/usr/local/lib64/python3.6/site-packages/torch/include/caffe2/operators
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/caffe2/operators/channel_stats_op.h (1807B)
#ifndef CAFFE2_OPERATORS_CHANNEL_STATS_OP_H_
#define CAFFE2_OPERATORS_CHANNEL_STATS_OP_H_
#include
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template
class ChannelStatsOp final : public Operator {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template
explicit ChannelStatsOp(Args&&... args)
: Operator(std::forward(args)...),
order_(StringToStorageOrder(
this->template GetSingleArgument("order", "NCHW"))) {
CAFFE_ENFORCE_NE(order_, StorageOrder::UNKNOWN);
}
bool RunOnDevice() override {
return DispatchHelper>::call(this, Input(0));
}
template
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());
auto* sumsq = Output(1, {C}, at::dtype());
const T* X_data = X.template data();
T* sum_data = sum->template mutable_data();
T* sumsq_data = sumsq->template mutable_data();
return order_ == StorageOrder::NCHW
? ComputeChannelStatsNCHW(N, C, HxW, X_data, sum_data, sumsq_data)
: ComputeChannelStatsNHWC(N, C, HxW, X_data, sum_data, sumsq_data);
}
private:
template
bool
ComputeChannelStatsNCHW(int N, int C, int HxW, const T* X, T* sum, T* sumsq);
template
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_