出现TypeError: issubclass() arg 2 must be a class, a tuple of classes, or a union

[xianzhixiong]

在运行model时，正常，转换tflite时不正常，出现TypeError: issubclass() arg 2 must be a class, a tuple of classes, or a union mode2.zip

[peterjc123]

@xianzhixiong 你的pth我们没法加载，没法调试啊。你有原始模型的代码吗？另外，tinynn里面没有issubclass的调用，所以这应该不是tinynn的问题

[zk1998]

import torch
import torch.nn as nn

from tinynn.graph.tracer import model_tracer
from tinynn.converter import TFLiteConverter

class SimpleNN(nn.Module):
    def __init__(self, input_size, num_classes):
        super(SimpleNN, self).__init__()
        self.fc1 = nn.Linear(input_size, 50)
        self.bn1 = nn.LayerNorm(50)  # 添加批量归一化层
        self.fc2 = nn.Linear(50, 30)
        self.bn2 = nn.LayerNorm(30)  # 添加批量归一化层
        self.fc3 = nn.Linear(30, 20)
        self.bn3 = nn.LayerNorm(20)  # 添加批量归一化层
        self.fc4 = nn.Linear(20, num_classes)

    def forward(self, x):
        x = torch.relu(self.bn1(self.fc1(x)))  # 在激活函数之前进行批量归一化
        x = torch.relu(self.bn2(self.fc2(x)))  # 在激活函数之前进行批量归一化
        x = torch.relu(self.bn3(self.fc3(x)))  # 在激活函数之前进行批量归一化
        x = self.fc4(x)
        return x

with model_tracer():
    dummy_input = torch.tensor([[0, -48, -92, 60587, 2319]])
    dummy_input = dummy_input.float()
    print(dummy_input)
    model = torch.load('mode2.pth', map_location=torch.device('cpu'))
    model.cpu()
    model.eval()

    output_path = "out/temp.tflite"
    model(dummy_input)
    print("OK")

    converter = TFLiteConverter(model, dummy_input, output_path)
    converter.convert()

The above code works, It is recommended to update to the latest TinyNN and try it out.