Method Forward_cpu

src/caffe/layers/eltwise_layer.cpp:47–99

template <typename Dtype>
void EltwiseLayer<Dtype>::Forward_cpu(
    const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top) {
  int* mask = NULL;
  const Dtype* bottom_data_a = NULL;
  const Dtype* bottom_data_b = NULL;
  const int count = top[0]->count();
  Dtype* top_data = top[0]->mutable_cpu_data();
  switch (op_) {
  case EltwiseParameter_EltwiseOp_PROD:
    caffe_mul(count, bottom[0]->cpu_data(), bottom[1]->cpu_data(), top_data);
    for (int i = 2; i < bottom.size(); ++i) {
      caffe_mul(count, top_data, bottom[i]->cpu_data(), top_data);
    }
    break;
  case EltwiseParameter_EltwiseOp_SUM:
    caffe_set(count, Dtype(0), top_data);
    // TODO(shelhamer) does BLAS optimize to sum for coeff = 1?
    for (int i = 0; i < bottom.size(); ++i) {
      caffe_axpy(count, coeffs_[i], bottom[i]->cpu_data(), top_data);
    }
    break;
  case EltwiseParameter_EltwiseOp_MAX:
    // Initialize
    mask = max_idx_.mutable_cpu_data();
    caffe_set(count, -1, mask);
    caffe_set(count, Dtype(-FLT_MAX), top_data);
    // bottom 0 & 1
    bottom_data_a = bottom[0]->cpu_data();
    bottom_data_b = bottom[1]->cpu_data();
    for (int idx = 0; idx < count; ++idx) {
      if (bottom_data_a[idx] > bottom_data_b[idx]) {
        top_data[idx] = bottom_data_a[idx];  // maxval
        mask[idx] = 0;  // maxid
      } else {
        top_data[idx] = bottom_data_b[idx];  // maxval
        mask[idx] = 1;  // maxid
      }
    }
    // bottom 2++
    for (int blob_idx = 2; blob_idx < bottom.size(); ++blob_idx) {
      bottom_data_b = bottom[blob_idx]->cpu_data();
      for (int idx = 0; idx < count; ++idx) {
        if (bottom_data_b[idx] > top_data[idx]) {
          top_data[idx] = bottom_data_b[idx];  // maxval
          mask[idx] = blob_idx;  // maxid
        }
      }
    }
    break;
  default:
    LOG(FATAL) << "Unknown elementwise operation.";
  }
}

template <typename Dtype>
void EltwiseLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,