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Already using distributed training for some time in other forms, and this looks very easy, but the pipelines I have are multi-cloud so this couldn’t work in those cases.
Tekton / Kubeflow pipelines with Feast, Katib, and Horovod, deploying to TF Serving (also using other TFX components for quality control). Also used built-in cluster API and tf.distribute recently (since v2) instead of Horovod for some pipelines. Works across various providers.
Alternatively use federation in many cases, offloading some of the training to edge devices. Quality control is significantly harder with that pattern and doesn’t accomplish exactly the same things as traditional distributed training.
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