

import numpy as np
def     UpperCAmelCase_       (						_A    ):





					'''simple docstring'''




					return 1 / (1 + np.exp(-vector    ))
def     UpperCAmelCase_       (						_A    ):





					'''simple docstring'''




					return vector * sigmoid(_A    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()





from ...utils import is_torch_available, is_transformers_available


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


