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@htahir1 htahir1 released this 22 Jan 16:20
· 6474 commits to main since this release
0.2.0
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This new release is a major one. Its the first to introduce our new integrations system, which is meant to be used to extend ZenML with various other ML/MLOps libraries easily. The first big advantage one gets is 🚀 PyTorch Support 🚀!

pip install --upgrade zenml

And to enable the PyTorch extension:

pip install zenml[pytorch]

New Features

  • Introduced integrations for ZenML with the extra_requires setuptools paradigm.
  • Added PyTorchTrainer support with easily extendable TorchBaseTrainer example.
  • Restructured trainer steps to be more intuitive to extend from Tensorflow and PyTorch. Now, we have a TrainerStep, followed by TFBaseTrainerStep and TorchBaseTrainerStep.
  • The input_fn of the TorchTrainer have implemented in a way that it can ingest from a tfrecords file. This marks one of the few projects out there
    that have native support for ingesting the TFRecords format into PyTorch directly.

Bug Fixes

  • Fixed an issue with Repository.get_zenml_dir() that caused any pipeline creates below root level to fail on creation.

Documentation Annoucement

The docs are almost complete! We are at 80% completion. Keep an eye out as we update with more details on how to use/extend ZenML and let us know via slack if there is something missing!

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