#ifndef CAFFE2_OPERATORS_PAD_OP_H_
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#define CAFFE2_OPERATORS_PAD_OP_H_
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#include "caffe2/core/context.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/operators/conv_pool_op_base.h"
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#include "caffe2/utils/math.h"
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namespace caffe2 {
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// Padding mode similar to numpy.
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enum class PadMode {
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CONSTANT = 0, // pad constant values, with string "constant"
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REFLECT = 1, // pads with reflect values, with string "reflect"
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EDGE = 2, // pads with the edge values, with string "edge"
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};
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CAFFE2_API PadMode StringToPadMode(const string&);
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template <typename T, class Context>
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class PadImageOp final : public ConvPoolOpBase<Context> {
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public:
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USE_CONV_POOL_BASE_FUNCTIONS(Context);
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template <class... Args>
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explicit PadImageOp(Args&&... args)
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: ConvPoolOpBase<Context>(std::forward<Args>(args)...),
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mode_(StringToPadMode(
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this->template GetSingleArgument<string>("mode", "constant"))),
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value_(static_cast<T>(
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this->template GetSingleArgument<float>("value", 0.0))) {
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CAFFE_ENFORCE(
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legacy_pad_ == LegacyPadding::NOTSET,
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"Padding layer only supports explicit pad values.");
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CAFFE_ENFORCE(
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dilation_h() == 1 && dilation_w() == 1,
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"Pooling op does not support dilation right now.");
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CAFFE_ENFORCE(
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stride_h() == 1 && stride_w() == 1,
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"Pooling op does not support stride right now.");
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// Pad op does not use kernel sizes, so we set it to 1 for computing the
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// output size.
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kernel_.assign(pads_.size() / 2, 1);
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}
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~PadImageOp() {}
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bool RunOnDeviceWithOrderNCHW() override;
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bool RunOnDeviceWithOrderNHWC() override;
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static std::vector<TensorShape> PadTensorInference(
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const OperatorDef& def,
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const vector<TensorShape>& in);
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private:
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PadMode mode_;
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T value_;
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// Input: X
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// Output: Y
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};
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template <typename T, class Context>
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class PadImageGradientOp final : public ConvPoolOpBase<Context> {
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public:
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USE_CONV_POOL_BASE_FUNCTIONS(Context);
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template <class... Args>
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explicit PadImageGradientOp(Args&&... args)
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: ConvPoolOpBase<Context>(std::forward<Args>(args)...),
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mode_(StringToPadMode(
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this->template GetSingleArgument<string>("mode", "constant"))) {
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CAFFE_ENFORCE(
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legacy_pad_ == LegacyPadding::NOTSET,
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"Padding layer only supports explicit pad values.");
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CAFFE_ENFORCE(
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dilation_h() == 1 && dilation_w() == 1,
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"Pooling op does not support dilation right now.");
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// Pad op does not use kernel sizes, so we set it to 1 for computing the
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// output size.
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kernel_.assign(pads_.size() / 2, 1);
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}
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~PadImageGradientOp() {}
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bool RunOnDeviceWithOrderNCHW() override;
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bool RunOnDeviceWithOrderNHWC() override;
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private:
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PadMode mode_;
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// Input: dY
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// Output: dX
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};
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} // namespace caffe2
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#endif // CAFFE2_OPERATORS_PAD_OP_H_
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