Chenhui/hyperdrive windows (#185)

* resolve format issues

* update log path and tensorboard path

* remove subprocess import

* fetch common utils from chenhui/dilatedcnn_windows

* update notebook

* removed explain module and added notebooks module

* get updated ci yml files

* updated kernel name

Former-commit-id: deac0cce96

examples/grocery_sales/python/03_model_tune_deploy/azure_hyperdrive_lightgbm.ipynb

@@ -55,6 +55,13 @@
     "%autoreload 2"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    ">Note: If you run into any issue with installing and enabling the AzureML widgets below, please *uncomment* the first line in the following cell to manually install `azureml-widgets`."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -81,6 +88,7 @@
    ],
    "source": [
     "# Install and enable AzureML widgets\n",
+    "#!pip -q install azureml-widgets==1.0.85\n",
     "!jupyter nbextension install --py --user azureml.widgets\n",
     "!jupyter nbextension enable --py --user azureml.widgets"
    ]
@@ -106,7 +114,6 @@
     "import shutil\n",
     "import azureml\n",
     "import requests\n",
-    "import subprocess\n",
     "import numpy as np\n",
     "from azureml.core import (\n",
     "    Experiment,\n",
@@ -130,7 +137,7 @@
     ")\n",
     "from azureml.core.webservice import AciWebservice\n",
     "from azureml.core.model import Model, InferenceConfig\n",
-    "from fclib.common.utils import git_repo_path\n",
+    "from fclib.common.utils import git_repo_path, module_path\n",
     "from fclib.azureml.azureml_utils import (\n",
     "    get_or_create_workspace,\n",
     "    get_or_create_amlcompute,\n",
@@ -280,8 +287,7 @@
    "outputs": [],
    "source": [
     "# Get Python interpreter path\n",
-    "python_path = subprocess.check_output(\"which python\", shell=True)\n",
-    "python_path = python_path.decode(\"utf-8\")[:-1]\n",
+    "python_path = module_path(\"forecasting_env\", \"python\")\n",
     "\n",
     "# Configure local, user managed environment\n",
     "run_config_user_managed = RunConfiguration()\n",

tests/integration/test_notebooks_python.py

@@ -7,13 +7,14 @@ import papermill as pm
 import scrapbook as sb
 
 ABS_TOL = 5.0
+KERNEL = "forecasting_env"
 
 
 @pytest.mark.integration
 def test_lightgbm_quick_start(notebooks):
     notebook_path = notebooks["lightgbm_quick_start"]
     output_notebook_path = os.path.join(os.path.dirname(notebook_path), "output.ipynb")
-    pm.execute_notebook(notebook_path, output_notebook_path, kernel_name="forecast_cpu")
+    pm.execute_notebook(notebook_path, output_notebook_path, kernel_name=KERNEL)
     nb = sb.read_notebook(output_notebook_path)
     df = nb.scraps.dataframe
     assert df.shape[0] == 1
@@ -26,7 +27,7 @@ def test_autoarima_quick_start(notebooks):
     notebook_path = notebooks["autoarima_quick_start"]
     output_notebook_path = os.path.join(os.path.dirname(notebook_path), "output.ipynb")
     pm.execute_notebook(
-        notebook_path, output_notebook_path, kernel_name="forecast_cpu", parameters=dict(STORE_SUBSET=True),
+        notebook_path, output_notebook_path, kernel_name=KERNEL, parameters=dict(STORE_SUBSET=True),
     )
     nb = sb.read_notebook(output_notebook_path)
     df = nb.scraps.dataframe
@@ -41,7 +42,7 @@ def test_lightgbm_multi_round(notebooks):
     notebook_path = notebooks["lightgbm_multi_round"]
     output_notebook_path = os.path.join(os.path.dirname(notebook_path), "output.ipynb")
     pm.execute_notebook(
-        notebook_path, output_notebook_path, kernel_name="forecast_cpu", parameters=dict(N_SPLITS=1),
+        notebook_path, output_notebook_path, kernel_name=KERNEL, parameters=dict(N_SPLITS=1),
     )
     nb = sb.read_notebook(output_notebook_path)
     df = nb.scraps.dataframe
@@ -55,7 +56,7 @@ def test_dilatedcnn_multi_round(notebooks):
     notebook_path = notebooks["dilatedcnn_multi_round"]
     output_notebook_path = os.path.join(os.path.dirname(notebook_path), "output.ipynb")
     pm.execute_notebook(
-        notebook_path, output_notebook_path, kernel_name="forecast_cpu", parameters=dict(N_SPLITS=2),
+        notebook_path, output_notebook_path, kernel_name=KERNEL, parameters=dict(N_SPLITS=2),
     )
     nb = sb.read_notebook(output_notebook_path)
     df = nb.scraps.dataframe
@@ -69,7 +70,7 @@ def test_autoarima_multi_round(notebooks):
     notebook_path = notebooks["autoarima_multi_round"]
     output_notebook_path = os.path.join(os.path.dirname(notebook_path), "output.ipynb")
     pm.execute_notebook(
-        notebook_path, output_notebook_path, kernel_name="forecast_cpu", parameters=dict(N_SPLITS=2, STORE_SUBSET=True),
+        notebook_path, output_notebook_path, kernel_name=KERNEL, parameters=dict(N_SPLITS=2, STORE_SUBSET=True),
     )
     nb = sb.read_notebook(output_notebook_path)
     df = nb.scraps.dataframe

tools/environment.yml

@@ -40,4 +40,4 @@ dependencies:
     - nteract-scrapbook==0.3.1
     - statsmodels>=0.11.1
     - pmdarima>=1.1.1
-    - azureml-sdk[explain,automl]==1.0.85
+    - azureml-sdk[automl,notebooks]==1.0.85