Change code into Tensorflow2 APIs #1475
DanielMao1
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In fact, there is an api called |
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Hello! From your question, I learned that you also participated in the asc22 competition, so I want to ask you a question, do you use the source code or the deepmd-kit installed by conda command? |
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Dear deepmd-kit developers,
I am trying to improve the GPU training process. I found that when I am training, the training step spend most of time in 'kernel launch'. I did the profiling for several days, and I think the training process have much small kernels(or tensorflow operations) which can be fused by tensorflow XLA. But this process requires me use 'tf.function' API, which is used in tensorflow2.
I would like to have a try to change the code into tensorflow2 APIs which may enable me use XLA to do GPU kernel fusion, which I think can boosting the training step.
My question is: do you think too much small kernels is bottleneck in small data set(192 atoms, 40000 frames, datasize<200MB)? Is this method a proper way to improve training process?
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