| #ifndef CAFFE2_OPERATORS_CHANNEL_STATS_OP_H_ |
| #define CAFFE2_OPERATORS_CHANNEL_STATS_OP_H_ |
| |
| #include <string> |
| |
| #include "caffe2/core/context.h" |
| #include "caffe2/core/operator.h" |
| #include "caffe2/utils/math.h" |
| |
| namespace caffe2 { |
| |
| template <class Context> |
| class ChannelStatsOp final : public Operator<Context> { |
| public: |
| USE_OPERATOR_CONTEXT_FUNCTIONS; |
| |
| template <class... Args> |
| explicit ChannelStatsOp(Args&&... args) |
| : Operator<Context>(std::forward<Args>(args)...), |
| order_(StringToStorageOrder( |
| this->template GetSingleArgument<std::string>("order", "NCHW"))) { |
| CAFFE_ENFORCE_NE(order_, StorageOrder::UNKNOWN); |
| } |
| |
| bool RunOnDevice() override { |
| return DispatchHelper<TensorTypes<float>>::call(this, Input(0)); |
| } |
| |
| template <typename T> |
| bool DoRunWithType() { |
| const auto& X = Input(0); |
| const int ndim = X.dim(); |
| const int N = X.dim32(0); |
| const int C = order_ == StorageOrder::NCHW ? X.dim32(1) : X.dim32(ndim - 1); |
| const int HxW = X.numel() / (N * C); |
| auto* sum = Output(0, {C}, at::dtype<T>()); |
| auto* sumsq = Output(1, {C}, at::dtype<T>()); |
| const T* X_data = X.template data<T>(); |
| T* sum_data = sum->template mutable_data<T>(); |
| T* sumsq_data = sumsq->template mutable_data<T>(); |
| return order_ == StorageOrder::NCHW |
| ? ComputeChannelStatsNCHW<T>(N, C, HxW, X_data, sum_data, sumsq_data) |
| : ComputeChannelStatsNHWC<T>(N, C, HxW, X_data, sum_data, sumsq_data); |
| } |
| |
| private: |
| template <typename T> |
| bool |
| ComputeChannelStatsNCHW(int N, int C, int HxW, const T* X, T* sum, T* sumsq); |
| |
| template <typename T> |
| bool |
| ComputeChannelStatsNHWC(int N, int C, int HxW, const T* X, T* sum, T* sumsq); |
| |
| const StorageOrder order_; |
| }; |
| |
| } // namespace caffe2 |
| |
| #endif // CAFFE2_OPERATORS_CHANNEL_STATS_OP_H_ |