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#ifndef CAFFE2_OPERATORS_MEAN_OPS_H_
#define CAFFE2_OPERATORS_MEAN_OPS_H_
#include "caffe2/core/common_omp.h"
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/types.h"
#include "caffe2/utils/math.h"
#include "caffe2/utils/proto_utils.h"
#include "c10/util/irange.h"
namespace caffe2 {
template <class Context>
class MeanOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
USE_SIMPLE_CTOR_DTOR(MeanOp)
template <typename T>
bool DoRunWithType() {
auto& input0 = Input(0);
auto* output = Output(0, input0.sizes(), at::dtype<T>());
output->CopyFrom(input0, true /*async*/);
if (InputSize() == 1) {
return true;
}
// Dimension checking
for (const auto i : c10::irange(1, InputSize())) {
if (output->sizes() != Input(i).sizes()) {
CAFFE_THROW(
"Check failed: output->sizes() == Input(i).sizes().",
"Description: Input #",
i,
", input dimension:",
Input(i).sizes(),
" should match output dimension: ",
output->sizes());
}
}
T* output_data = output->template mutable_data<T>();
for (const auto i : c10::irange(1, InputSize())) {
math::Add(
output->numel(),
output_data,
Input(i).template data<T>(),
output_data,
&context_);
}
math::Scale(
output->numel(),
1.0f / InputSize(),
output_data,
output_data,
&context_);
return true;
}
bool RunOnDevice() override {
if (Input(0).template IsType<float>()) {
return DoRunWithType<float>();
} else if (Input(0).template IsType<double>()) {
return DoRunWithType<double>();
} else {
CAFFE_THROW(
"Mean operator only supports 32-bit float or 64-bit double, but",
" input was of type ",
Input(0).dtype().name());
}
}
};
template <class Context>
class MeanGradientOp : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit MeanGradientOp(Args&&... args)
: Operator<Context>(std::forward<Args>(args)...) {}
template <typename T>
bool DoRunWithType() {
auto& dY = Input(0);
const auto* dY_data = dY.template data<T>();
int size = dY.numel();
int num_inputs = OutputSize();
float scale = 1.0f / num_inputs;
// dX0 = scale * dY
auto* dX0 = Output(0, dY.sizes(), at::dtype<T>());
math::Scale(
size, scale, dY_data, dX0->template mutable_data<T>(), &context_);
// Copy the rest dX
for (const auto i : c10::irange(1, num_inputs)) {
auto* cur_dX = Output(i);
cur_dX->ResizeLike(dY);
cur_dX->CopyFrom(*dX0, true /*async*/);
}
return true;
}
bool RunOnDevice() override {
if (Input(0).template IsType<float>()) {
return DoRunWithType<float>();
} else if (Input(0).template IsType<double>()) {
return DoRunWithType<double>();
} else {
CAFFE_THROW(
"Mean operator only supports 32-bit float or 64-bit double, but",
" input was of type ",
Input(0).dtype().name());
}
}
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_MEAN_OPS_H_
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