如何在libtorch中重复张量

Question

我正在使用libtorch进行推理，我已将数据从txt文件读取到向量并转换为张量，我想重复张量 三次，然后将其更改为 3D， 我试过了，

std::vector<std::vector<float>> feature_data(255, std::vector<float>(221));
ifstream f_data("../data.txt"); // 
if (! f_data) {
    cout << "Error, file couldn't be opened" << endl; 
    return 1; 
}    
for(int i=0;i<255;i++)
{
    for(int j=0;j<221;j++)
    {
        if ( !f_data ) 
        {
            std::cout << "read error" << std::endl;
            break;
        }
        f_data >> feature_data[i][j];
    }
}
auto data_options = torch::TensorOptions().dtype(at::kFloat);
auto feature_tensor = torch::zeros({255,221}, data_options);
for (int i = 0; i < 255; i++)
    feature_tensor.slice(0, i,i+1) = torch::from_blob(feature_data[i].data(), {221}, 
    data_options);

// begin to repeat three times
auto tensor_clone = feature_tensor.clone();
auto one_time_clone = torch::cat({feature_tensor, tensor_clone}, 0);
auto two_times_clone = torch::cat({one_time_clone, tensor_clone}, 0);
auto transformed_asr = two_times_clone.view({3, 255, 221});

看起来很麻烦，不知道是否正确，有没有简单的方法？

Answer 1

...
for (int i = 0; i < 255; i++)
    feature_tensor.slice(0, i,i+1) = torch::from_blob(feature_data[i].data(), {221}, 
data_options);
auto tensor_clone = feature_tensor.repeat({3, 1});
...