
"""simple docstring"""




import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


lowerCAmelCase__				=					[
    {'dataset': 'wikipedia', 'config_name': '20220301.de'},
    {'dataset': 'wikipedia', 'config_name': '20220301.en'},
    {'dataset': 'wikipedia', 'config_name': '20220301.fr'},
    {'dataset': 'wikipedia', 'config_name': '20220301.frr'},
    {'dataset': 'wikipedia', 'config_name': '20220301.it'},
    {'dataset': 'wikipedia', 'config_name': '20220301.simple'},
    {'dataset': 'snli', 'config_name': 'plain_text'},
    {'dataset': 'eli5', 'config_name': 'LFQA_reddit'},
    {'dataset': 'wiki40b', 'config_name': 'en'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.nq.compressed'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.nq.no_index'},
    {'dataset': 'wiki_dpr', 'config_name': 'psgs_w100.multiset.no_index'},
    {'dataset': 'natural_questions', 'config_name': 'default'},
]



def 							_lowerCamelCase			(			__a=True     ):
		if with_config:
				return [
				    {
				        "testcase_name": d["dataset"] + "/" + d["config_name"],
				        "dataset": d["dataset"],
				        "config_name": d["config_name"],
				    }
				    for d in DATASETS_ON_HF_GCP
				]
		else:
				return [
				    {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
				]





@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=__lowercase ) )
class 			snake_case  (				__lowercase ):
							UpperCAmelCase__      =   None
							UpperCAmelCase__      =   None

							def _lowercase       (self							,							SCREAMING_SNAKE_CASE_							,							SCREAMING_SNAKE_CASE_     ):

									"""simple docstring"""







									with TemporaryDirectory() as tmp_dir:
											SCREAMING_SNAKE_CASE_    			=			dataset_module_factory(SCREAMING_SNAKE_CASE_							,							cache_dir=SCREAMING_SNAKE_CASE_     )

											SCREAMING_SNAKE_CASE_    			=			import_main_class(dataset_module.module_path							,							dataset=SCREAMING_SNAKE_CASE_     )

											SCREAMING_SNAKE_CASE_    			=			builder_cls(
											    cache_dir=SCREAMING_SNAKE_CASE_							,							config_name=SCREAMING_SNAKE_CASE_							,							hash=dataset_module.hash							,							)

											SCREAMING_SNAKE_CASE_    			=			'''/'''.join(
											    [
											        HF_GCP_BASE_URL,
											        builder_instance._relative_data_dir(with_hash=SCREAMING_SNAKE_CASE_     ).replace(os.sep							,							'''/'''     ),
											        config.DATASET_INFO_FILENAME,
											    ]     )
											SCREAMING_SNAKE_CASE_    			=			cached_path(SCREAMING_SNAKE_CASE_							,							cache_dir=SCREAMING_SNAKE_CASE_     )
											self.assertTrue(os.path.exists(SCREAMING_SNAKE_CASE_     )     )







@pytest.mark.integration
def 							_lowerCamelCase			(			__a     ):
		SCREAMING_SNAKE_CASE_    			=			tmp_path_factory.mktemp('''test_hf_gcp'''     ) / '''test_wikipedia_simple'''
		SCREAMING_SNAKE_CASE_    			=			dataset_module_factory('''wikipedia''',				cache_dir=__a     )
		SCREAMING_SNAKE_CASE_    			=			import_main_class(dataset_module.module_path     )
		SCREAMING_SNAKE_CASE_    			=			builder_cls(
		    cache_dir=__a,				config_name='''20220301.frr''',				hash=dataset_module.hash,				)
		# use the HF cloud storage, not the original download_and_prepare that uses apache-beam
		SCREAMING_SNAKE_CASE_    			=			None
		builder_instance.download_and_prepare()
		SCREAMING_SNAKE_CASE_    			=			builder_instance.as_dataset()
		assert ds



@pytest.mark.integration
def 							_lowerCamelCase			(			__a     ):
		SCREAMING_SNAKE_CASE_    			=			dataset_module_factory('''wikipedia''',				cache_dir=__a     )
		SCREAMING_SNAKE_CASE_    			=			import_main_class(dataset_module.module_path,				dataset=__a     )
		SCREAMING_SNAKE_CASE_    			=			builder_cls(
		    cache_dir=__a,				config_name='''20220301.frr''',				hash=dataset_module.hash,				)
		SCREAMING_SNAKE_CASE_    			=			builder_instance.as_streaming_dataset()
		assert ds
		assert isinstance(__a,				__a     )
		assert "train" in ds
		assert isinstance(ds['''train'''],				__a     )
		assert next(iter(ds['''train''']     )     )

"""simple docstring"""




from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ..utils.dummy_pt_objects import *  # noqa F403
else:
						from .scheduling_consistency_models import CMStochasticIterativeScheduler
						from .scheduling_ddim import DDIMScheduler
						from .scheduling_ddim_inverse import DDIMInverseScheduler
						from .scheduling_ddim_parallel import DDIMParallelScheduler
						from .scheduling_ddpm import DDPMScheduler
						from .scheduling_ddpm_parallel import DDPMParallelScheduler
						from .scheduling_deis_multistep import DEISMultistepScheduler
						from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
						from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
						from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
						from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
						from .scheduling_euler_discrete import EulerDiscreteScheduler
						from .scheduling_heun_discrete import HeunDiscreteScheduler
						from .scheduling_ipndm import IPNDMScheduler
						from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
						from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
						from .scheduling_karras_ve import KarrasVeScheduler
						from .scheduling_pndm import PNDMScheduler
						from .scheduling_repaint import RePaintScheduler
						from .scheduling_sde_ve import ScoreSdeVeScheduler
						from .scheduling_sde_vp import ScoreSdeVpScheduler
						from .scheduling_unclip import UnCLIPScheduler
						from .scheduling_unipc_multistep import UniPCMultistepScheduler
						from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
						from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ..utils.dummy_flax_objects import *  # noqa F403
else:
						from .scheduling_ddim_flax import FlaxDDIMScheduler
						from .scheduling_ddpm_flax import FlaxDDPMScheduler
						from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
						from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
						from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
						from .scheduling_pndm_flax import FlaxPNDMScheduler
						from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
						from .scheduling_utils_flax import (
						    FlaxKarrasDiffusionSchedulers,
						    FlaxSchedulerMixin,
						    FlaxSchedulerOutput,
						    broadcast_to_shape_from_left,
						)


try:
						if not (is_torch_available() and is_scipy_available()):
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
						from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
						if not (is_torch_available() and is_torchsde_available()):
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
						from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler