Metadata-Version: 2.1
Name: sagemaker-experiments
Version: 0.1.7
Summary: Open source library for Experiment Tracking in SageMaker Jobs and Notebooks
Home-page: https://github.com/aws/sagemaker-experiment-tracking/
Author: Amazon Web Services
License: Apache License 2.0
Keywords: ML Amazon AWS AI Tensorflow MXNet
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/x-rst
Requires-Dist: boto3 (>=1.10.32)
Provides-Extra: test
Requires-Dist: tox (==3.13.1) ; extra == 'test'
Requires-Dist: flake8 ; extra == 'test'
Requires-Dist: pytest (==4.4.1) ; extra == 'test'
Requires-Dist: pytest-cov ; extra == 'test'
Requires-Dist: pytest-coverage ; extra == 'test'
Requires-Dist: pytest-rerunfailures ; extra == 'test'
Requires-Dist: pytest-xdist ; extra == 'test'
Requires-Dist: docker ; extra == 'test'

.. image:: https://github.com/aws/sagemaker-experiments/raw/master/branding/icon/sagemaker-banner.png
    :height: 100px
    :alt: SageMaker
    :target: https://aws.amazon.com/sagemaker/

================================
SageMaker Experiments Python SDK
================================

.. image:: https://img.shields.io/pypi/v/sagemaker-experiments.svg
    :target: https://pypi.python.org/pypi/sagemaker-experiments
    :alt: Latest Version

.. image:: https://img.shields.io/pypi/pyversions/sagemaker-experiments.svg
    :target: https://pypi.python.org/pypi/sagemaker-experiments
    :alt: Supported Python Versions

.. image:: https://img.shields.io/pypi/l/sagemaker-experiments
    :target: https://github.com/aws/sagemaker-experiments/blob/master/LICENSE
    :alt: License

.. image:: https://img.shields.io/pypi/dm/sagemaker-experiments
    :target: https://pypi.python.org/pypi/sagemaker-experiments
    :alt: PyPI - Downloads

.. image:: https://codecov.io/gh/aws/sagemaker-experiments/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/aws/sagemaker-experiments
   :alt: CodeCov

.. image:: https://img.shields.io/pypi/status/sagemaker-experiments
    :target: https://github.com/aws/sagemaker-experiments
    :alt: PyPI - Status

.. image:: https://img.shields.io/pypi/format/coverage.svg
    :target: https://pypi.org/project/coverage/
    :alt: Kit format

.. image:: https://img.shields.io/github/workflow/status/aws/sagemaker-experiments/Main
    :target: https://github.com/aws/sagemaker-experiments/actions
    :alt: GitHub Workflow Status

.. image:: https://img.shields.io/github/stars/aws/sagemaker-experiments.svg?logo=github
    :target: https://github.com/aws/sagemaker-experiments/stargazers
    :alt: Github stars

.. image:: https://img.shields.io/github/forks/aws/sagemaker-experiments.svg?logo=github
    :target: https://github.com/aws/sagemaker-experiments/network/members
    :alt: Github forks

.. image:: https://img.shields.io/github/contributors/aws/sagemaker-experiments.svg?logo=github
    :target: https://github.com/aws/sagemaker-experiments/graphs/contributors
    :alt: Contributors

.. image:: https://img.shields.io/github/search/aws/sagemaker-experiments/sagemaker
    :target: https://github.com/aws/sagemaker-experiments
    :alt: GitHub search hit counter

.. image:: https://img.shields.io/badge/code_style-black-000000.svg
    :target: https://github.com/python/black
    :alt: Code style: black

.. image:: https://readthedocs.org/projects/sagemaker-experiments/badge/?version=latest
    :target: https://readthedocs.org/projects/sagemaker-experiments/
    :alt: Read the Docs - Sagemaker Experiments

.. image:: https://mybinder.org/badge_logo.svg
    :target: https://mybinder.org/v2/gh/awslabs/amazon-sagemaker-examples/master?filepath=sagemaker-experiments%2Fmnist-handwritten-digits-classification-experiment.ipynb



Experiment tracking in SageMaker Training Jobs, Processing Jobs, and Notebooks.

Overview
--------
SageMaker Experiments is an AWS service for tracking machine learning Experiments. The SageMaker Experiments Python SDK is a high-level interface to this service that helps you track Experiment information using Python.

Experiment tracking powers the machine learning integrated development environment `Amazon SageMaker Studio <https://docs.aws.amazon.com/sagemaker/latest/dg/gs-studio.html>`_.

For detailed API reference please go to: `Read the Docs <https://sagemaker-experiments.readthedocs.io>`_

Concepts
--------

- **Experiment**: A collection of related Trials. Add Trials to an Experiment that you wish to compare together.
- **Trial**: A description of a multi-step machine learning workflow. Each step in the workflow is described by a Trial Component. There is no relationship between Trial Components such as ordering.
- **Trial Component**: A description of a single step in a machine learning workflow.  For example data cleaning, feature extraction, model training, model evaluation, etc...
- **Tracker**: A Python context-manager for logging information about a single TrialComponent.

For more information see `Amazon SageMaker Experiments - Organize, Track, and Compare Your Machine Learning Trainings <https://aws.amazon.com/blogs/aws/amazon-sagemaker-experiments-organize-track-and-compare-your-machine-learning-trainings/>`_

Using the SDK
-------------
You can use this SDK to:

- Manage Experiments, Trials, and Trial Components within Python scripts, programs, and notebooks.
- Add tracking information to a SageMaker notebook, allowing you to model your notebook in SageMaker Experiments as a multi-step ML workflow.
- Record experiment information from inside your running SageMaker Training and Processing Jobs.

Installation
------------

.. code-block:: bash

    pip install sagemaker-experiments

Examples
--------
See: `sagemaker-experiments <https://github.com/awslabs/amazon-sagemaker-examples/tree/master/sagemaker-experiments>`_ in `AWS Labs Amazon SageMaker Examples <https://github.com/awslabs/amazon-sagemaker-examples>`_.

License
-------
This library is licensed under the Apache 2.0 License.

Running Tests
-------------

**Unit Tests**

.. code-block:: bash

    tox tests/unit

**Integration Tests**

To run the integration tests, the following prerequisites must be met:

- AWS account credentials are available in the environment for the boto3 client to use.
- The AWS account has an IAM role with SageMaker permissions.

.. code-block:: bash

    tox tests/integ

