accelbrainbase.samplabledata.truesampler package¶
Subpackages¶
Submodules¶
accelbrainbase.samplabledata.truesampler.conditional_true_sampler module¶
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class
accelbrainbase.samplabledata.truesampler.conditional_true_sampler.
ConditionalTrueSampler
¶ Bases:
accelbrainbase.samplabledata.true_sampler.TrueSampler
The class to draw true samples from distributions.
You should use this class when you want to build the Condtional GAN.
References
- 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).
- Mirza, M., & Osindero, S. (2014). Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784.
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conditonal_dim
¶ getter
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draw
()¶ Draws samples from the true distribution.
Returns: nd.ndarray of samples.
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get_conditonal_dim
()¶ getter
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set_conditonal_dim
(value)¶ setter
accelbrainbase.samplabledata.truesampler.labeled_true_sampler module¶
-
class
accelbrainbase.samplabledata.truesampler.labeled_true_sampler.
LabeledTrueSampler
¶ Bases:
accelbrainbase.samplabledata.true_sampler.TrueSampler
The class to draw true labeled samples from distributions.
References
- Bousmalis, K., Silberman, N., Dohan, D., Erhan, D., & Krishnan, D. (2017). Unsupervised pixel-level domain adaptation with generative adversarial networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3722-3731).
- 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).
- Mirza, M., & Osindero, S. (2014). Conditional generative adversarial nets. arXiv preprint arXiv:1411.1784.
-
get_labeled_image_iterator
()¶ getter
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labeled_image_iterator
¶ getter
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set_labeled_image_iterator
(value)¶ setter
accelbrainbase.samplabledata.truesampler.normal_true_sampler module¶
-
class
accelbrainbase.samplabledata.truesampler.normal_true_sampler.
NormalTrueSampler
(loc=0.0, scale=1.0, batch_size=40, seq_len=0, channel=3, height=96, width=96, ctx=gpu(0))¶ Bases:
accelbrainbase.samplabledata.true_sampler.TrueSampler
The class to draw fake samples from Gaussian distributions.
References
- 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).
- Makhzani, A., Shlens, J., Jaitly, N., Goodfellow, I., & Frey, B. (2015). Adversarial autoencoders. arXiv preprint arXiv:1511.05644.