From 6f893ff0b40d3d6af94ac43867676a3d9df1fcbd Mon Sep 17 00:00:00 2001 From: nikAI77 <70364961+nikAI77@users.noreply.github.com> Date: Tue, 6 Apr 2021 22:06:12 +0530 Subject: [PATCH] update samples from Release-94 as a part of SDK release (#1418) Co-authored-by: amlrelsa-ms --- configuration.ipynb | 2 +- .../automated-machine-learning/automl_env.yml | 4 +- .../automl_env_linux.yml | 4 +- .../automl_env_mac.yml | 4 +- ...fication-bank-marketing-all-features.ipynb | 2 +- ...-ml-classification-credit-card-fraud.ipynb | 2 +- .../auto-ml-classification-text-dnn.ipynb | 2 +- .../auto-ml-continuous-retraining.ipynb | 2 +- .../auto-ml-regression-model-proxy.ipynb | 2 +- .../auto-ml-forecasting-beer-remote.ipynb | 2 +- .../auto-ml-forecasting-bike-share.ipynb | 2 +- .../auto-ml-forecasting-energy-demand.ipynb | 2 +- .../auto-ml-forecasting-function.ipynb | 2 +- ...to-ml-forecasting-orange-juice-sales.ipynb | 2 +- ...assification-credit-card-fraud-local.ipynb | 2 +- ...regression-explanation-featurization.ipynb | 2 +- .../regression/auto-ml-regression.ipynb | 2 +- .../explain-model-on-amlcompute.ipynb | 3 - ...ain-explain-model-locally-and-deploy.ipynb | 7 +- ...plain-model-on-amlcompute-and-deploy.ipynb | 10 ++- ...nes-parameter-tuning-with-hyperdrive.ipynb | 81 ++++++++++--------- ...erparameter-tune-deploy-with-chainer.ipynb | 19 ++--- .../logging-api/logging-api.ipynb | 2 +- setup-environment/configuration.ipynb | 2 +- tutorials/quickstart/score.py | 51 ++++++++++++ 25 files changed, 134 insertions(+), 81 deletions(-) create mode 100644 tutorials/quickstart/score.py diff --git a/configuration.ipynb b/configuration.ipynb index 75343747..e2cefa2a 100644 --- a/configuration.ipynb +++ b/configuration.ipynb @@ -103,7 +103,7 @@ "source": [ "import azureml.core\n", "\n", - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/automl_env.yml b/how-to-use-azureml/automated-machine-learning/automl_env.yml index e34d3ff5..7e62803a 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env.yml @@ -21,8 +21,8 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.25.0 + - azureml-widgets~=1.26.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.25.0/validated_win32_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.26.0/validated_win32_requirements.txt [--no-deps] diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml index 7c646316..d4f3c553 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env_linux.yml @@ -21,8 +21,8 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.25.0 + - azureml-widgets~=1.26.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.25.0/validated_linux_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.26.0/validated_linux_requirements.txt [--no-deps] diff --git a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml index eb0d2589..9d277028 100644 --- a/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml +++ b/how-to-use-azureml/automated-machine-learning/automl_env_mac.yml @@ -22,8 +22,8 @@ dependencies: - pip: # Required packages for AzureML execution, history, and data preparation. - - azureml-widgets~=1.25.0 + - azureml-widgets~=1.26.0 - pytorch-transformers==1.0.0 - spacy==2.1.8 - https://aka.ms/automl-resources/packages/en_core_web_sm-2.1.0.tar.gz - - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.25.0/validated_darwin_requirements.txt [--no-deps] + - -r https://automlcesdkdataresources.blob.core.windows.net/validated-requirements/1.26.0/validated_darwin_requirements.txt [--no-deps] diff --git a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb index 56885e2e..870352c0 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-bank-marketing-all-features/auto-ml-classification-bank-marketing-all-features.ipynb @@ -105,7 +105,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb index b1d21d1a..03701b12 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-credit-card-fraud/auto-ml-classification-credit-card-fraud.ipynb @@ -93,7 +93,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb index 55874589..ed7c222e 100644 --- a/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb +++ b/how-to-use-azureml/automated-machine-learning/classification-text-dnn/auto-ml-classification-text-dnn.