如何将以下tensorflow代码转换为pytorch

import tensorflow as tf

# 创建一个 TensorFlow 图
graph = tf.Graph()
with graph.as_default():
    # 定义输入占位符
    input_placeholder = tf.placeholder(tf.float32, shape=(None, 784))
    # 定义全连接层
    fc_layer = tf.layers.dense(input_placeholder, 256, activation=tf.nn.relu)
    # 定义输出层
    output_layer = tf.layers.dense(fc_layer, 10, activation=None)

# 创建会话并运行图
with tf.Session(graph=graph) as sess:
    # 初始化变量
    sess.run(tf.global_variables_initializer())
    # 运行图
    output = sess.run(output_layer, feed_dict={input_placeholder: input_data})
    print(output)

import torch
import torch.nn as nn

# 定义 PyTorch 模型类
class MyModel(nn.Module):
    def __init__(self):
        super(MyModel, self).__init__()
        self.fc_layer = nn.Linear(784, 256)
        self.output_layer = nn.Linear(256, 10)

    def forward(self, x):
        x = torch.relu(self.fc_layer(x))
        x = self.output_layer(x)
        return x

# 创建模型实例
model = MyModel()

# 创建输入数据
input_data = torch.randn(1, 784)

# 运行模型
output = model(input_data)
print(output)