Correcting percentage string

emanbuc · Aug 27, 2021 · 674c5f5 · 674c5f5
1 parent b89843e
commit 674c5f5
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Showing 2 changed files with 11 additions and 11 deletions.
diff --git a/docs/tutorial_notebooks/tutorial2/Introduction_to_PyTorch.ipynb b/docs/tutorial_notebooks/tutorial2/Introduction_to_PyTorch.ipynb
@@ -2766,7 +2766,7 @@
     "            num_preds += data_labels.shape[0]\n",
     "            \n",
     "    acc = true_preds / num_preds\n",
-    "    print(f\"Accuracy of the model: {100.0*acc:4.2f}%%\")"
+    "    print(f\"Accuracy of the model: {100.0*acc:4.2f}%\")"
    ]
   },
   {

diff --git a/docs/tutorial_notebooks/tutorial3/Activation_Functions.ipynb b/docs/tutorial_notebooks/tutorial3/Activation_Functions.ipynb
@@ -145,7 +145,7 @@
     "    file_path = os.path.join(CHECKPOINT_PATH, file_name)\n",
     "    if not os.path.isfile(file_path):\n",
     "        file_url = base_url + file_name\n",
-    "        print(\"Downloading %s...\" % file_url)\n",
+    "        print(f\"Downloading {file_url}...\")\n",
     "        try:\n",
     "            urllib.request.urlretrieve(file_url, file_path)\n",
     "        except HTTPError as e:\n",
@@ -3085,8 +3085,8 @@
     "        net - (Optional) If given, the state dict is loaded into this model. Otherwise, a new model is created.\n",
     "    \"\"\"\n",
     "    config_file, model_file = _get_config_file(model_path, model_name), _get_model_file(model_path, model_name)\n",
-    "    assert os.path.isfile(config_file), \"Could not find the config file \\\"%s\\\". Are you sure this is the correct path and you have your model config stored here?\" % (config_file)\n",
-    "    assert os.path.isfile(model_file), \"Could not find the model file \\\"%s\\\". Are you sure this is the correct path and you have your model stored here?\" % (model_file)\n",
+    "    assert os.path.isfile(config_file), f\"Could not find the config file \\\"{config_file}\\\". Are you sure this is the correct path and you have your model config stored here?\"\n",
+    "    assert os.path.isfile(model_file), f\"Could not find the model file \\\"{model_file}\\\". Are you sure this is the correct path and you have your model stored here?\"\n",
     "    with open(config_file, \"r\") as f:\n",
     "        config_dict = json.load(f)\n",
     "    if net is None:\n",
@@ -24170,7 +24170,7 @@
     "    set_seed(42) # Setting the seed ensures that we have the same weight initialization for each activation function\n",
     "    act_fn = act_fn_by_name[act_fn_name]()\n",
     "    net_actfn = BaseNetwork(act_fn=act_fn).to(device)\n",
-    "    visualize_gradients(net_actfn, color=\"C%i\"%i)"
+    "    visualize_gradients(net_actfn, color=f\"C{i}\")"
    ]
   },
   {
@@ -24250,7 +24250,7 @@
     "            ################\n",
     "            val_acc = test_model(net, val_loader)\n",
     "            val_scores.append(val_acc)\n",
-    "            print(f\"[Epoch {epoch+1:2i}] Training accuracy: {train_acc*100.0:05.2f}%%, Validation accuracy: {val_acc*100.0:05.2f}%%\")\n",
+    "            print(f\"[Epoch {epoch+1:2i}] Training accuracy: {train_acc*100.0:05.2f}%, Validation accuracy: {val_acc*100.0:05.2f}%\")\n",
     "\n",
     "            if len(val_scores) == 1 or val_acc > val_scores[best_val_epoch]:\n",
     "                print(\"\\t   (New best performance, saving model...)\")\n",
@@ -24270,7 +24270,7 @@
     "    \n",
     "    load_model(CHECKPOINT_PATH, model_name, net=net)\n",
     "    test_acc = test_model(net, test_loader)\n",
-    "    print((f\" Test accuracy: {test_acc*100.0:4.2f}%% \").center(50, \"=\")+\"\\n\")\n",
+    "    print((f\" Test accuracy: {test_acc*100.0:4.2f}% \").center(50, \"=\")+\"\\n\")\n",
     "    return test_acc\n",
     "    \n",
     "\n",
@@ -24345,7 +24345,7 @@
     "    set_seed(42)\n",
     "    act_fn = act_fn_by_name[act_fn_name]()\n",
     "    net_actfn = BaseNetwork(act_fn=act_fn).to(device)\n",
-    "    train_model(net_actfn, \"FashionMNIST_%s\" % act_fn_name, overwrite=False)"
+    "    train_model(net_actfn, f\"FashionMNIST_{act_fn_name}\", overwrite=False)"
    ]
   },
   {
@@ -59193,8 +59193,8 @@
    ],
    "source": [
     "for i, act_fn_name in enumerate(act_fn_by_name):\n",
-    "    net_actfn = load_model(model_path=CHECKPOINT_PATH, model_name=\"FashionMNIST_%s\" % act_fn_name).to(device)\n",
-    "    visualize_activations(net_actfn, color=\"C%i\" % i)"
+    "    net_actfn = load_model(model_path=CHECKPOINT_PATH, model_name=f\"FashionMNIST_{act_fn_name}\").to(device)\n",
+    "    visualize_activations(net_actfn, color=f\"C{i}\")"
    ]
   },
   {
@@ -59261,7 +59261,7 @@
     "                    layer_index += 1\n",
     "    number_neurons_dead = [t.sum().item() for t in neurons_dead]\n",
     "    print(\"Number of dead neurons:\", number_neurons_dead)\n",
-    "    print(\"In percentage:\", \", \".join([f\"{(100.0 * num_dead / tens.shape[0]):4.2f}%%\" for tens, num_dead in zip(neurons_dead, number_neurons_dead)]))"
+    "    print(\"In percentage:\", \", \".join([f\"{(100.0 * num_dead / tens.shape[0]):4.2f}%\" for tens, num_dead in zip(neurons_dead, number_neurons_dead)]))"
    ]
   },
   {