
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 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			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_						=			DatasetInfosDict.from_directory(lowerCamelCase__    )
				assert dataset_infos
				assert dataset_infos["default"].dataset_size == 4_2





@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=4_2	, ),
    ]	, )
def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			str(lowerCamelCase__    )
				dataset_info.write_to_directory(lowerCamelCase__    )
				lowerCamelCase_						=			DatasetInfo.from_directory(lowerCamelCase__    )
				assert dataset_info == reloaded
				assert os.path.exists(os.path.join(lowerCamelCase__	, "dataset_info.json"    )    )





def 			lowerCamelCase_ (				):
				lowerCamelCase_						=			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": 4_2}]	, download_checksums={}	, download_size=1_3_3_7	, post_processing_size=4_4_2	, dataset_size=1_2_3_4	, size_in_bytes=1_3_3_7 + 4_4_2 + 1_2_3_4	, )
				lowerCamelCase_						=			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_						=			yaml.safe_dump(lowerCamelCase__    )
				lowerCamelCase_						=			yaml.safe_load(lowerCamelCase__    )
				assert dataset_info_yaml_dict == reloaded





def 			lowerCamelCase_ (				):
				lowerCamelCase_						=			DatasetInfo()
				lowerCamelCase_						=			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=4_2	, )
            }    ),
        DatasetInfosDict(
            {
                "v1": DatasetInfo(dataset_size=4_2    ),
                "v2": DatasetInfo(dataset_size=1_3_3_7    ),
            }    ),
    ]	, )
def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			str(lowerCamelCase__    )
				dataset_infos_dict.write_to_directory(lowerCamelCase__    )
				lowerCamelCase_						=			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_						=			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_						=			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"    )    )




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A				={'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A				=[
			    '''WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''WavLMForAudioFrameClassification''',
			    '''WavLMForCTC''',
			    '''WavLMForSequenceClassification''',
			    '''WavLMForXVector''',
			    '''WavLMModel''',
			    '''WavLMPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_wavlm import (
						    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
						    WavLMForAudioFrameClassification,
						    WavLMForCTC,
						    WavLMForSequenceClassification,
						    WavLMForXVector,
						    WavLMModel,
						    WavLMPreTrainedModel,
						)

else:
			import sys

			__A				=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


