




import pytest

import datasets


# Import fixture modules as plugins
UpperCAmelCase_		:				Union[str, Any]									=     ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]




def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				# Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
				for item in items:
								if any(marker in item.keywords for marker in ["""integration""", """unit"""]   ):
												continue
								item.add_marker(pytest.mark.unit   )




def 		lowerCAmelCase_   (	lowerCamelCase   ):
				config.addinivalue_line("""markers"""	,     """torchaudio_latest: mark test to run with torchaudio>=0.12"""   )




@pytest.fixture(autouse=lowerCamelCase   )
def 		lowerCAmelCase_   (	lowerCamelCase	,     lowerCamelCase   ):
				# test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
				__magic_name__	:	Tuple								=tmp_path_factory.getbasetemp() / """cache"""
				__magic_name__	:	Optional[int]								=test_hf_cache_home / """datasets"""
				__magic_name__	:	List[str]								=test_hf_cache_home / """metrics"""
				__magic_name__	:	List[str]								=test_hf_cache_home / """modules"""
				monkeypatch.setattr("""datasets.config.HF_DATASETS_CACHE"""	,     str(lowerCamelCase   )   )
				monkeypatch.setattr("""datasets.config.HF_METRICS_CACHE"""	,     str(lowerCamelCase   )   )
				monkeypatch.setattr("""datasets.config.HF_MODULES_CACHE"""	,     str(lowerCamelCase   )   )
				__magic_name__	:	Optional[Any]								=test_hf_datasets_cache / """downloads"""
				monkeypatch.setattr("""datasets.config.DOWNLOADED_DATASETS_PATH"""	,     str(lowerCamelCase   )   )
				__magic_name__	:	Tuple								=test_hf_datasets_cache / """downloads""" / """extracted"""
				monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""	,     str(lowerCamelCase   )   )




@pytest.fixture(autouse=lowerCamelCase	,     scope="""session"""   )
def 		lowerCAmelCase_   (	):
				datasets.disable_progress_bar()




@pytest.fixture(autouse=lowerCamelCase   )
def 		lowerCAmelCase_   (	lowerCamelCase   ):
				# don't take tests into account when counting downloads
				monkeypatch.setattr("""datasets.config.HF_UPDATE_DOWNLOAD_COUNTS"""	,     lowerCamelCase   )




@pytest.fixture
def 		lowerCAmelCase_   (	lowerCamelCase   ):
				# Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
				# To be removed once SQLAlchemy 2.0 supported
				monkeypatch.setattr("""sqlalchemy.util.deprecations.SILENCE_UBER_WARNING"""	,     lowerCamelCase   )










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_		:				Dict									=     {"configuration_wavlm": ["WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "WavLMConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase_		:				Optional[int]									=     [
							    "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

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




