accelbrainbase.samplabledata.conditionsampler._mxnet package

Submodules

accelbrainbase.samplabledata.conditionsampler._mxnet.block_diagonal_constraint_sampler module

class accelbrainbase.samplabledata.conditionsampler._mxnet.block_diagonal_constraint_sampler.BlockDiagonalConstraintSampler(cluster_n, low=0.0, high=1.0, batch_size=40, ctx=cpu(0))

Bases: accelbrainbase.samplabledata.condition_sampler.ConditionSampler

The class to draw conditional samples from distributions of the block diagonal constraint.

References

  • Ghasedi, K., Wang, X., Deng, C., & Huang, H. (2019). Balanced self-paced learning for generative adversarial clustering network. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4391-4400).
  • Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., … & Bengio, Y. (2014). Generative adversarial nets. In Advances in neural information processing systems (pp. 2672-2680).
draw()

Draw samples from distribtions.

Returns:Tuple of `mx.nd.array`s.
get_noise_sampler()

getter

noise_sampler

getter

set_noise_sampler(value)

setter

Module contents