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#ifndef CAFFE2_OPERATORS_INT8_RESIZE_NEAREST_OP_H_
#define CAFFE2_OPERATORS_INT8_RESIZE_NEAREST_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include <c10/util/irange.h>
namespace caffe2 {
namespace int8 {
class Int8ResizeNearestOp final : public Operator<CPUContext> {
public:
template <class... Args>
explicit Int8ResizeNearestOp(Args&&... args)
: Operator<CPUContext>(std::forward<Args>(args)...) {
width_scale_ = this->template GetSingleArgument<float>("width_scale", 1);
height_scale_ = this->template GetSingleArgument<float>("height_scale", 1);
output_dims =
this->template GetRepeatedArgument<int>("output_size", vector<int>{});
CAFFE_ENFORCE_GT(width_scale_, 0);
CAFFE_ENFORCE_GT(height_scale_, 0);
}
bool RunOnDevice() override {
// Assume NHWC layout.
const auto& X = Inputs()[0]->template Get<Int8TensorCPU>();
auto* Y = Outputs()[0]->template GetMutable<Int8TensorCPU>();
CAFFE_ENFORCE_EQ(4, X.t.dim());
const int N = X.t.dim32(0);
const int IH = X.t.dim32(1);
const int IW = X.t.dim32(2);
const int C = X.t.dim32(3);
if (!output_dims.empty()) {
CAFFE_ENFORCE_EQ(
2, output_dims.size(), "Int8ResizeNearest expects 2 dim output size");
height_scale_ = output_dims[0] / IH;
width_scale_ = output_dims[1] / IW;
}
const int OW = IW * width_scale_;
const int OH = IH * height_scale_;
ReinitializeTensor(&Y->t, {N, OH, OW, C}, at::dtype<uint8_t>().device(CPU));
Y->scale = X.scale;
Y->zero_point = X.zero_point;
int32_t Y_offset = this->template GetSingleArgument<int>("Y_zero_point", 0);
auto Y_scale = this->template GetSingleArgument<float>("Y_scale", 1);
TORCH_CHECK_EQ(Y_offset, X.zero_point);
TORCH_CHECK_EQ(Y_scale, X.scale);
const uint8_t* Xdata = X.t.data<uint8_t>();
uint8_t* Ydata = Y->t.mutable_data<uint8_t>();
for (const auto n : c10::irange(N)) {
for (const auto y : c10::irange(OH)) {
const int in_y = std::min((int)(y / height_scale_), (IH - 1));
for (const auto x : c10::irange(OW)) {
const int in_x = std::min((int)(x / width_scale_), (IW - 1));
std::memcpy(
&Ydata[C * x + C * OW * y + C * OW * OH * n],
&Xdata[C * in_x + C * IW * in_y + C * IW * IH * n],
C);
}
}
}
return true;
}
private:
float width_scale_;
float height_scale_;
vector<int> output_dims;
};
} // namespace int8
} // namespace caffe2
#endif // CAFFE2_OPERATORS_INT8_RESIZE_NEAREST_OP_H_
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