I have been reading the documentation as well as the discussion on using
float16 instead of float32 to reduce memory footprint on a single GPU.
My task is to train a 3D convolutional neural network which has a large
memory footprint (as a result of the feature cubes and their gradients).
How should I shift from currently float32 to float16 if possible?
What is the step-by-step guide to do so?
Simply updating the configuration file with floatX = float16 breaks the
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