accelbrainbase.samplabledata.conditionsampler._mxnet package¶
Submodules¶
accelbrainbase.samplabledata.conditionsampler._mxnet.block_diagonal_constraint_sampler module¶
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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).
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get_noise_sampler
()¶ getter
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noise_sampler
¶ getter
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set_noise_sampler
(value)¶ setter