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb index 99c5cd03..c6ca4a5c 100644 --- a/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb +++ b/how-to-use-azureml/automated-machine-learning/continuous-retraining/auto-ml-continuous-retraining.ipynb @@ -81,7 +81,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb index fb0b07a1..efc2674b 100644 --- a/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb +++ b/how-to-use-azureml/automated-machine-learning/experimental/regression-model-proxy/auto-ml-regression-model-proxy.ipynb @@ -91,7 +91,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb index 3e7f2122..38514b45 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-beer-remote/auto-ml-forecasting-beer-remote.ipynb @@ -113,7 +113,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb index afe9a218..a1a42d90 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-bike-share/auto-ml-forecasting-bike-share.ipynb @@ -87,7 +87,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb index e2861e0c..b78e6e4f 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-energy-demand/auto-ml-forecasting-energy-demand.ipynb @@ -97,7 +97,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb index 0650086e..6942f0c5 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-forecast-function/auto-ml-forecasting-function.ipynb @@ -94,7 +94,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb index 47657e92..1b9f31ec 100644 --- a/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb +++ b/how-to-use-azureml/automated-machine-learning/forecasting-orange-juice-sales/auto-ml-forecasting-orange-juice-sales.ipynb @@ -82,7 +82,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb index bd3a59e3..0f18e264 100644 --- a/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb +++ b/how-to-use-azureml/automated-machine-learning/local-run-classification-credit-card-fraud/auto-ml-classification-credit-card-fraud-local.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb index 8151a237..fea9e2f9 100644 --- a/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb +++ b/how-to-use-azureml/automated-machine-learning/regression-explanation-featurization/auto-ml-regression-explanation-featurization.ipynb @@ -96,7 +96,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb index 86bd4c2e..9ee62c9b 100644 --- a/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb +++ b/how-to-use-azureml/automated-machine-learning/regression/auto-ml-regression.ipynb @@ -92,7 +92,7 @@ "metadata": {}, "outputs": [], "source": [ - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb index 2b323fda..8fbf089a 100644 --- a/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/remote-explanation/explain-model-on-amlcompute.ipynb @@ -255,9 +255,6 @@ "# Set compute target to AmlCompute target created in previous step\n", "run_config.target = cpu_cluster.name\n", "\n", - "# Enable Docker \n", - "run_config.environment.docker.enabled = True\n", - "\n", "azureml_pip_packages = [\n", " 'azureml-defaults', 'azureml-telemetry', 'azureml-interpret'\n", "]\n", diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb index e34c9a38..e78e4a87 100644 --- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-locally-and-deploy.ipynb @@ -401,7 +401,12 @@ "\n", "# Use configs and models generated above\n", "service = Model.deploy(ws, 'model-scoring-deploy-local', [scoring_explainer_model, original_model], inference_config, aciconfig)\n", - "service.wait_for_deployment(show_output=True)" + "try:\n", + " service.wait_for_deployment(show_output=True)\n", + "except WebserviceException as e:\n", + " print(e.message)\n", + " print(service.get_logs())\n", + " raise" ] }, { diff --git a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb index 606d013c..0881ebf9 100644 --- a/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb +++ b/how-to-use-azureml/explain-model/azure-integration/scoring-time/train-explain-model-on-amlcompute-and-deploy.ipynb @@ -257,9 +257,6 @@ "# Set compute target to AmlCompute target created in previous step\n", "run_config.target = cpu_cluster.name\n", "\n", - "# Enable Docker \n", - "run_config.environment.docker.enabled = True\n", - "\n", "# Set Docker base image to the default CPU-based image\n", "run_config.environment.docker.base_image = DEFAULT_CPU_IMAGE\n", "\n", @@ -502,7 +499,12 @@ "\n", "# Use configs and models generated above\n", "service = Model.deploy(ws, 'model-scoring-service', [scoring_explainer_model, original_model], inference_config, aciconfig)\n", - "service.wait_for_deployment(show_output=True)" + "try:\n", + " service.wait_for_deployment(show_output=True)\n", + "except WebserviceException as e:\n", + " print(e.message)\n", + " print(service.get_logs())\n", + " raise" ] }, { diff --git a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-parameter-tuning-with-hyperdrive.ipynb b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-parameter-tuning-with-hyperdrive.ipynb index ab1c2ee2..0832d71f 100644 --- a/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-parameter-tuning-with-hyperdrive.ipynb +++ b/how-to-use-azureml/machine-learning-pipelines/intro-to-pipelines/aml-pipelines-parameter-tuning-with-hyperdrive.ipynb @@ -42,15 +42,13 @@ "outputs": [], "source": [ "import