#ifndef CAFFE2_OPERATORS_SCALE_BLOBS_OP_H_
|
#define CAFFE2_OPERATORS_SCALE_BLOBS_OP_H_
|
|
#include "caffe2/core/context.h"
|
#include "caffe2/core/operator.h"
|
#include "caffe2/utils/math.h"
|
|
namespace caffe2 {
|
|
template <class Context>
|
class ScaleBlobsOp final : public Operator<Context> {
|
public:
|
USE_OPERATOR_CONTEXT_FUNCTIONS;
|
template <class... Args>
|
explicit ScaleBlobsOp(Args&&... args)
|
: Operator<Context>(std::forward<Args>(args)...),
|
OP_SINGLE_ARG(float, "scale", scale_, 1.0f) {}
|
|
template <typename T>
|
bool DoRunWithType() {
|
int batchSize = InputSize();
|
|
for (int i = 0; i < batchSize; ++i) {
|
const auto& X = Input(i);
|
auto* Y = Output(i, X.sizes(), at::dtype<T>());
|
math::Scale<float, T, Context>(
|
X.numel(),
|
scale_,
|
X.template data<T>(),
|
Y->template mutable_data<T>(),
|
&context_);
|
}
|
return true;
|
}
|
|
bool RunOnDevice() override {
|
for (int i = 0; i < InputSize(); ++i) {
|
auto& input = this->template Input<Tensor>(i, CPU);
|
auto* output = this->template Output<Tensor>(i, CPU);
|
output->ResizeLike(input);
|
}
|
return DispatchHelper<TensorTypes<float>>::call(this, Input(0));
|
}
|
|
private:
|
const float scale_;
|
Tensor blobSizes_;
|
Tensor inputs_;
|
Tensor outputs_;
|
|
Tensor hostBlobSizes_;
|
Tensor hostInputs_;
|
Tensor hostOutputs_;
|
};
|
|
} // namespace caffe2
|
|
#endif // CAFFE2_OPERATORS_SCALE_BLOBS_OP_H_
|
