如何将C++框架与机器学习集成

#include <Eigen/Dense>
#include <tensorflow/core/framework/op.h>
#include <tensorflow/core/framework/op_kernel.h>
#include <tensorflow/core/framework/shape_inference.h>

using namespace Eigen;

class LinearRegressionOp : public tensorflow::OpKernel {
 public:
  explicit LinearRegressionOp(tensorflow::OpKernelConstruction* context) : OpKernel(context) {}

  void Compute(tensorflow::OpKernelContext* context) override {
    // Get input tensors
    const auto& features = context->input(0);
    const auto& labels = context->input(1);

    // Convert tensors to Eigen matrices
    Eigen::MatrixXf X(features.flat<float>().data(), features.dim_size(0), features.dim_size(1));
    Eigen::VectorXf y(labels.flat<float>().data(), labels.dim_size(1));

    // Solve the linear regression problem
    Eigen::VectorXf weights = (X.transpose() * X).ldlt().solve(X.transpose() * y);

    // Create output tensor
    tensorflow::Tensor* output = nullptr;
    OP_REQUIRES_OK(context, context->allocate_output(0, {weights.rows(), 1}, &output));

    // Copy weights to output tensor
    auto output_flat = output->flat<float>();
    for (int i = 0; i < weights.rows(); i++) {
      output_flat(i) = weights(i);
    }
  }
};