#pragma once
#include "caffe2/core/operator.h"
#include "caffe2/core/timer.h"
namespace caffe2 {
template <class Context>
void fp16_momentum_sgd_update(
int N,
const at::Half* g,
const at::Half* m,
at::Half* ng,
at::Half* nm,
const float* lr,
float momentum,
bool nesterov,
float weight_decay,
bool fp32_update,
at::Half* param,
Context* /*context*/) {}
template <typename T, class Context>
class FP16MomentumSGDUpdateOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
FP16MomentumSGDUpdateOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
momentum_(this->template GetSingleArgument<float>("momentum", 0.0)),
weight_decay_(
this->template GetSingleArgument<float>("weight_decay", 0.0)),
nesterov_(this->template GetSingleArgument<int>("nesterov", 0)),
// when set, fp32_update will read in the fp16 data but
// perform all the compute in fp32 precision.
fp32_update_(this->template GetSingleArgument<int>("fp32_update", 0)) {}
bool RunOnDevice() override {
auto device_type = Context::GetDeviceType();
// Iter live on the CPU
CAFFE_ENFORCE(OperatorBase::InputIsTensorType(GRAD, device_type));
CAFFE_ENFORCE(OperatorBase::InputIsTensorType(MOMENTUM, device_type));
CAFFE_ENFORCE(Input(LR).size() == 1);
CAFFE_ENFORCE(Input(GRAD).size() == Input(MOMENTUM).size());
Output(OUTPUT_GRAD)->ResizeLike(Input(GRAD));
Output(OUTPUT_MOMENTUM)->ResizeLike(Input(MOMENTUM));
fp16_momentum_sgd_update<Context>(
Input(GRAD).size(),
Input(GRAD).template data<T>(),
Input(MOMENTUM).template data<T>(),
Output(OUTPUT_GRAD)->template mutable_data<T>(),
Output(OUTPUT_MOMENTUM)->template mutable_data<T>(),
Input(LR).template data<float>(),
momentum_,
nesterov_,
weight_decay_,
fp32_update_,
Output(OUTPUT_PARAM)->template mutable_data<T>(),
&context_);
return true;
}
protected:
float momentum_{0.9};
float weight_decay_{0.0};
bool nesterov_;
bool fp32_update_;
INPUT_TAGS(GRAD, MOMENTUM, LR, PARAM);
OUTPUT_TAGS(OUTPUT_GRAD, OUTPUT_MOMENTUM, OUTPUT_PARAM);
};
}