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#pragma once
#include "caffe2/core/operator.h"
namespace caffe2 {
template <typename Context>
void wngrad_update(
int N,
const float* w,
const float* g,
const float* h,
float* nw,
float* nh,
float epsilon,
const float* lr,
Context* /*context*/) {
for (const auto i : c10::irange(N)) {
float gi = g[i];
nw[i] = w[i] + lr[0] * gi / (h[0] + epsilon);
}
float nhTmp = 0.0;
for (const auto i : c10::irange(N)) {
float gi = g[i];
nhTmp += gi * gi;
}
nhTmp /= (h[0] + epsilon);
nh[0] = h[0] + nhTmp;
}
template <typename Context>
void wngrad_update_output_effective_lr(
int N,
const float* paramIn,
const float* gradIn,
const float* seqBIn,
float* paramOut,
float* seqBOut,
float* effectiveLROut,
float epsilon,
const float* lr,
Context* /*context*/) {
effectiveLROut[0] = lr[0] / (seqBIn[0] + epsilon);
float seqBTmp = 0.0;
for (const auto i : c10::irange(N)) {
float gi = gradIn[i];
seqBTmp += gi * gi;
}
seqBTmp /= (seqBIn[0] + epsilon);
seqBOut[0] = seqBIn[0] + seqBTmp;
for (const auto i : c10::irange(N)) {
float grad = gradIn[i];
paramOut[i] = paramIn[i] + effectiveLROut[0] * grad;
}
}
template <typename Context>
void wngrad_update_output_effective_lr_and_update(
int N,
const float* paramIn,
const float* gradIn,
const float* seqBIn,
float* paramOut,
float* seqBOut,
float* effectiveLROut,
float* updateOut,
float epsilon,
const float* lr,
Context* /*context*/) {
effectiveLROut[0] = lr[0] / (seqBIn[0] + epsilon);
float seqBTmp = 0.0;
for (const auto i : c10::irange(N)) {
float gi = gradIn[i];
seqBTmp += gi * gi;
}
seqBTmp /= (seqBIn[0] + epsilon);
seqBOut[0] = seqBIn[0] + seqBTmp;
for (const auto i : c10::irange(N)) {
float grad = gradIn[i];
float update = updateOut[i] = effectiveLROut[0] * grad;
paramOut[i] = paramIn[i] + update;
}
}
template <typename T, class Context>
class WngradOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
WngradOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
epsilon_(this->template GetSingleArgument<T>("epsilon", 1e-5f)) {}
bool RunOnDevice() override {
CAFFE_ENFORCE_EQ(
Input(GRAD).numel(),
Input(PARAM).numel(),
"PARAM size: ",
Input(PARAM).numel(),
", GRAD size: ",
Input(GRAD).numel(),
", SEQ_B size: ",
Input(SEQ_B).numel(),
", LR size: ",
Input(LR).numel());
Output(OUTPUT_PARAM)->ResizeLike(Input(PARAM));
Output(OUTPUT_SEQ_B)->ResizeLike(Input(SEQ_B));
if (OutputSize() == 2) {
wngrad_update<Context>(
Input(GRAD).numel(),
Input(PARAM).template data<T>(),
Input(GRAD).template data<T>(),
Input(SEQ_B).template data<T>(),
Output(OUTPUT_PARAM)->template mutable_data<T>(),
Output(OUTPUT_SEQ_B)->template mutable_data<T>(),
epsilon_,
Input(LR).template data<T>(),
&context_);
} else if (OutputSize() == 3) {
Output(OUTPUT_EFFECTIVE_LR)->ResizeLike(Input(SEQ_B));
wngrad_update_output_effective_lr<Context>(
Input(GRAD).numel(),
Input(PARAM).template data<T>(),
Input(GRAD).template data<T>(),
Input(SEQ_B).template data<T>(),
Output(OUTPUT_PARAM)->template mutable_data<T>(),
Output(OUTPUT_SEQ_B)->template mutable_data<T>(),
Output(OUTPUT_EFFECTIVE_LR)->template mutable_data<T>(),
