import torch
import torch.nn as nn
from model import MobileNetV3_large
weight = 'weights/best.pkl'
net = MobileNetV3_large(num_classes = 3755)

net.eval()
if torch.cuda.is_available():
    net.cuda()
net.load_state_dict(torch.load(weight))
input_shape = (3, 224, 224) 
batch_size = 1
x = torch.randn(batch_size, *input_shape)   # 生成张量
if torch.cuda.is_available():
    x = x.to(torch.device("cuda"))
export_file="onnx/handwriting.onnx"

torch.onnx.export(net,x, export_file,input_names=["input"],output_names=["output"])