Just pass in training data with a lower precision type (e.g., singles versus doubles).
Lower precision in trainnet workflow
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Hi,
Is there a way to adjust the precision when training a network using the "trainnet" workflow (2024a)? I'm interested in lowering precision to speed up training, in the same way I would use "torch.set_float32_matmul_precision" in pytorch.
Thanks,
Eric
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