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#ifndef CAFFE2_OPERATORS_SQUARE_ROOT_DIVIDE_OP_H_
#define CAFFE2_OPERATORS_SQUARE_ROOT_DIVIDE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
#include "c10/util/irange.h"
namespace caffe2 {
template <class Context>
class SquareRootDivideOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_DISPATCH_HELPER;
template <class... Args>
explicit SquareRootDivideOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...) {}
bool RunOnDevice() override {
return DispatchHelper<TensorTypes<float>>::call(this, Input(DATA));
}
private:
template <typename TData>
bool DoRunWithType() {
return DispatchHelper<TensorTypes2<float, int32_t, int64_t>, TData>::call(
this, Input(SCALE));
}
template <typename TData, typename TScale>
bool DoRunWithType2() {
auto& data = Input(DATA);
auto& scale = Input(SCALE);
auto* Y = Output(0, data.sizes(), at::dtype<TData>());
size_t batchSize = data.size(0);
size_t exampleSize = data.size_from_dim(1);
// NOLINTNEXTLINE(clang-diagnostic-sign-compare)
CAFFE_ENFORCE(batchSize == scale.size(0), batchSize, " != ", scale.size(0));
auto* scalePtr = scale.template data<TScale>();
auto* dataPtr = data.template data<TData>();
auto* yPtr = Y->template mutable_data<TData>();
for (const auto i : c10::irange(0U, batchSize)) {
auto scale = scalePtr[i];
CAFFE_ENFORCE(scale >= 0, scale, " < 0");
auto multiplier = scale == 0 ? 1.0 : 1 / std::sqrt(scale);
math::Scale<float, TData, Context>(
exampleSize,
multiplier,
dataPtr + i * exampleSize,
yPtr + i * exampleSize,
&context_);
}
return true;
}
INPUT_TAGS(DATA, SCALE);
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_SQUARE_ROOT_DIVIDE_OP_H_
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