f93beff338925cc1bf1b3ff1b32a2c440a4c9427,tests/_tests_scripts/z_mvp_mnist_gan.py,CustomRunner,_handle_batch,#CustomRunner#Any#,18

Before Change

        Docs.
        
        images, _ = batch
        images = images.view(images.size(0), -1)
        bs = images.shape[0]
        z = torch.randn(bs, 128).to(self.device)
        generated_images = self.model["generator"](z)

        // generator step
        // predictions & labels
        generated_labels = torch.ones(bs, 1).to(self.device)
        generated_pred = self.model["discriminator"](generated_images)

        // loss
        loss_generator = F.binary_cross_entropy(
            generated_pred, generated_labels
        )
        self.state.batch_metrics["loss_generator"] = loss_generator

        // discriminator step
        // real

After Change

            self.device
        )
        // Assemble labels that say "all real images"
        misleading_labels = torch.zeros((batch_size, 1)).to(self.device)

        // Train the generator
        generated_images = self.model["generator"](random_latent_vectors)
        predictions = self.model["discriminator"](generated_images)

Instances