



'''simple docstring'''




import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset



@pytest.mark.parametrize("""dataset_size"""			,       [None, 4_0_0 * 2**2_0, 6_0_0 * 2**2_0]	)
@pytest.mark.parametrize("""input_in_memory_max_size"""			,       ["""default""", 0, 1_0_0 * 2**2_0, 9_0_0 * 2**2_0]	)
def    __lowerCamelCase						(      _lowercase			,       _lowercase			,       _lowercase	)   ->    List[str]:
							if input_in_memory_max_size != "default":
														monkeypatch.setattr(datasets.config			,       """IN_MEMORY_MAX_SIZE"""			,       _lowercase	)
							UpperCAmelCase  :	Tuple							  =	datasets.config.IN_MEMORY_MAX_SIZE
							if input_in_memory_max_size == "default":
														assert in_memory_max_size == 0
							else:
														assert in_memory_max_size == input_in_memory_max_size
							if dataset_size and in_memory_max_size:
														UpperCAmelCase  :	Any							  =	dataset_size < in_memory_max_size
							else:
														UpperCAmelCase  :	Any							  =	False
							UpperCAmelCase  :	Optional[Any]							  =	is_small_dataset(_lowercase	)
							assert result == expected






'''simple docstring'''




from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
							from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline

