| | ########################################### |
| | Use Version 2.x of the SageMaker Python SDK |
| | ########################################### |
| |
|
| | .. contents:: |
| | :local: |
| | :depth: 2 |
| |
|
| | ************ |
| | Installation |
| | ************ |
| |
|
| | To install the latest version: |
| |
|
| | .. code:: bash |
| |
|
| | pip install --upgrade sagemaker |
| |
|
| | If you are executing this pip install command in a notebook, make sure to restart your kernel. |
| |
|
| | **************** |
| | Breaking Changes |
| | **************** |
| |
|
| | This section is for major changes that may require updates to your SageMaker Python SDK code. |
| | For the full list of changes, see the `CHANGELOG <https://github.com/aws/sagemaker-python-sdk/blob/master/CHANGELOG.md>`_. |
| |
|
| | Removals |
| | ============ |
| |
|
| | Python 2 Support |
| | ---------------- |
| |
|
| | This library is no longer compatible with Python 2. |
| | Python 2 has been EOL since January 1, 2020. |
| | Please upgrade to Python 3 if you haven't already. |
| |
|
| | Remove Legacy TensorFlow |
| | --------------------------- |
| |
|
| | TensorFlow versions 1.4-1.10 and some variations of versions 1.11-1.12 |
| | (see `What Constitutes "Legacy TensorFlow Support" <frameworks/tensorflow/upgrade_from_legacy.html#what-constitutes-legacy-tensorflow-support>`_) |
| | are no longer natively supported by the SageMaker Python SDK. |
| |
|
| | To use those versions of TensorFlow, you must specify the Docker image URI explicitly, |
| | and configure settings via hyperparameters or environment variables rather than using SDK parameters. |
| | For more information, see `Upgrade from Legacy TensorFlow Support <frameworks/tensorflow/upgrade_from_legacy.html>`_. |
| |
|
| | SageMaker Python SDK CLI |
| | ------------------------ |
| |
|
| | The SageMaker Python SDK CLI has been removed. |
| | (This is different from the AWS CLI.) |
| |
|
| | ``delete_endpoint()`` for Estimators and ``HyperparameterTuner`` |
| | ---------------------------------------------------------------- |
| |
|
| | The ``delete_endpoint()`` method for estimators and ``HyperparameterTuner`` is now a no-op. |
| | Please use :func:`sagemaker.predictor.Predictor.delete_endpoint` instead. |
| |
|
| | ``update_endpoint`` in ``deploy()`` |
| | ----------------------------------- |
| |
|
| | The ``update_endpoint`` argument in ``deploy()`` methods for estimators and models is now a no-op. |
| | Please use :func:`sagemaker.predictor.Predictor.update_endpoint` instead. |
| |
|
| | ``serializer`` and ``deserializer`` in ``create_model()`` |
| | --------------------------------------------------------- |
| |
|
| | The ``serializer`` and ``deserializer`` arguments in |
| | :func:`sagemaker.estimator.Estimator.create_model` are now no-ops. |
| | Please specify serializers and deserializers in ``deploy()`` methods instead. |
| |
|
| | ``content_type`` and ``accept`` in the Predictor Constructor |
| | ------------------------------------------------------------ |
| |
|
| | The ``content_type`` and ``accept`` parameters are now no-ops in the |
| | following classes and methods: |
| |
|
| | - ``sagemaker.predictor.Predictor`` |
| | - ``sagemaker.estimator.Estimator.create_model`` |
| | - ``sagemaker.algorithms.AlgorithmEstimator.create_model`` |
| | - ``sagemaker.tensorflow.model.TensorFlowPredictor`` |
| |
|
| | Please specify content types in a serializer or deserializer class instead. |
| |
|
| | Changes in Default Behavior |
| | =========================== |
| |
|
| | Require ``framework_version`` and ``py_version`` for Frameworks |
| | --------------------------------------------------------------- |
| |
|
| | Framework estimator and model classes now require ``framework_version`` and ``py_version`` instead of supplying defaults, |
| | unless an image URI is explicitly supplied. |
| |
|
| | For example: |
| |
|
| | .. code:: python |
| |
|
| | from sagemaker.tensorflow import TensorFlow |
| |
|
| | TensorFlow( |
| | entry_point="script.py", |
| | framework_version="2.2.0", # now required |
| | py_version="py37", # now required |
| | role="my-role", |
| | instance_type="ml.m5.xlarge", |
| | instance_count=1, |
| | ) |
| |
|
| | from sagemaker.mxnet import MXNetModel |
| |
|
| | MXNetModel( |
| | model_data="s3://bucket/model.tar.gz", |
| | role="my-role", |
| | entry_point="inference.py", |
| | framework_version="1.6.0", # now required |
| | py_version="py3", # now required |
| | ) |
| |
|
| | Log Display Behavior with ``attach()`` |
| | -------------------------------------- |
| |
|
| | Logs are no longer printed when using ``attach()`` with an estimator. |
| | To view logs after attaching a training job to an estimator, use :func:`sagemaker.estimator.EstimatorBase.logs`. |
| |
|
| | ``HyperparameterTuner.fit()`` and ``Transformer.transform()`` |
| | ------------------------------------------------------------- |
| |
|
| | :func:`sagemaker.tuner.HyperparameterTuner.fit` and :func:`sagemaker.transformer.Transformer.transform` now wait |
| | until the completion of the Hyperparameter Tuning Job or Batch Transform Job, respectively. |
| | To make the function non-blocking, use ``wait=False``. |
| |
|
| | XGBoost Predictor |
| | ----------------- |
| |
|
| | The default serializer of ``sagemaker.xgboost.model.XGBoostPredictor`` has been changed from ``NumpySerializer`` to ``LibSVMSerializer``. |
| |
|
| |
|
| | Parameter Order Changes |
| | ======================= |
| |
|
| | ``sagemaker.model.Model`` Parameter Order |
| | ----------------------------------------- |
| |
|
| | The parameter order for :class:`sagemaker.model.Model` changed: instead of ``model_data`` being first, ``image_uri`` (formerly ``image``) is first. |
| | As a result, ``model_data`` has been made into an optional parameter. |
| |
|
| | If you are using the :class:`sagemaker.model.Model` class, your code should be changed as follows: |
| |
|
| | .. code:: python |
| |
|
| | # v1.x |
| | Model("s3://bucket/path/model.tar.gz", "my-image:latest") |
| |
|
| | # v2.0 and later |
| | Model("my-image:latest", model_data="s3://bucket/path/model.tar.gz") |
| |
|
| | Airflow Parameter Order |
| | ----------------------- |
| |
|
| | For :func:`sagemaker.workflow.airflow.model_config` and :func:`sagemaker.workflow.airflow.model_config_from_estimator`, |
| | ``instance_type`` is no longer the first positional argument and is now an optional keyword argument. |
| | |
| | Dependency Changes |
| | ================== |
| |
|
| | SciPy |
| | ----- |
| |
|
| | SciPy is no longer a required dependency of the SageMaker Python SDK. |
| |
|
| | If you use :func:`sagemaker.amazon.common.write_spmatrix_to_sparse_tensor` and |
| | don't already install SciPy in your environment, you can use our ``scipy`` installation target: |
| |
|
| | .. code:: bash |
| |
|
| | pip install sagemaker[scipy] |
| |
|
| | TensorFlow |
| | ---------- |
| |
|
| | The ``tensorflow`` installation target has been removed, as it is no longer needed for any SageMaker Python SDK functionality. |
| |
|
| | If you want to install TensorFlow, see `the TensorFlow documentation <https://www.tensorflow.org/install>`_. |
| |
|
| | ******************** |
| | Non-Breaking Changes |
| | ******************** |
| |
|
| | Deprecations |
| | ============ |
| |
|
| | Pre-instantiated Serializer and Deserializer Objects |
| | ---------------------------------------------------- |
| |
|
| | The ``csv_serializer``, ``json_serializer``, ``npy_serializer``, ``csv_deserializer``, |
| | ``json_deserializer``, and ``numpy_deserializer`` objects have been deprecated. |
| |
|
| | Please instantiate the objects instead. |
| |
|
| | +--------------------------------------------+------------------------------------------------+ |
| | | v1.x | v2.0 and later | |
| | +============================================+================================================+ |
| | | ``sagemaker.predictor.csv_serializer`` | ``sagemaker.serializers.CSVSerializer()`` | |
| | +--------------------------------------------+------------------------------------------------+ |
| | | ``sagemaker.predictor.json_serializer`` | ``sagemaker.serializers.JSONSerializer()`` | |
| | +--------------------------------------------+------------------------------------------------+ |
| | | ``sagemaker.predictor.npy_serializer`` | ``sagemaker.serializers.NumpySerializer()`` | |
| | +--------------------------------------------+------------------------------------------------+ |
| | | ``sagemaker.predictor.csv_deserializer`` | ``sagemaker.deserializers.CSVDeserializer()`` | |
| | +--------------------------------------------+------------------------------------------------+ |
| | | ``sagemaker.predictor.json_deserializer`` | ``sagemaker.deserializers.JSONDeserializer()`` | |
| | +--------------------------------------------+------------------------------------------------+ |
| | | ``sagemaker.predictor.numpy_deserializer`` | ``sagemaker.deserializers.NumpyDeserializer()``| |
| | +--------------------------------------------+------------------------------------------------+ |
| |
|
| | ``sagemaker.content_types`` |
| | --------------------------- |
| |
|
| | The ``sagemaker.content_types`` module is deprecated in v2.0 and later of the |
| | SageMaker Python SDK. |
| |
|
| | Instead of importing constants from ``sagemaker.content_types``, explicitly |
| | write MIME types as a string. |
| |
|
| | +-------------------------------+--------------------------------+ |
| | | v1.x | v2.0 and later | |
| | +===============================+================================+ |
| | | ``CONTENT_TYPE_JSON`` | ``"application/json"`` | |
| | +-------------------------------+--------------------------------+ |
| | | ``CONTENT_TYPE_CSV`` | ``"text/csv"`` | |
| | +-------------------------------+--------------------------------+ |
| | | ``CONTENT_TYPE_OCTET_STREAM`` | ``"application/octet-stream"`` | |
| | +-------------------------------+--------------------------------+ |
| | | ``CONTENT_TYPE_NPY`` | ``"application/x-npy"`` | |
| | +-------------------------------+--------------------------------+ |
| |
|
| | Image URI Functions (e.g. ``get_image_uri``) |
| | -------------------------------------------- |
| |
|
| | The following functions have been deprecated in favor of :func:`sagemaker.image_uris.retrieve`: |
| |
|
| | - ``sagemaker.amazon_estimator.get_image_uri()`` |
| | - ``sagemaker.fw_utils.create_image_uri()`` |
| | - ``sagemaker.fw_registry.registry()`` |
| | - ``sagemaker.utils.get_ecr_image_uri_prefix()`` |
| |
|
| | For more information about usage, see :func:`sagemaker.image_uris.retrieve`. |
| |
|
| | ``enable_cloudwatch_metrics`` for Estimators and Models |
| | ------------------------------------------------------- |
| |
|
| | The parameter ``enable_cloudwatch_metrics`` has been deprecated. |
| | CloudWatch metrics are already emitted for all Training Jobs, etc. |
| |
|
| | ``sagemaker.fw_utils.parse_s3_url`` |
| | ----------------------------------- |
| |
|
| | The ``sagemaker.fw_utils.parse_s3_url`` function has been deprecated. |
| | Please use :func:`sagemaker.s3.parse_s3_url` instead. |
| |
|
| | ``sagemaker.session.ModelContainer`` |
| | ------------------------------------ |
| |
|
| | The class ``sagemaker.session.ModelContainer`` has been deprecated, as it is not needed for creating inference pipelines. |
| |
|
| | ``sagemaker.workflow.condition_step.JsonGet`` |
| | --------------------------------------------- |
| |
|
| | The class ``sagemaker.workflow.condition_step.JsonGet`` has been deprecated. |
| | Please use :class:`sagemaker.workflow.functions.JsonGet` instead. |
| |
|
| | Parameter and Class Name Changes |
| | ================================ |
| |
|
| | Estimators |
| | ---------- |
| |
|
| | Renamed Estimator Parameters |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | The following estimator parameters have been renamed: |
| |
|
| | +------------------------------+------------------------+ |
| | | v1.x | v2.0 and later | |
| | +==============================+========================+ |
| | | ``train_instance_count`` | ``instance_count`` | |
| | +------------------------------+------------------------+ |
