0de148f6892361e61d4b68cf97814e73692f6b1a,docs/_static/examples/gan.py,,,#,124

Before Change

// Model and optimizer
model = GAN()
optim = torch.optim.Adam(model.parameters(), lr=lr, betas=(0.5, 0.999))


@tb.metrics.running_mean

After Change

    state[DISC_OPT].step()

from torchbearer.metrics import mean, running_mean
metrics = ["loss", mean(running_mean(D_LOSS)), mean(running_mean(G_LOSS))]

trial = tb.Trial(generator, None, criterion=gen_crit, metrics=metrics, callbacks=[saver_callback])
trial.with_train_generator(dataloader, steps=200000)

Instances