ONE - On-device Neural Engine
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#include <GradientApplier.h>
Public Member Functions | |
GradientApplier () | |
~GradientApplier ()=default | |
void | configure (const exec::train::optimizer::Optimizer *optimizer, const IPortableTensor *gradient, ITrainableTensor *trainable) |
void | applyGradient (uint32_t training_step) override |
Apply gradients to a trainable tensor. | |
Public Member Functions inherited from onert::exec::train::IGradientApplier | |
virtual | ~IGradientApplier ()=default |
Definition at line 33 of file GradientApplier.h.
onert::backend::train::ops::GradientApplier::GradientApplier | ( | ) |
Definition at line 30 of file GradientApplier.cc.
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default |
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overridevirtual |
Apply gradients to a trainable tensor.
training_step | The number of iterations of the training process. |
Implements onert::exec::train::IGradientApplier.
Definition at line 43 of file GradientApplier.cc.
References onert::exec::train::optimizer::Optimizer::applyGradient().
void onert::backend::train::ops::GradientApplier::configure | ( | const exec::train::optimizer::Optimizer * | optimizer, |
const IPortableTensor * | gradient, | ||
ITrainableTensor * | trainable | ||
) |
Definition at line 35 of file GradientApplier.cc.