This talk showcases multiple performance improvements in TensorFlow 2.2 to accelerate and scale users’ ML training workload to multi-worker multi-GPUs. We walk through the optimizations using a BERT fine-tuning task in TF model garden, written using a custom training loop.
#tensorflow