A library for maintaining metadata for artifacts.
Project description
ML Metadata
ML Metadata (MLMD) is a library for recording and retrieving metadata associated with ML developer and data scientist workflows.
Caution: ML Metadata may be backwards incompatible before version 1.0.
Getting Started
For more background on MLMD and instructions on using it, see the getting started guide
Installing from PyPI
The recommended way to install ML Metadata is to use the PyPI package:
pip install ml-metadata
Installing from source
1. Prerequisites
To compile and use ML Metadata, you need to set up some prerequisites.
Install Bazel
If Bazel is not installed on your system, install it now by following these directions.
Install cmake
If cmake is not installed on your system, install it now by following these directions.
2. Clone ML Metadata repository
git clone https://github.com/tensorflow/ml-metadata
cd ml-metadata
Note that these instructions will install the latest master branch of ML
Metadata. If you want to install a specific branch (such as a release branch),
pass -b <branchname>
to the git clone
command.
3. Build the pip package
ML Metadata uses Bazel to build the pip package from source:
bazel run -c opt --define grpc_no_ares=true ml_metadata:build_pip_package
You can find the generated .whl
file in the dist
subdirectory.
4. Install the pip package
pip install dist/*.whl
Supported platforms
MLMD is built and tested on the following 64-bit operating systems:
- macOS 10.12.6 (Sierra) or later.
- Ubuntu 14.04 or later.
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