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Add support for training apis to support custom ops #16601
Add support for training apis to support custom ops #16601
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I am curious how custom ops are needed in on device training scenarios? the product team want to write their own operator?
orttraining/orttraining/python/training/onnxblock/_training_graph_utils.py
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…baijumeswani/training-artifacts-with-custom-ops
One of our partner teams has a need for the op This pull request allows for us to register any user provided custom op library (such as |
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Here are some comments.
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Looks good, there is one minor comments.
Co-authored-by: pengwa <[email protected]>
This pull request contains a few changes: 1. Adds support for string ort values. 2. Fixes the training minimal build (that was broken with #16601) by putting custom op registration behind #ifdefs 3. Fixes the iOS pod package generation (that was again broken with #16601) by explicitly providing paths to be copied during pod creation.
This pull request contains a few changes: 1. Adds support for string ort values. 2. Fixes the training minimal build (that was broken with #16601) by putting custom op registration behind #ifdefs 3. Fixes the iOS pod package generation (that was again broken with #16601) by explicitly providing paths to be copied during pod creation.
So far, the training API did not include support to register custom op libraries.
One of the models we are working with requires the use of
onnxruntime-extensions
.onnxruntime-extensions
is implemented as a custom op and needs to be registered withONNX Runtime
before an ONNX model containing the custom op nodes can be executed.This pull request adds the necessary tooling to register the custom op library for both, artifact generation, and graph execution.
In addition, this pull request also adds support for executing models with string tensor inputs.