Test Run for v0.1.0b5 (Azure#1473)

* Updated setup.sh to use latest SDK * Updated setup.sh for sample validation * Ran black on sdk * Ran black on cli * Ran black for scripts * Added dummy comment to rerun validation * Removed dummy comment
scbedd · Jul 11, 2022 · d9f75fd · d9f75fd
1 parent 43f88da
commit d9f75fd
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Showing 5 changed files with 19 additions and 29 deletions.
diff --git a/...nents/image_classification_with_densenet/image_cnn_train/image_classification/training.py b/...nents/image_classification_with_densenet/image_cnn_train/image_classification/training.py
@@ -257,7 +257,7 @@ def _lr_fn(iteration, epoch):
             lr = base_lr * (epoch + 1) / warmup_length
         else:
             e = epoch - warmup_length
-            lr = base_lr * (epoch_decay ** e)
+            lr = base_lr * (epoch_decay**e)
         return lr
 
     return lr_policy(_lr_fn, logger=logger)

diff --git a/scripts/validation/check_experiment_result.py b/scripts/validation/check_experiment_result.py
@@ -174,11 +174,15 @@ def checkVisionTrainRun(child_runs, expected_min_score, expected_max_score):
         )
         print("Primary metric value of {}: {}".format(hd_run.id, best_metric))
 
-        lower_err_msg = "Primary metric value was lower than the expected min value of {}".format(
-            expected_min_score
+        lower_err_msg = (
+            "Primary metric value was lower than the expected min value of {}".format(
+                expected_min_score
+            )
         )
-        higher_err_msg = "Primary metric value was higher than the expected max value of {}".format(
-            expected_max_score
+        higher_err_msg = (
+            "Primary metric value was higher than the expected max value of {}".format(
+                expected_max_score
+            )
         )
         assert best_metric >= expected_min_score, lower_err_msg
         assert best_metric <= expected_max_score, higher_err_msg

diff --git a/sdk/assets/data/data.ipynb b/sdk/assets/data/data.ipynb
@@ -65,16 +65,13 @@
     "from azure.ai.ml import Input\n",
     "from azure.ai.ml.constants import AssetTypes\n",
     "\n",
-    "# === Note on path === \n",
-    "# can be can be a local path or a cloud path. AzureML supports https://`, `abfss://`, `wasbs://` and `azureml://` URIs. \n",
+    "# === Note on path ===\n",
+    "# can be can be a local path or a cloud path. AzureML supports https://`, `abfss://`, `wasbs://` and `azureml://` URIs.\n",
     "# Local paths are automatically uploaded to the default datastore in the cloud.\n",
     "# More details on supported paths: https://docs.microsoft.com/azure/machine-learning/how-to-read-write-data-v2#supported-paths\n",
     "\n",
     "inputs = {\n",
-    "    \"input_data\": Input(\n",
-    "        type=AssetTypes.URI_FILE, \n",
-    "        path=\"./sample_data/titanic.csv\"\n",
-    "    )\n",
+    "    \"input_data\": Input(type=AssetTypes.URI_FILE, path=\"./sample_data/titanic.csv\")\n",
     "}\n",
     "\n",
     "job = command(\n",
@@ -118,16 +115,13 @@
     "from azure.ai.ml.constants import AssetTypes\n",
     "\n",
     "inputs = {\n",
-    "    \"input_data\": Input(\n",
-    "        type=AssetTypes.URI_FILE, \n",
-    "        path=\"./sample_data/titanic.csv\"\n",
-    "    )\n",
+    "    \"input_data\": Input(type=AssetTypes.URI_FILE, path=\"./sample_data/titanic.csv\")\n",
     "}\n",
     "\n",
     "outputs = {\n",
     "    \"output_folder\": Output(\n",
-    "        type=AssetTypes.URI_FOLDER, \n",
-    "        path=f\"azureml://subscriptions/{subscription_id}/resourcegroups/{resource_group}/workspaces/{workspace}/datastores/workspaceblobstore/paths/\"\n",
+    "        type=AssetTypes.URI_FOLDER,\n",
+    "        path=f\"azureml://subscriptions/{subscription_id}/resourcegroups/{resource_group}/workspaces/{workspace}/datastores/workspaceblobstore/paths/\",\n",
     "    )\n",
     "}\n",
     "\n",
@@ -205,10 +199,7 @@
     "registered_data_asset = ml_client.data.get(name=\"titanic\", version=\"1\")\n",
     "\n",
     "my_job_inputs = {\n",
-    "    \"input_data\": Input(\n",
-    "        type=AssetTypes.URI_FILE,\n",
-    "        path=registered_data_asset.id\n",
-    "    )\n",
+    "    \"input_data\": Input(type=AssetTypes.URI_FILE, path=registered_data_asset.id)\n",
     "}\n",
     "\n",
     "job = command(\n",
@@ -322,12 +313,7 @@
     "from azure.ai.ml import Input\n",
     "from azure.ai.ml.constants import AssetTypes\n",
     "\n",
-    "inputs = {\n",
-    "    \"input_data\": Input(\n",
-    "        type=AssetTypes.MLTABLE, \n",
-    "        path=\"./sample-mltable\"\n",
-    "    )\n",
-    "}\n",
+    "inputs = {\"input_data\": Input(type=AssetTypes.MLTABLE, path=\"./sample-mltable\")}\n",
     "\n",
     "job = command(\n",
     "    code=\"./src\",  # local path where the code is stored\n",

diff --git a/...nes/2d_image_classification_with_densenet/imagecnn_train/image_classification/training.py b/...nes/2d_image_classification_with_densenet/imagecnn_train/image_classification/training.py
@@ -257,7 +257,7 @@ def _lr_fn(iteration, epoch):
             lr = base_lr * (epoch + 1) / warmup_length
         else:
             e = epoch - warmup_length
-            lr = base_lr * (epoch_decay ** e)
+            lr = base_lr * (epoch_decay**e)
         return lr
 
     return lr_policy(_lr_fn, logger=logger)

diff --git a/sdk/setup.sh b/sdk/setup.sh
@@ -9,7 +9,7 @@ pip install mldesigner
 # </mldesigner_install>
 
 # <az_ml_sdk_test_install>
-# pip install azure-ai-ml==0.1.0.b4
+pip install azure-ai-ml==0.1.0.b5
 # </az_ml_sdk_test_install>
 
 pip list