

import pytest

import datasets


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





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							for item in items:
														if any(marker in item.keywords for marker in ['integration', 'unit']   ):
																					continue
														item.add_marker(pytest.mark.unit   )





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							config.addinivalue_line('markers'     ,							'torchaudio_latest: mark test to run with torchaudio>=0.12'   )





@pytest.fixture(autouse=UpperCamelCase__   )
def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					tmp_path_factory.getbasetemp() / 'cache'
							snake_case_           =					test_hf_cache_home / 'datasets'
							snake_case_           =					test_hf_cache_home / 'metrics'
							snake_case_           =					test_hf_cache_home / 'modules'
							monkeypatch.setattr('datasets.config.HF_DATASETS_CACHE'     ,							str(UpperCamelCase__   )   )
							monkeypatch.setattr('datasets.config.HF_METRICS_CACHE'     ,							str(UpperCamelCase__   )   )
							monkeypatch.setattr('datasets.config.HF_MODULES_CACHE'     ,							str(UpperCamelCase__   )   )
							snake_case_           =					test_hf_datasets_cache / 'downloads'
							monkeypatch.setattr('datasets.config.DOWNLOADED_DATASETS_PATH'     ,							str(UpperCamelCase__   )   )
							snake_case_           =					test_hf_datasets_cache / 'downloads' / 'extracted'
							monkeypatch.setattr('datasets.config.EXTRACTED_DATASETS_PATH'     ,							str(UpperCamelCase__   )   )





@pytest.fixture(autouse=UpperCamelCase__     ,							scope='session'   )
def       __lowerCamelCase			(				):







							'''simple docstring'''






							datasets.disable_progress_bar()





@pytest.fixture(autouse=UpperCamelCase__   )
def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							monkeypatch.setattr('datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'     ,							UpperCamelCase__   )





@pytest.fixture
def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							monkeypatch.setattr('sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'     ,							UpperCamelCase__   )







from typing import TYPE_CHECKING

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


_UpperCAmelCase	:     Any		       = {
    """configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5OnnxConfig"""],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase	:     Any		       = [
					    """LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """LongT5EncoderModel""",
					    """LongT5ForConditionalGeneration""",
					    """LongT5Model""",
					    """LongT5PreTrainedModel""",
					]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					_UpperCAmelCase	:     Optional[int]		       = [
					    """FlaxLongT5ForConditionalGeneration""",
					    """FlaxLongT5Model""",
					    """FlaxLongT5PreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_longta import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongTaConfig, LongTaOnnxConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_longta import (
										    LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
										    LongTaEncoderModel,
										    LongTaForConditionalGeneration,
										    LongTaModel,
										    LongTaPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_longta import (
										    FlaxLongTaForConditionalGeneration,
										    FlaxLongTaModel,
										    FlaxLongTaPreTrainedModel,
										)


else:
					import sys

					_UpperCAmelCase	:     Optional[Any]		       = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




