y_x0 = torch.autograd.grad(y, 0,grad_outputs=torch.ones_like(net(pt_x_in)),create_graph=True)[0]
时间: 2024-05-30 13:16:51 浏览: 14
This line of code computes the gradient of a given function y with respect to its first argument (parameter 0) at a specific input point pt_x_in. The gradient is computed using automatic differentiation provided by PyTorch's autograd module.
The optional argument grad_outputs=torch.ones_like(net(pt_x_in)) specifies the shape and dtype of the initial gradient tensor. In this case, it creates a tensor of ones with the same shape as the output of the neural network net evaluated at pt_x_in.
The create_graph=True argument allows the computation graph to be retained, so that higher-order derivatives can be computed if needed. The resulting gradient tensor is returned as the output of the function.
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