Upgrade azure-cli and azureml-sdk. Remove workarounds got feedback 20566

07_Train_With_AML_Pipeline.ipynb

@@ -292,7 +292,7 @@
    "metadata": {},
    "source": [
     "## Create AML Pipeline Tuning Step <a id='aml_pipeline_tune_step'></a>\n",
-    "We create a HyperDrive step in the AML pipeline to perform a search for hyperparameters. The `tune_estimators` pipeline parameter that controls the number of estimators used in tuning deliberately has a low default value for the speed of pipeline testing. The `tune_steps_data` output pipeline data is only used to synchronize with the next pipeline step."
+    "We create a HyperDrive step in the AML pipeline to perform a search for hyperparameters. The `tune_estimators` pipeline parameter that controls the number of estimators used in tuning deliberately has a low default value for the speed of pipeline testing."
    ]
   },
   {
@@ -302,7 +302,6 @@
    "outputs": [],
    "source": [
     "tune_step_name=\"tune_model\"\n",
-    "tune_steps_data = PipelineData(\"tune_steps_data\", datastore=ds)\n",
     "tune_estimators = PipelineParameter(name=\"tune_estimators\", default_value=1)  # Set to 1000 when running the pipeline.\n",
     "tune_step = HyperDriveStep(\n",
     "    name=tune_step_name,\n",
@@ -310,7 +309,6 @@
     "    estimator_entry_script_arguments=[\"--data-folder\", data_folder,\n",
     "                                      \"--estimators\", tune_estimators],\n",
     "    inputs=[data_folder],\n",
-    "    outputs=[tune_steps_data],\n",
     "    allow_reuse=False)"
    ]
   },
@@ -404,7 +402,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Creating PythonScript Step for AML pipeline to get the best run's hyperparameters. The `tune_steps_data` input pipeline data is only used to synchronize with the previous pipeline step."
+    "Creating PythonScript Step for AML pipeline to get the best run's hyperparameters."
    ]
   },
   {
@@ -428,10 +426,10 @@
     "    arguments=[\"--hd-step\", tune_step_name,\n",
     "               \"--output-steps-data\", bh_steps_data,\n",
     "               \"--hyperparameters\", bh_hyperparameters_file],\n",
-    "    inputs=[tune_steps_data],\n",
     "    outputs=[bh_steps_data],\n",
     "    runconfig=bh_run_config,\n",
-    "    allow_reuse=False)"
+    "    allow_reuse=False)\n",
+    "bh_step.run_after(tune_step)"
    ]
   },
   {
@@ -439,7 +437,7 @@
    "metadata": {},
    "source": [
     "## Create AML Pipeline Best Model Step <a id='aml_pipeline_estimator_step'></a>\n",
-    "This step passes the hyperparameters file from the previous step to the training script to create the best model. The `best_estimators` pipeline parameter that controls the number of estimators used in getting the best model deliberately has a low default value for the speed of pipeline testing. The `bm_steps_data` output pipeline data is only used to synchronize with the next pipeline step."
+    "This step passes the hyperparameters file from the previous step to the training script to create the best model. The `best_estimators` pipeline parameter that controls the number of estimators used in getting the best model deliberately has a low default value for the speed of pipeline testing."
    ]
   },
   {
@@ -449,7 +447,6 @@
    "outputs": [],
    "source": [
     "bm_step_name=\"best_model\"\n",
-    "bm_steps_data = PipelineData(\"bm_steps_data\", datastore=ds)\n",
     "bm_estimators = PipelineParameter(name=\"best_estimators\", default_value=1)  # Set to 8000 when running the pipeline\n",
     "bm_estimator = Estimator(source_directory=os.path.join('.', 'scripts'),  # Use a new Estimator as a bug workaround\n",
     "                         entry_script='TrainClassifier.py',\n",
@@ -467,7 +464,6 @@
     "                                      \"--save\", model_name],\n",
     "    compute_target=compute_target,\n",
     "    inputs=[data_folder, bh_steps_data],\n",
-    "    outputs=[bm_steps_data],\n",
     "    allow_reuse=False)"
    ]
   },
@@ -532,7 +528,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Creating PythonScript Step for AML pipeline to register the best model. The `bm_steps_data` input pipeline data is only used to synchronize with the previous pipeline step."
+    "Creating PythonScript Step for AML pipeline to register the best model."
    ]
   },
   {
@@ -554,9 +550,9 @@
     "    arguments=[\"--es-step\", bm_step_name,\n",
     "               \"--outputs\", \"outputs\",\n",
     "               \"--model-name\", model_name],\n",
-    "    inputs=[bm_steps_data],\n",
     "    runconfig=rm_run_config,\n",
-    "    allow_reuse=False)"
+    "    allow_reuse=False)\n",
+    "rm_step.run_after(bm_step)"
    ]
   },
   {
@@ -671,7 +667,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.6.7"
   }
  },
  "nbformat": 4,

environment.yml

@@ -11,5 +11,5 @@ dependencies:
   - lightgbm==2.2.1
   - pip:
     - prompt_toolkit==2.0.9
-    - azure-cli==2.0.75
-    - azureml-sdk[notebooks]==1.0.69
+    - azure-cli==2.0.77
+    - azureml-sdk[notebooks]==1.0.76