Fix format (#349)

Signed-off-by: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>

Author: Warvito

generative/metrics/ms_ssim.py

@@ -121,7 +121,7 @@ def _compute_metric(self, y_pred: torch.Tensor, y: torch.Tensor) -> torch.Tensor
         avg_pool = getattr(F, f"avg_pool{self.spatial_dims}d")
 
         multiscale_list: list[torch.Tensor] = []
-        for i in range(len(weights)):
+        for _ in range(len(weights)):
             ssim, cs = compute_ssim_and_cs(
                 y_pred=y_pred,
                 y=y,

tutorials/generative/image_to_image_translation/tutorial_segmentation_with_ddpm.ipynb

@@ -182,7 +182,7 @@
     "from monai.apps import DecathlonDataset\n",
     "from monai.config import print_config\n",
     "from monai.data import DataLoader\n",
-    "from monai.utils import first, set_determinism\n",
+    "from monai.utils import set_determinism\n",
     "from torch.cuda.amp import GradScaler, autocast\n",
     "from tqdm import tqdm\n",
     "\n",
@@ -693,9 +693,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "scheduler = DDPMScheduler(\n",
-    "    num_train_timesteps=1000,\n",
-    ")\n",
+    "scheduler = DDPMScheduler(num_train_timesteps=1000)\n",
     "optimizer = torch.optim.Adam(params=model.parameters(), lr=2.5e-5)\n",
     "inferer = DiffusionInferer(scheduler)"
    ]
@@ -1462,7 +1460,7 @@
     "plt.imshow(var[0, ...].cpu(), vmin=0, vmax=1, cmap=\"jet\")  # We plot the variance map\n",
     "plt.tight_layout()\n",
     "plt.axis(\"off\")\n",
-    "plt.show()\n"
+    "plt.show()"
    ]
   }
  ],

tutorials/generative/image_to_image_translation/tutorial_segmentation_with_ddpm.py

@@ -184,9 +184,7 @@
 )
 model.to(device)
 
-scheduler = DDPMScheduler(
-    num_train_timesteps=1000,
-)
+scheduler = DDPMScheduler(num_train_timesteps=1000)
 optimizer = torch.optim.Adam(params=model.parameters(), lr=2.5e-5)
 inferer = DiffusionInferer(scheduler)
 
@@ -396,4 +394,3 @@ def dice_coeff(im1, im2, empty_score=1.0):
 plt.tight_layout()
 plt.axis("off")
 plt.show()
-