PyTorchDiscriminator

class PyTorchDiscriminator(n_features=1, n_out=1)

Bases : DiscriminativeNetwork

Discriminator based on PyTorch

Paramètres:

• n_features (int) – Dimension of input data vector.

• n_out (int) – Dimension of the discriminator’s output vector.

Attributes

discriminator_net

Get discriminator

Methods

get_label(x[, detach])	Get data sample labels, i.e. true or fake.
gradient_penalty(x[, lambda_, k, c])	Compute gradient penalty for discriminator optimization
load_model(load_dir)	Load discriminator model
loss(x, y[, weights])	Loss function
save_model(snapshot_dir)	Save discriminator model
set_seed(seed)	Set seed.
train(data, weights[, penalty, ...])	Perform one training step w.r.t to the discriminator's parameters