# tf.contrib.gan.losses.wargs.wasserstein_generator_loss

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,
)


Wasserstein generator loss for GANs.

See Wasserstein GAN (https://arxiv.org/abs/1701.07875) for more details.

#### Args:

• 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.

#### Returns:

A loss Tensor. The shape depends on reduction.