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This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters. Learn more about bidirectional Unicode charactersOriginal file line number Diff line number Diff line change @@ -0,0 +1,32 @@ def get_discriminator_loss(generator, discriminator, criterion, real_samples, n_samples, dim_noise, device): ''' Discriminator predict and get loss Parameters: generator: generator network discriminator: discriminator network criterion: loss function, likely `nn.BCEWithLogitsLoss()` real_samples: samples from training dataset n_samples: int number of samples to generate dim_noise: int dimension of noise vector device: string device, cpu or cuda Returns: discriminator_loss: loss scalar ''' random_noise = get_noise(n_samples, dim_noise, device=device) generated_samples = generator(random_noise) discriminator_fake_pred = discriminator(generated_samples.detach()) discriminator_fake_loss = criterion(discriminator_fake_pred, torch.zeros_like(discriminator_fake_pred)) discriminator_real_pred = discriminator(real_samples) discriminator_real_loss = criterion(discriminator_real_pred, torch.ones_like(discriminator_real_pred)) discriminator_loss = (discriminator_fake_loss + discriminator_real_loss) / 2 return discriminator_loss