tf.contrib.gan.losses.wargs.wasserstein_generator_loss( discriminator_gen_outputs, weights=1.0, scope=None, loss_collection=tf.GraphKeys.LOSSES, reduction=losses.Reduction.SUM_BY_NONZERO_WEIGHTS, add_summaries=False )
Defined in tensorflow/contrib/gan/python/losses/python/losses_impl.py
.
Wasserstein generator loss for GANs.
See Wasserstein GAN
(https://arxiv.org/abs/1701.07875) for more details.
discriminator_gen_outputs
: Discriminator output on generated data. Expected to be in the range of (-inf, inf).weights
: Optional Tensor
whose rank is either 0, or the same rank as discriminator_gen_outputs
, and must be broadcastable to discriminator_gen_outputs
(i.e., all dimensions must be either 1
, or the same as the corresponding dimension).scope
: The scope for the operations performed in computing the loss.loss_collection
: collection to which this loss will be added.reduction
: A tf.losses.Reduction
to apply to loss.add_summaries
: Whether or not to add detailed summaries for the loss.A loss Tensor. The shape depends on reduction
.
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/gan/losses/wargs/wasserstein_generator_loss