#ifndef CAFFE2_OPERATORS_LOCAL_RESPONSE_NORMALIZATION_OP_H_
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#define CAFFE2_OPERATORS_LOCAL_RESPONSE_NORMALIZATION_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/utils/math.h"
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namespace caffe2 {
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template <typename T, class Context>
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class LRNOpBase : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit LRNOpBase(Args&&... args)
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: Operator<Context>(std::forward<Args>(args)...),
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size_(this->template GetSingleArgument<int>("size", 0)),
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alpha_(this->template GetSingleArgument<float>("alpha", 0)),
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beta_(this->template GetSingleArgument<float>("beta", 0)),
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bias_(this->template GetSingleArgument<float>("bias", 1)),
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order_(StringToStorageOrder(
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this->template GetSingleArgument<string>("order", "NCHW"))),
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pre_pad_((size_ - 1) / 2) {
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DCHECK_GT(size_, 0);
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DCHECK_EQ(size_ % 2, 1);
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DCHECK_GT(alpha_, 0);
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DCHECK_GT(beta_, 0);
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}
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bool RunOnDevice() override {
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switch (order_) {
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case StorageOrder::NHWC:
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return RunOnDeviceWithOrderNHWC();
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case StorageOrder::NCHW:
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return RunOnDeviceWithOrderNCHW();
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default:
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LOG(FATAL) << "Unknown storage order: " << order_;
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}
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// To suppress old compiler warnings
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return true;
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}
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virtual bool RunOnDeviceWithOrderNCHW() = 0;
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virtual bool RunOnDeviceWithOrderNHWC() = 0;
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protected:
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const int size_;
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const float alpha_;
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const float beta_;
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const float bias_;
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const StorageOrder order_;
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const int pre_pad_;
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// Input: X; Output: Y, scale.
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};
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template <typename T, class Context>
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class LRNOp final : public LRNOpBase<T, Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit LRNOp(Args&&... args)
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: LRNOpBase<T, Context>(std::forward<Args>(args)...) {}
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bool RunOnDeviceWithOrderNCHW() override;
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bool RunOnDeviceWithOrderNHWC() override;
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protected:
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// Input: X; Output: Y, scale.
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OUTPUT_TAGS(OUTPUT, SCALE);
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Tensor* scale_ = nullptr;
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Tensor local_scale_tensor_{Context::GetDeviceType()};
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};
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template <typename T, class Context>
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class LRNGradientOp final : public LRNOpBase<T, Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit LRNGradientOp(Args&&... args)
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: LRNOpBase<T, Context>(std::forward<Args>(args)...) {}
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bool RunOnDeviceWithOrderNCHW() override;
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bool RunOnDeviceWithOrderNHWC() override;
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protected:
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// Input: X, Y, scale, dY; Output: dX
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INPUT_TAGS(INPUT, OUTPUT, SCALE, OUTPUT_GRAD);
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Tensor* scale_ = nullptr;
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Tensor local_scale_tensor_{Context::GetDeviceType()};
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};
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} // namespace caffe2
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#endif // CAFFE2_OPERATORS_LOCAL_RESPONSE_NORMALIZATION_OP_H_
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