Merge pull request #202 from Project-MONAI/186-consistent-usage-of-annotation-syntax

Fix typo

Author: Warvito

README.md

@@ -3,7 +3,7 @@
 </p>
 
 # MONAI Generative Models
-Prototyping repo for generative models to be integrated into MONAI core.
+Prototyping repository for generative models to be integrated into MONAI core.
 ## Features
 * Network architectures: Diffusion Model, Autoencoder-KL, VQ-VAE, (Multi-scale) Patch-GAN discriminator.
 * Diffusion Model Schedulers: DDPM, DDIM, and PNDM.

tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb

@@ -818,7 +818,7 @@
     "use_pretrained = False\n",
     "\n",
     "if use_pretrained:\n",
-    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models\", model=\"ddpm_2d\", verbose=True).to(device)\n",
+    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models:v0.2\", model=\"ddpm_2d\", verbose=True).to(device)\n",
     "else:\n",
     "    n_epochs = 100\n",
     "    val_interval = 10\n",
@@ -1096,7 +1096,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,

tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py

@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.14.4
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: Python 3 (ipykernel)
 #     language: python
@@ -207,7 +207,7 @@
 use_pretrained = False
 
 if use_pretrained:
-    model = torch.hub.load("marksgraham/pretrained_generative_models", model="ddpm_2d", verbose=True).to(device)
+    model = torch.hub.load("marksgraham/pretrained_generative_models:v0.2", model="ddpm_2d", verbose=True).to(device)
 else:
     n_epochs = 100
     val_interval = 10

tutorials/generative/2d_ddpm/2d_ddpm_inpainting.ipynb

@@ -636,7 +636,7 @@
     "use_pretrained = False\n",
     "\n",
     "if use_pretrained:\n",
-    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models\", model=\"ddpm_2d\", verbose=True).to(device)\n",
+    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models:v0.2\", model=\"ddpm_2d\", verbose=True).to(device)\n",
     "else:\n",
     "    n_epochs = 50\n",
     "    val_interval = 5\n",
@@ -914,7 +914,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,

tutorials/generative/2d_ddpm/2d_ddpm_inpainting.py

@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.14.4
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: Python 3 (ipykernel)
 #     language: python
@@ -191,7 +191,7 @@
 use_pretrained = False
 
 if use_pretrained:
-    model = torch.hub.load("marksgraham/pretrained_generative_models", model="ddpm_2d", verbose=True).to(device)
+    model = torch.hub.load("marksgraham/pretrained_generative_models:v0.2", model="ddpm_2d", verbose=True).to(device)
 else:
     n_epochs = 50
     val_interval = 5

tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb

@@ -42,6 +42,7 @@
    "execution_count": 2,
    "id": "dd62a552",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -137,6 +138,7 @@
    "execution_count": 3,
    "id": "8fc58c80",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -169,6 +171,7 @@
    "execution_count": 4,
    "id": "ad5a1948",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -194,6 +197,7 @@
    "execution_count": 5,
    "id": "65e1c200",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -232,6 +236,7 @@
    "execution_count": 6,
    "id": "e2f9bebd",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -271,6 +276,7 @@
    "execution_count": 7,
    "id": "938318c2",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -320,6 +326,7 @@
    "execution_count": 8,
    "id": "b698f4f8",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -372,6 +379,7 @@
    "execution_count": 9,
    "id": "2c52e4f4",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -415,6 +423,7 @@
    "execution_count": 10,
    "id": "0f697a13",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -763,7 +772,7 @@
     "use_pretrained = False\n",
     "\n",
     "if use_pretrained:\n",
-    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models\", model=\"ddpm_2d\", verbose=True).to(device)\n",
+    "    model = torch.hub.load(\"marksgraham/pretrained_generative_models:v0.2\", model=\"ddpm_2d\", verbose=True).to(device)\n",
     "else:\n",
     "    n_epochs = 75\n",
     "    val_interval = 5\n",
@@ -852,6 +861,7 @@
    "execution_count": 11,
    "id": "2cdcda81",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -901,6 +911,7 @@
    "execution_count": 12,
    "id": "1427e5d4",
    "metadata": {
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -984,7 +995,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,

tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py

@@ -6,7 +6,7 @@
 #       extension: .py
 #       format_name: percent
 #       format_version: '1.3'
-#       jupytext_version: 1.14.4
+#       jupytext_version: 1.14.1
 #   kernelspec:
 #     display_name: Python 3 (ipykernel)
 #     language: python
@@ -190,7 +190,7 @@
 use_pretrained = False
 
 if use_pretrained:
-    model = torch.hub.load("marksgraham/pretrained_generative_models", model="ddpm_2d", verbose=True).to(device)
+    model = torch.hub.load("marksgraham/pretrained_generative_models:v0.2", model="ddpm_2d", verbose=True).to(device)
 else:
     n_epochs = 75
     val_interval = 5

tutorials/generative/distributed_training/ddpm_training_ddp.py

@@ -197,7 +197,7 @@ def main_worker(args):
 
     inferer = DiffusionInferer(scheduler)
     # wrap the model with DistributedDataParallel module
-    model = DistributedDataParallel(model, device_ids=[device])
+    model = DistributedDataParallel(model, device_ids=[device], find_unused_parameters=True)
 
     # start a typical PyTorch training
     best_metric = 10000