snake_case__   )
				dataset_info.write_to_directory(snake_case__   )
				lowercase_	    =   DatasetInfo.from_directory(snake_case__   )
				assert dataset_info == reloaded
				assert os.path.exists(os.path.join(snake_case__		,  '''dataset_info.json'''   )   )




def 							a		(				):


				'''simple docstring'''
				lowercase_	    =   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=1_337		,  post_processing_size=442		,  dataset_size=1_234		,  size_in_bytes=1_337 + 442 + 1_234		,  )
				lowercase_	    =   dataset_info._to_yaml_dict()
				assert sorted(snake_case__   ) == 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)   )
				lowercase_	    =   yaml.safe_dump(snake_case__   )
				lowercase_	    =   yaml.safe_load(snake_case__   )
				assert dataset_info_yaml_dict == reloaded




def 							a		(				):


				'''simple docstring'''
				lowercase_	    =   DatasetInfo()
				lowercase_	    =   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=1_337   ),
            }   ),
    ]		,  )
def 							a		(				snake_case__:   Optional[Any]		,  snake_case__:   DatasetInfosDict   ):


				'''simple docstring'''
				lowercase_	    =   str(snake_case__   )
				dataset_infos_dict.write_to_directory(snake_case__   )
				lowercase_	    =   DatasetInfosDict.from_directory(snake_case__   )

				# the config_name of the dataset_infos_dict take over the attribute
				for config_name, dataset_info in dataset_infos_dict.items():
								lowercase_	    =   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
								lowercase_	    =   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(snake_case__		,  '''README.md'''   )   )











"""simple docstring"""


import warnings


warnings.warn(
    "memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
    "`from accelerate import find_executable_batch_size` to avoid this warning.",
    FutureWarning,
)
