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#ifndef CAFFE2_OPERATORS_PAD_OP_H_
#define CAFFE2_OPERATORS_PAD_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
// Padding mode similar to numpy.
enum class PadMode {
CONSTANT = 0, // pad constant values, with string "constant"
REFLECT = 1, // pads with reflect values, with string "reflect"
EDGE = 2, // pads with the edge values, with string "edge"
};
TORCH_API PadMode StringToPadMode(const string&);
template <typename T, class Context>
class PadImageOp final : public ConvPoolOpBase<Context> {
public:
USE_CONV_POOL_BASE_FUNCTIONS(Context);
template <class... Args>
explicit PadImageOp(Args&&... args)
: ConvPoolOpBase<Context>(std::forward<Args>(args)...),
mode_(StringToPadMode(
this->template GetSingleArgument<string>("mode", "constant"))),
value_(static_cast<T>(
this->template GetSingleArgument<float>("value", 0.0))) {
CAFFE_ENFORCE(
legacy_pad_ == LegacyPadding::NOTSET,
"Padding layer only supports explicit pad values.");
CAFFE_ENFORCE(
dilation_h() == 1 && dilation_w() == 1,
"Pooling op does not support dilation right now.");
CAFFE_ENFORCE(
stride_h() == 1 && stride_w() == 1,
"Pooling op does not support stride right now.");
// Pad op does not use kernel sizes, so we set it to 1 for computing the
// output size.
kernel_.assign(pads_.size() / 2, 1);
}
~PadImageOp() {}
bool RunOnDeviceWithOrderNCHW() override;
bool RunOnDeviceWithOrderNHWC() override;
static std::vector<TensorShape> PadTensorInference(
const OperatorDef& def,
const vector<TensorShape>& in);
private:
PadMode mode_;
T value_;
// Input: X
// Output: Y
};
template <typename T, class Context>
class PadImageGradientOp final : public ConvPoolOpBase<Context> {
public:
USE_CONV_POOL_BASE_FUNCTIONS(Context);
template <class... Args>
explicit PadImageGradientOp(Args&&... args)
: ConvPoolOpBase<Context>(std::forward<Args>(args)...),
mode_(StringToPadMode(
this->template GetSingleArgument<string>("mode", "constant"))) {
CAFFE_ENFORCE(
legacy_pad_ == LegacyPadding::NOTSET,
"Padding layer only supports explicit pad values.");
CAFFE_ENFORCE(
dilation_h() == 1 && dilation_w() == 1,
"Pooling op does not support dilation right now.");
// Pad op does not use kernel sizes, so we set it to 1 for computing the
// output size.
kernel_.assign(pads_.size() / 2, 1);
}
~PadImageGradientOp() {}
bool RunOnDeviceWithOrderNCHW() override;
bool RunOnDeviceWithOrderNHWC() override;
private:
PadMode mode_;
// Input: dY
// Output: dX
};
} // namespace caffe2
#endif // CAFFE2_OPERATORS_PAD_OP_H_
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