Fix formatting issues

Azure · Oct 29, 2024 · 1fb52e0 · 1fb52e0
1 parent 132522e
commit 1fb52e0
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Showing 2 changed files with 5 additions and 36 deletions.
diff --git a/...toml-forecasting-forecast-function/auto-ml-forecasting-function-gap-batch-inference.ipynb b/...toml-forecasting-forecast-function/auto-ml-forecasting-function-gap-batch-inference.ipynb
@@ -79,7 +79,6 @@
    "outputs": [],
    "source": [
     "from mlflow.tracking.client import MlflowClient\n",
-    "from mlflow.artifacts import download_artifacts\n",
     "\n",
     "# Set the MLFLOW TRACKING URI\n",
     "mlflow.set_tracking_uri(MLFLOW_TRACKING_URI)\n",
@@ -260,9 +259,7 @@
    "outputs": [],
    "source": [
     "# We stored the training and test data during training\n",
-    "df_train = pd.read_parquet(\n",
-    "    \"./data/training-mltable-folder/df_train.parquet\"\n",
-    ")  \n",
+    "df_train = pd.read_parquet(\"./data/training-mltable-folder/df_train.parquet\")\n",
     "df_test = pd.read_parquet(\"./data/testing-mltable-folder/df_test.parquet\")"
    ]
   },
@@ -387,21 +384,6 @@
     "### Invoke the endpoint with the test data"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.system(\"az login\")\n",
-    "\n",
-    "def refresh_token():\n",
-    "    os.system(\"az account get-access-token\")\n",
-    "refresh_token()\n",
-    "# Call refresh_token() at regular intervals in your notebook, if necessary"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 27,
@@ -552,6 +534,7 @@
    "source": [
     "# Now make the forecast query from context. This is the main thing for predicting gap data\n",
     "from helper import make_forecasting_query\n",
+    "\n",
     "X_pred, y_pred = make_forecasting_query(\n",
     "    fulldata, TIME_COLUMN_NAME, TARGET_COLUMN_NAME, forecast_origin, horizon, lookback\n",
     ")\n",
@@ -605,21 +588,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.system(\"az login\")\n",
-    "\n",
-    "def refresh_token():\n",
-    "    os.system(\"az account get-access-token\")\n",
-    "refresh_token()\n",
-    "# Call refresh_token() at regular intervals in your notebook, if necessary"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 61,
@@ -685,7 +653,7 @@
    "outputs": [],
    "source": [
     "# show the forecast aligned without the generated features\n",
-    "X_show = gap_fcst_df[gap_fcst_df['data_type']==\"test\"]\n",
+    "X_show = gap_fcst_df[gap_fcst_df[\"data_type\"] == \"test\"]\n",
     "X_show"
    ]
   }

diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-forecast-function/helper.py b/sdk/python/jobs/automl-standalone-jobs/automl-forecasting-forecast-function/helper.py
@@ -3,6 +3,7 @@
 import pandas as pd
 import numpy as np
 
+
 def get_timeseries(
     train_len: int,
     test_len: int,
@@ -115,4 +116,4 @@ def make_forecasting_query(
 
     X_pred = pd.concat([X_past, X_future])
     y_pred = np.concatenate([y_past, y_query])
-    return X_pred, y_pred
+    return X_pred, y_pred