update nb with fill_missing_args

notebooks/01_model_results.ipynb

@@ -167,6 +167,9 @@
     }
    ],
    "source": [
+    "# fill missing args with default values from argparse\n",
+    "r = notebook_helper.fill_missing_args_with_default(r, fname='01_train_model.py')\n",
+    "\n",
     "# group using these experiment hyperparams when averaging over random seeds\n",
     "group_keys = [k for k in notebook_helper.get_main_args_list(fname='01_train_model.py') if not k == 'seed']\n",
     "ravg = (\n",
@@ -266,7 +269,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.8.10 (default, Nov 14 2022, 12:59:47) \n[GCC 9.4.0]"
   },
   "orig_nbformat": 4,
   "vscode": {

notebooks/notebook_helper.py

@@ -14,3 +14,20 @@ def get_main_args_list(fname='01_train_model.py'):
     train_script = __import__(fname)
     args = train_script.add_main_args(argparse.ArgumentParser()).parse_args([])
     return list(vars(args).keys())
+
+def fill_missing_args_with_default(df, fname='01_train_model.py'):
+    """Returns main arguments from the argparser used by an experiments script
+    """
+    if fname.endswith('.py'):
+        fname = fname[:-3]
+    sys.path.append(join(repo_dir, 'experiments'))
+    train_script = __import__(fname)
+    parser = train_script.add_main_args(argparse.ArgumentParser())
+    parser = train_script.add_computational_args(parser)
+    args = parser.parse_args([])
+    args_dict = vars(args)
+    for k, v in args_dict.items():
+        if k not in df.columns:
+            df[k] = v
+        df[k] = df[k].fillna(v)
+    return df