41 lines
1.5 KiB
Python
41 lines
1.5 KiB
Python
# ========================================================
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# Media and Cognition
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# Homework 3 Support Vector Machine
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# check.py - Check your implementation of several modules
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# Tsinghua University
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# (C) Copyright 2024
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# ========================================================
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from svm_hw import SVM_HINGE, LinearFunction, Hinge
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import torch
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from torch.autograd import gradcheck
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def run():
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model = SVM_HINGE(2, C=1.0).double()
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x = torch.randn(50, 2, requires_grad=False).double()
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W = torch.randn(1, 2, requires_grad=True).double()
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b = torch.zeros(1, requires_grad=True).double()
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test = gradcheck(LinearFunction.apply, (x, W, b), eps=1e-6, atol=1e-4)
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if test:
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print('Linear successully tested!')
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output = torch.randn(50, 1, requires_grad=True).double()
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W = torch.randn(1, 2, requires_grad=True).double()
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labels = torch.ones(1, requires_grad=False).double()
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C = torch.tensor([[1.0]], requires_grad=False).double()
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test = gradcheck(Hinge.apply, (output, W, labels, C), eps=1e-6, atol=1e-5)
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if test:
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print('Hinge successfully tested！')
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x = torch.randn(50, 2, requires_grad=False).double()
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labels = torch.ones(50, requires_grad=False).double()
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try:
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output, loss = model(x, labels)
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assert model.W.requires_grad is True
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assert model.b.requires_grad is True
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print('SVM_HINGE successfully tested！')
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except:
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raise Exception('Failed testing SVM_HINGE!')
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if __name__ == '__main__':
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run() |