update mednist (#792)

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

Author: KumoLiu

2d_classification/mednist_tutorial.ipynb

@@ -104,7 +104,7 @@
     "\n",
     "from monai.apps import download_and_extract\n",
     "from monai.config import print_config\n",
-    "from monai.data import decollate_batch\n",
+    "from monai.data import decollate_batch, DataLoader\n",
     "from monai.metrics import ROCAUCMetric\n",
     "from monai.networks.nets import DenseNet121\n",
     "from monai.transforms import (\n",
@@ -117,7 +117,6 @@
     "    RandRotate,\n",
     "    RandZoom,\n",
     "    ScaleIntensity,\n",
-    "    EnsureType,\n",
     ")\n",
     "from monai.utils import set_determinism\n",
     "\n",
@@ -361,21 +360,20 @@
    "source": [
     "train_transforms = Compose(\n",
     "    [\n",
-    "        LoadImage(image_only=True),\n",
+    "        LoadImage(),\n",
     "        AddChannel(),\n",
     "        ScaleIntensity(),\n",
     "        RandRotate(range_x=np.pi / 12, prob=0.5, keep_size=True),\n",
     "        RandFlip(spatial_axis=0, prob=0.5),\n",
     "        RandZoom(min_zoom=0.9, max_zoom=1.1, prob=0.5),\n",
-    "        EnsureType(),\n",
     "    ]\n",
     ")\n",
     "\n",
     "val_transforms = Compose(\n",
-    "    [LoadImage(image_only=True), AddChannel(), ScaleIntensity(), EnsureType()])\n",
+    "    [LoadImage(), AddChannel(), ScaleIntensity()])\n",
     "\n",
-    "y_pred_trans = Compose([EnsureType(), Activations(softmax=True)])\n",
-    "y_trans = Compose([EnsureType(), AsDiscrete(to_onehot=num_class)])"
+    "y_pred_trans = Compose([Activations(softmax=True)])\n",
+    "y_trans = Compose([AsDiscrete(to_onehot=num_class)])"
    ]
   },
   {
@@ -398,15 +396,15 @@
     "\n",
     "\n",
     "train_ds = MedNISTDataset(train_x, train_y, train_transforms)\n",
-    "train_loader = torch.utils.data.DataLoader(\n",
+    "train_loader = DataLoader(\n",
     "    train_ds, batch_size=300, shuffle=True, num_workers=10)\n",
     "\n",
     "val_ds = MedNISTDataset(val_x, val_y, val_transforms)\n",
-    "val_loader = torch.utils.data.DataLoader(\n",
+    "val_loader = DataLoader(\n",
     "    val_ds, batch_size=300, num_workers=10)\n",
     "\n",
     "test_ds = MedNISTDataset(test_x, test_y, val_transforms)\n",
-    "test_loader = torch.utils.data.DataLoader(\n",
+    "test_loader = DataLoader(\n",
     "    test_ds, batch_size=300, num_workers=10)"
    ]
   },
@@ -1328,7 +1326,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -1342,7 +1340,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,