Fixed one pep8 error.

Signed-off-by: Virginia <[email protected]>

Author: Virginia Fernandez

generation/2d_diffusion_autoencoder/2d_diffusion_autoencoder_tutorial.ipynb

@@ -492,8 +492,8 @@
     "        # Create timesteps\n",
     "        timesteps = torch.randint(0, inferer.scheduler.num_train_timesteps, (batch_size,)).to(device).long()\n",
     "        # Get model prediction\n",
-    "        # cross attention expects shape [batch size, sequence length, channels], \n",
-    "        #we are use channels = latent dimension and sequence length = 1\n",
+    "        # cross attention expects shape [batch size, sequence length, channels],\n",
+    "        # we are use channels = latent dimension and sequence length = 1\n",
     "        latent = model.semantic_encoder(images)\n",
     "        noise_pred = inferer(\n",
     "            inputs=images, diffusion_model=model.unet, noise=noise, timesteps=timesteps, condition=latent.unsqueeze(2)\n",
@@ -529,10 +529,11 @@
     "        iter_loss_list.append(iter_loss / val_interval)\n",
     "        val_iter_loss_list.append(val_iter_loss / len(val_loader))\n",
     "        iter_loss = 0\n",
-    "        print(\n",
-    "            f\"Iteration {epoch} - Interval Loss {iter_loss_list[-1]:.4f}, \n",
-    "            Interval Loss Val {val_iter_loss_list[-1]:.4f}\"\n",
-    "        )\n",
+    "        to_print = [\n",
+    "            f\"Iteration {epoch} - Interval Loss {iter_loss_list[-1]:.4f}\",\n",
+    "            f\"Interval Loss Val {val_iter_loss_list[-1]:.4f}\",\n",
+    "        ]\n",
+    "        print(\"\".join(to_print))\n",
     "\n",
     "total_time = time.time() - total_start\n",
     "\n",