| 39 | |
| 40 | template <typename data_type> |
| 41 | void kernel_run(void* in_data, void* out_data, void* gamma_data, void* beta_data, const TShape shape) |
| 42 | { |
| 43 | const std::vector<int> dims = shape.GetDim(); |
| 44 | int batch_number = dims[0]; |
| 45 | int channel_num = dims[1]; |
| 46 | int channel_size = dims[2] * dims[3]; |
| 47 | int img_size = channel_num * channel_size; |
| 48 | |
| 49 | data_type* input = ( data_type* )in_data; |
| 50 | data_type* gamma = ( data_type* )gamma_data; |
| 51 | data_type* beta = ( data_type* )beta_data; |
| 52 | data_type* output = ( data_type* )out_data; |
| 53 | |
| 54 | for(int i = 0; i < batch_number; i++) |
| 55 | { |
| 56 | for(int c = 0; c < channel_num; c++) |
| 57 | { |
| 58 | int offset = i * img_size + c * channel_size; |
| 59 | for(int l = 0; l < channel_size; l++) |
| 60 | { |
| 61 | if(beta != nullptr) |
| 62 | output[offset + l] = input[offset + l] * gamma[c] + beta[c]; |
| 63 | else |
| 64 | output[offset + l] = input[offset + l] * gamma[c]; |
| 65 | } |
| 66 | } |
| 67 | } |
| 68 | } |
| 69 | |
| 70 | struct ScaleOps : public NodeOps |
| 71 | { |