Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Hello team,
In recent times, we had the opportunity to experiment with the usage of ml-metadata following the official documentation, specifically focusing on using MLMD with a gRPC server [1].
Initially, based on the examples in the doc currently, we were led to believe users are forced to handle RPC requests/responses, thus requiring a different approach compared to what is shown in the non-gRPC server scenario [2].
After some code investigation, we discovered that it is actually possible to use the
MetadataStore
by providing it with aMetadataStoreClientConfig
as a parameter (with proper MLMD gRPC host and port).This way, users do not need to manage gRPC requests and responses themselves, unless they have a valid reason to do so.
In order to demonstrate its usage, I have created a simple notebook [3] that precisely executes all the steps described in the documentation [2] by making use of a
MetadataStore
configured with aMetadataStoreClientConfig
.We believe that adding this information to the documentation could be very useful and helpful for all ml-metadata users.
Hope this helps!
[1] https://www.tensorflow.org/tfx/guide/mlmd#use_mlmd_with_a_remote_grpc_server
[2] https://www.tensorflow.org/tfx/guide/mlmd#integrate_ml_metadata_into_your_ml_workflows
[3] https://github.com/lampajr/demo20231018-mlmd-showcase/blob/d9c6d31cb4c9221e62f6915c41d73cad132505e4/mlmd-grpc-store.ipynb