| | | ``train_instance_type`` | ``instance_type`` | |
| | +------------------------------+------------------------+ |
| | | ``train_max_run`` | ``max_run`` | |
| | +------------------------------+------------------------+ |
| | | ``train_use_spot_instances`` | ``use_spot_instances`` | |
| | +------------------------------+------------------------+ |
| | | ``train_max_wait`` | ``max_wait`` | |
| | +------------------------------+------------------------+ |
| | | ``train_volume_size`` | ``volume_size`` | |
| | +------------------------------+------------------------+ |
| | | ``train_volume_kms_key`` | ``volume_kms_key`` | |
| | +------------------------------+------------------------+ |
| |
|
| | Serializer and Deserializer Classes |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | The follow serializer/deserializer classes have been renamed and/or moved: |
| |
|
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | v1.x | v2.0 and later | |
| | +========================================================+=======================================================+ |
| | | ``sagemaker.predictor._CsvDeserializer`` | ``sagemaker.deserializers.CSVDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor._CsvSerializer`` | ``sagemaker.serializers.CSVSerializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor.BytesDeserializer`` | ``sagemaker.deserializers.BytesDeserializers`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor.StringDeserializer`` | ``sagemaker.deserializers.StringDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor.StreamDeserializer`` | ``sagemaker.deserializers.StreamDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor._JsonSerializer`` | ``sagemaker.serializers.JSONSerializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor._NumpyDeserializer`` | ``sagemaker.deserializers.NumpyDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor._NPYSerializer`` | ``sagemaker.serializers.NumpySerializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.amazon.common.numpy_to_record_serializer`` | ``sagemaker.amazon.common.RecordSerializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.amazon.common.record_deserializer`` | ``sagemaker.amazon.common.RecordDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| | | ``sagemaker.predictor._JsonDeserializer`` | ``sagemaker.deserializers.JSONDeserializer`` | |
| | +--------------------------------------------------------+-------------------------------------------------------+ |
| |
|
| | ``sagemaker.serializers.LibSVMSerializer`` has been added in v2.0. |
| |
|
| | ``distributions`` |
| | ~~~~~~~~~~~~~~~~~ |
| |
|
| | For TensorFlow and MXNet estimators, ``distributions`` has been renamed to ``distribution``. |
| |
|
| | Specify Custom Training Images |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | The ``image_name`` parameter has been renamed to ``image_uri`` for specifying a custom Docker image URI to use with training. |
| |
|
| |
|
| | Models |
| | ------ |
| |
|
| | Specify Custom Serving Image |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | The ``image`` parameter has been renamed to ``image_uri`` for specifying a custom Docker image URI to use with inference. |
| |
|
| | TensorFlow Serving Model |
| | ~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | ``sagemaker.tensorflow.serving.Model`` has been renamed to :class:`sagemaker.tensorflow.model.TensorFlowModel`. |
| | (For the previous implementation of that class, see `Remove Legacy TensorFlow <#remove-legacy-tensorflow>`_). |
| |
|
| | Predictors |
| | ---------- |
| |
|
| | Generic Predictor Class Name |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | ``sagemaker.predictor.RealTimePredictor`` has been renamed to :class:`sagemaker.predictor.Predictor`. |
| |
|
| | Endpoint Argument Name |
| | ~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | For :class:`sagemaker.predictor.Predictor`, :class:`sagemaker.sparkml.model.SparkMLPredictor`, |
| | and predictors for Amazon algorithm (e.g. Factorization Machines, Linear Learner, etc.), |
| | the ``endpoint`` attribute has been renamed to ``endpoint_name``. |