epsilon_,
Input(LR).template data<T>(),
&context_);
} else {
Output(OUTPUT_EFFECTIVE_LR)->ResizeLike(Input(SEQ_B));
Output(OUTPUT_UPDATE)->ResizeLike(Input(GRAD));
wngrad_update_output_effective_lr_and_update<Context>(
Input(GRAD).numel(),
Input(PARAM).template data<T>(),
Input(GRAD).template data<T>(),
Input(SEQ_B).template data<T>(),
Output(OUTPUT_PARAM)->template mutable_data<T>(),
Output(OUTPUT_SEQ_B)->template mutable_data<T>(),
Output(OUTPUT_EFFECTIVE_LR)->template mutable_data<T>(),
Output(OUTPUT_UPDATE)->template mutable_data<T>(),
epsilon_,
Input(LR).template data<T>(),
&context_);
}
return true;
}
protected:
T epsilon_;
INPUT_TAGS(PARAM, SEQ_B, GRAD, LR);
OUTPUT_TAGS(OUTPUT_PARAM, OUTPUT_SEQ_B, OUTPUT_EFFECTIVE_LR, OUTPUT_UPDATE);
};
template <typename T, class Context>
class SparseWngradOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
SparseWngradOp(const OperatorDef& operator_def, Workspace* ws)
: Operator<Context>(operator_def, ws),
epsilon_(this->template GetSingleArgument<float>("epsilon", 1e-5f)) {}
bool RunOnDevice() override {
// Enforce shapes
CAFFE_ENFORCE_EQ(Input(SEQ_B).numel(), 1);
CAFFE_ENFORCE_EQ(Input(LR).numel(), 1);
CAFFE_ENFORCE_EQ(
Input(PARAM).size_from_dim(1),
Input(GRAD).size_from_dim(Input(INDICES).dim()));
return DispatchHelper<TensorTypes<int32_t, int64_t>>::call(
this, Input(INDICES));
}
template <typename SIndex>
bool DoRunWithType() {
const auto* lr = Input(LR).template data<T>();
const auto* indices = Input(INDICES).template data<SIndex>();
const auto* gradIn = Input(GRAD).template data<T>();
const auto* paramIn = Input(PARAM).template data<T>();
const auto* seqBIn = Input(SEQ_B).template data<T>();
auto* paramOut = Output(OUTPUT_PARAM)->template mutable_data<T>();
auto* seqBOut = Output(OUTPUT_SEQ_B)->template mutable_data<T>();
auto n = Input(INDICES).numel();
if (n == 0) {
return true;
}
auto block_size = Input(GRAD).numel() / n;
for (const auto i : c10::irange(n)) {
auto idx = indices[i];
if (block_size == 1) {
float gi = gradIn[i];
paramOut[idx] = paramIn[idx] + lr[0] * gi / (seqBIn[0] + epsilon_);
} else {
auto offsetI = i * block_size;
auto offsetIdx = idx * block_size;
#ifndef NDEBUG
CAFFE_ENFORCE_GE(
Input(PARAM).numel(),
block_size + offsetIdx,
this->debug_def().input(PARAM),
", out of bound, idx:",
idx,
" for input i:",
i,
" and block size:",
block_size);
CAFFE_ENFORCE_GE(
Input(GRAD).numel(),
block_size + offsetI,
this->debug_def().input(GRAD),
", out of bound idx, idx:",
idx,
" for input i:",
i);
#endif
for (const auto j : c10::irange(block_size)) {
float gi = gradIn[offsetI + j];
paramOut[offsetIdx + j] =
paramIn[offsetIdx + j] + lr[0] * gi / (seqBIn[0] + epsilon_);
}
}
}
float seqBTmp = 0.0;
for (const auto i : c10::irange(Input(GRAD).numel())) {
float gi = gradIn[i];
seqBTmp += gi * gi;
}
seqBTmp /= seqBIn[0];
seqBOut[0] = seqBTmp + seqBIn[0];
return true;
}
protected:
T epsilon_;
INPUT_TAGS(PARAM, SEQ_B, INDICES, GRAD, LR);
OUTPUT_TAGS(OUTPUT_PARAM, OUTPUT_SEQ_B);
};
} // namespace caffe2
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