如何将MLP的神经网络从tensorflow转换到pytorch

import torch
import torch.nn as nn

class MLP(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(MLP, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(hidden_size, output_size)

    def forward(self, x):
        x = self.fc1(x)
        x = self.relu(x)
        x = self.fc2(x)
        return x

import tensorflow as tf

# 加载TensorFlow模型参数
tf_model_path = "path/to/tensorflow/model.ckpt"

with tf.Session() as sess:
    saver = tf.train.Saver()
    saver.restore(sess, tf_model_path)
    weights = {
        'fc1.weight': sess.run('fully_connected/weights:0'),
        'fc1.bias': sess.run('fully_connected/biases:0'),
        'fc2.weight': sess.run('fully_connected_1/weights:0'),
        'fc2.bias': sess.run('fully_connected_1/biases:0')
    }

mlp = MLP(input_size, hidden_size, output_size)
mlp.load_state_dict(weights)