| ########################################### |
| 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. |
|
|
