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TensorBoard is TensorFlow’s visualization toolkit enables tracking metrics like loss and accuracy, visualize the model graph, view histograms of weights, biases, or other tensors as they change over time, and much more.
A managed TensorBoard support in IBM CP4D would enable us monitoring, profiling, uploading and sharing GPU ML experiment results with relevant stakeholders.
Possible ways to get this in IBM CP4D and WMLA :
Add a managed TensorBoard service in CP4D and enable creating instance. This instance should be exposed so that WMLA jobs can submit appropriate logs towards it ( TensorBoard APIs to prepare TensorBoard logs. These logs can then be uploaded or streamed into CP4D TensorBoard instance )
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