azureml.core\n", - "from azureml.core import Workspace, Experiment, Datastore, Dataset\n", + "from azureml.core import Workspace, Environment, Experiment, Datastore, Dataset, ScriptRunConfig\n", "from azureml.core.compute import ComputeTarget, AmlCompute\n", "from azureml.core.conda_dependencies import CondaDependencies\n", "from azureml.core.runconfig import RunConfiguration\n", "from azureml.exceptions import ComputeTargetException\n", "from azureml.pipeline.steps import HyperDriveStep, HyperDriveStepRun, PythonScriptStep\n", "from azureml.pipeline.core import Pipeline, PipelineData, TrainingOutput\n", - "from azureml.train.dnn import TensorFlow\n", - "# from azureml.train.hyperdrive import *\n", "from azureml.train.hyperdrive import RandomParameterSampling, BanditPolicy, HyperDriveConfig, PrimaryMetricGoal\n", "from azureml.train.hyperdrive import choice, loguniform\n", "\n", @@ -282,13 +280,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Create TensorFlow estimator\n", - "Next, we construct an [TensorFlow](https://docs.microsoft.com/python/api/azureml-train-core/azureml.train.dnn.tensorflow?view=azure-ml-py) estimator object.\n", - "The TensorFlow estimator is providing a simple way of launching a TensorFlow training job on a compute target. It will automatically provide a docker image that has TensorFlow installed -- if additional pip or conda packages are required, their names can be passed in via the `pip_packages` and `conda_packages` arguments and they will be included in the resulting docker.\n", - "\n", - "The TensorFlow estimator also takes a `framework_version` parameter -- if no version is provided, the estimator will default to the latest version supported by AzureML. Use `TensorFlow.get_supported_versions()` to get a list of all versions supported by your current SDK version or see the [SDK documentation](https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.dnn?view=azure-ml-py) for the versions supported in the most current release.\n", - "\n", - "The TensorFlow estimator also takes a `framework_version` parameter -- if no version is provided, the estimator will default to the latest version supported by AzureML. Use `TensorFlow.get_supported_versions()` to get a list of all versions supported by your current SDK version or see the [SDK documentation](https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.dnn?view=azure-ml-py) for the versions supported in the most current release." + "## Retrieve an Environment\n", + "In this tutorial, we will use one of Azure ML's curated TensorFlow environments for training. Curated environments are available in your workspace by default. Specifically, we will use the TensorFlow 2.0 GPU curated environment." ] }, { @@ -297,12 +290,45 @@ "metadata": {}, "outputs": [], "source": [ - "est = TensorFlow(source_directory=script_folder, \n", - " compute_target=compute_target,\n", - " entry_script='tf_mnist.py', \n", - " use_gpu=True,\n", - " framework_version='2.0',\n", - " pip_packages=['azureml-dataset-runtime[pandas,fuse]'])" + "tf_env = Environment.get(ws, name='AzureML-TensorFlow-2.0-GPU')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Setup an input for the ScriptRunConfig step\n", + "You can mount dataset to remote compute." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data_folder = dataset.as_mount()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Configure the training job\n", + "Create a ScriptRunConfig object to specify the configuration details of your training job, including your training script, environment to use, and the compute target to run on" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "src = ScriptRunConfig(source_directory=script_folder,\n", + " script='tf_mnist.py',\n", + " arguments=['--data-folder', data_folder],\n", + " compute_target=compute_target,\n", + " environment=tf_env)" ] }, { @@ -366,7 +392,7 @@ }, "outputs": [], "source": [ - "hd_config = HyperDriveConfig(estimator=est, \n", + "hd_config = HyperDriveConfig(run_config=src, \n", " hyperparameter_sampling=ps,\n", " policy=early_termination_policy,\n", " primary_metric_name='validation_acc', \n", @@ -375,25 +401,6 @@ " max_concurrent_runs=4)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Add HyperDrive as a step of pipeline\n", - "\n", - "### Setup an input for the hypderdrive step\n", - "You can mount dataset to remote compute." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "data_folder = dataset.as_mount()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -402,7 +409,6 @@ "HyperDriveStep can be used to run HyperDrive job as a step in pipeline.