小编alx*_*yok的帖子

我有一个计算向量的神经网络u。我想计算关于 input 的x一阶和二阶雅可比，单个元素。

有人知道如何在 PyTorch 中做到这一点吗？下面是我项目中的代码片段：

import torch
import torch.nn as nn

class PINN(torch.nn.Module):
    
    def __init__(self, layers:list):
        super(PINN, self).__init__()
        self.linears = nn.ModuleList([])
        for i, dim in enumerate(layers[:-2]):
            self.linears.append(nn.Linear(dim, layers[i+1]))
            self.linears.append(nn.ReLU())
        self.linears.append(nn.Linear(layers[-2], layers[-1]))
        
    def forward(self, x):
        for layer in self.linears:
            x = layer(x)
        return x

然后我实例化我的网络：

n_in = 1
units = 50
q = 500

pinn = PINN([n_in, units, units, units, q+1])
pinn

哪个返回

PINN(
  (linears): ModuleList(
    (0): Linear(in_features=1, out_features=50, bias=True)
    (1): ReLU()
    (2): Linear(in_features=50, out_features=50, bias=True) …