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import torch
import torch.nn as nun
class SimpleModel(nun.Module):
def __init__(self):
super(SimpleModel, self).__init__()
self.linear = nun.Linear(10, 1)
def forward(self, x):
return self.linear(x)
model= SimpleModel()
model.linear
x = torch.randn(1, 10)
t1 = x.to(torch.float)
with torch.no_grad():
prediction = model(t1).tolist()
print(prediction)
model= SimpleModel()
torch.save(model.state_dict(),'model.pth')
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