\n", "- **name:** Name of the step\n", "- **hyperdrive_config:** A HyperDriveConfig that defines the configuration for this HyperDrive run\n", - "- **estimator_entry_script_arguments:** List of command-line arguments for estimator entry script\n", "- **inputs:** List of input port bindings\n", "- **outputs:** List of output port bindings\n", "- **metrics_output:** Optional value specifying the location to store HyperDrive run metrics as a JSON file\n", @@ -437,7 +443,6 @@ "hd_step = HyperDriveStep(\n", " name=hd_step_name,\n", " hyperdrive_config=hd_config,\n", - " estimator_entry_script_arguments=['--data-folder', data_folder],\n", " inputs=[data_folder],\n", " outputs=[metrics_data, saved_model])" ] diff --git a/how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb b/how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb index 7975c9af..905c2c75 100644 --- a/how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb +++ b/how-to-use-azureml/ml-frameworks/chainer/train-hyperparameter-tune-deploy-with-chainer/train-hyperparameter-tune-deploy-with-chainer.ipynb @@ -45,16 +45,6 @@ "print(\"SDK version:\", azureml.core.VERSION)" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "!jupyter nbextension install --py --user azureml.widgets\n", - "!jupyter nbextension enable --py --user azureml.widgets" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -278,12 +268,14 @@ "outputs": [], "source": [ "from azureml.core import Environment\n", + "from azureml.core.runconfig import DockerConfiguration\n", "\n", "chainer_env = Environment.from_conda_specification(name = 'chainer-5.1.0-gpu', file_path = './conda_dependencies.yml')\n", "\n", "# Specify a GPU base image\n", - "chainer_env.docker.enabled = True\n", - "chainer_env.docker.base_image = 'mcr.microsoft.com/azureml/intelmpi2018.3-cuda9.0-cudnn7-ubuntu16.04'" + "chainer_env.docker.base_image = 'mcr.microsoft.com/azureml/intelmpi2018.3-cuda9.0-cudnn7-ubuntu16.04'\n", + "\n", + "docker_config = DockerConfiguration(use_docker=True)" ] }, { @@ -307,7 +299,8 @@ " script='chainer_mnist.py',\n", " arguments=['--epochs', 10, '--batchsize', 128, '--output_dir', './outputs'],\n", " compute_target=compute_target,\n", - " environment=chainer_env)" + " environment=chainer_env,\n", + " docker_runtime_config=docker_config)" ] }, { diff --git a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb index ce0d1402..3d9f93c7 100644 --- a/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb +++ b/how-to-use-azureml/track-and-monitor-experiments/logging-api/logging-api.ipynb @@ -100,7 +100,7 @@ "\n", "# Check core SDK version number\n", "\n", - "print(\"This notebook was created using SDK version 1.25.0, you are currently running version\", azureml.core.VERSION)" + "print(\"This notebook was created using SDK version 1.26.0, you are currently running version\", azureml.core.VERSION)" ] }, { diff --git a/setup-environment/configuration.ipynb b/setup-environment/configuration.ipynb index 80691cf1..90adaed4 100644 --- a/setup-environment/configuration.ipynb +++ b/setup-environment/configuration.ipynb @@ -102,7 +102,7 @@ "source": [ "import azureml.core\n", "\n", - "print(\"This notebook was created using version 1.25.0 of the Azure ML SDK\")\n", + "print(\"This notebook was created using version 1.26.0 of the Azure ML SDK\")\n", "print(\"You are currently using version\", azureml.core.VERSION, \"of the Azure ML SDK\")" ] }, diff --git a/tutorials/quickstart/score.py b/tutorials/quickstart/score.py new file mode 100644 index 00000000..a3e7f706 --- /dev/null +++ b/tutorials/quickstart/score.py @@ -0,0 +1,51 @@ +import os +import torch +import json +import torch.nn as nn +import torch.nn.functional as F + + +class Net(nn.Module): + def __init__(self): + super(Net, self).__init__() + self.conv1 = nn.Conv2d(3, 6, 5) + self.pool = nn.MaxPool2d(2, 2) + self.conv2 = nn.Conv2d(6, 16, 5) + self.fc1 = nn.Linear(16 * 5 * 5, 120) + self.fc2 = nn.Linear(120, 84) + self.fc3 = nn.Linear(84, 10) + + def forward(self, x): + x = self.pool(F.relu(self.conv1(x))) + x = self.pool(F.relu(self.conv2(x))) + x = x.view(-1, 16 * 5 * 5) + x = F.relu(self.fc1(x)) + x = F.relu(self.fc2(x)) + x = self.fc3(x) + return x + + +def init(): + global net + global classes + + model_filename = 'cifar_net.pth' + model_path = os.path.join(os.environ['AZUREML_MODEL_DIR'], model_filename) + net = Net() + net.load_state_dict(torch.load(model_path)) + classes = ('plane', 'car', 'bird', 'cat', + 'deer', 'dog', 'frog', 'horse', 'ship', 'truck') + + +def run(data): + data = json.loads(data) + images = torch.FloatTensor(data['data']) + outputs = net(images) + + _, predicted = torch.max(outputs, 1) + + result = [classes[predicted[j]] for j in range(4)] + result_json = json.dumps({"predictions": result}) + + # You can return any JSON-serializable object. + return result_json