Update notebooks

training/01.train-hyperparameter-tune-deploy-with-pytorch/01.train-hyperparameter-tune-deploy-with-pytorch.ipynb

@@ -43,6 +43,28 @@
         "print(\"SDK version:\", azureml.core.VERSION)"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## Diagnostics\n",
+        "Opt-in diagnostics for better experience, quality, and security of future releases."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "tags": [
+          "Diagnostics"
+        ]
+      },
+      "outputs": [],
+      "source": [
+        "from azureml.telemetry import set_diagnostics_collection\n",
+        "set_diagnostics_collection(send_diagnostics = True)"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -244,7 +266,7 @@
         "In `pytorch_train.py`, we will log some metrics to our AML run. To do so, we will access the AML run object within the script:\n",
         "```Python\n",
         "from azureml.core.run import Run\n",
-        "run = Run.get_submitted_run()\n",
+        "run = Run.get_context()\n",
         "```\n",
         "Further within `pytorch_train.py`, we log the learning rate and momentum parameters, and the best validation accuracy the model achieves:\n",
         "```Python\n",
@@ -735,6 +757,11 @@
     }
   ],
   "metadata": {
+    "authors": [
+      {
+        "name": "minxia"
+      }
+    ],
     "kernelspec": {
       "display_name": "Python 3.6",
       "language": "python",

training/01.train-hyperparameter-tune-deploy-with-pytorch/pytorch_train.py

@@ -17,7 +17,7 @@ import argparse
 
 from azureml.core.run import Run
 # get the Azure ML run object
-run = Run.get_submitted_run()
+run = Run.get_context()
 
 
 def load_data(data_dir):
@@ -162,8 +162,8 @@ def main():
     parser.add_argument('--data_dir', type=str, help='directory of training data')
     parser.add_argument('--num_epochs', type=int, default=25, help='number of epochs to train')
     parser.add_argument('--output_dir', type=str, help='output directory')
-    parser.add_argument('--learning_rate', type=float, help='learning rate')
-    parser.add_argument('--momentum', type=float, help='momentum')
+    parser.add_argument('--learning_rate', type=float, default=0.001, help='learning rate')
+    parser.add_argument('--momentum', type=float, default=0.9, help='momentum')
     args = parser.parse_args()
 
     print("data directory is: " + args.data_dir)