| |
|
| | TensorFlow Serving Predictor |
| | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ |
| |
|
| | ``sagemaker.tensorflow.serving.Predictor`` has been renamed to :class:`sagemaker.tensorflow.model.TensorFlowPredictor`. |
| | (For the previous implementation of that class, see `Remove Legacy TensorFlow <#remove-legacy-tensorflow>`_). |
| |
|
| |
|
| | Inputs |
| | ------ |
| |
|
| | ``s3_input`` |
| | ~~~~~~~~~~~~ |
| |
|
| | ``sagemaker.session.s3_input`` has been renamed to :class:`sagemaker.inputs.TrainingInput`. |
| |
|
| | ``ShuffleConfig`` |
| | ~~~~~~~~~~~~~~~~~ |
| |
|
| | ``sagemaker.session.ShuffleConfig`` has been renamed to :class:`sagemaker.inputs.ShuffleConfig`. |
| |
|
| | Airflow |
| | ------- |
| |
|
| | For :func:`sagemaker.workflow.airflow.model_config`, :func:`sagemaker.workflow.airflow.model_config_from_estimator`, and |
| | :func:`sagemaker.workflow.airflow.transform_config_from_estimator`, the ``image`` argument has been renamed to ``image_uri``. |
| | |
| | ******************************* |
| | Automatically Upgrade Your Code |
| | ******************************* |
| |
|
| | To help make your transition as seamless as possible, v2 of the SageMaker Python SDK comes with a command-line tool to automate updating your code. |
| | It automates as much as possible, but there are still syntactical and stylistic changes that cannot be performed by the script. |
| |
|
| | .. warning:: |
| | While the tool is intended to be easy to use, we recommend using it as part of a process that includes testing before and after you run the tool. |
| |
|
| | Usage |
| | ===== |
| |
|
| | Currently, the tool supports only converting one file at a time: |
| |
|
| | .. code:: |
| |
|
| | $ sagemaker-upgrade-v2 --in-file input.py --out-file output.py |
| | $ sagemaker-upgrade-v2 --in-file input.ipynb --out-file output.ipynb |
| |
|
| | You can apply it to a set of files using a loop: |
| |
|
| | .. code:: bash |
| |
|
| | $ for file in $(find input-dir); do sagemaker-upgrade-v2 --in-file $file --out-file output-dir/$file; done |
| |
|
| | Limitations |
| | =========== |
| |
|
| | Jupyter Notebook Cells with Shell Commands |
| | ------------------------------------------ |
| |
|
| | If your Jupyter notebook has a code cell with lines that start with either ``%%`` or ``!``, the tool ignores that cell. |
| | The other cells in the notebook are still updated. |
| |
|
| | Aliased Imports |
| | --------------- |
| |
|
| | The tool checks for a limited number of patterns when looking for constructors. |
| | For example, if you are using a TensorFlow estimator, only the following invocation styles are handled: |
| |
|
| | .. code:: python |
| |
|
| | TensorFlow() |
| | sagemaker.tensorflow.TensorFlow() |
| | sagemaker.tensorflow.estimator.TensorFlow() |
| |
|
| | If you have aliased an import, e.g. ``from sagemaker.tensorflow import TensorFlow as TF``, the tool does not take care of updating its parameters. |
| |
|
| | TensorFlow Serving |
| | ------------------ |
| |
|
| | If you are using the ``sagemaker.tensorflow.serving.Model`` class, the tool does not take care of adding a framework version or changing it to ``sagemaker.tensorflow.TensorFlowModel``. |
| |
|
| | ``sagemaker.model.Model`` |
| | ------------------------- |
| |
|
| | If you are using the :class:`sagemaker.model.Model` class, the tool does not take care of switching the order between ``model_data`` and ``image_uri`` (formerly ``image``). |
| |
|
| | ``update_endpoint`` and ``delete_endpoint`` |
| | ------------------------------------------- |
| |
|
| | The tool does not take care of removing the ``update_endpoint`` argument from a ``deploy`` call. |
| | If you are using that argument, please modify your code to use :func:`sagemaker.predictor.Predictor.update_endpoint` instead. |
| |
|
| | The tool also does not handle ``delete_endpoint`` calls on estimators or ``HyperparameterTuner``. |
| | If you are using that method, please modify your code to use :func:`sagemaker.predictor.Predictor.delete_endpoint` instead. |
| |
|
