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import numpy as np
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import pytest
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import torch
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from numpy.testing import assert_array_almost_equal
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from torch.autograd import Variable
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from mmaction.models import OHEMHingeLoss
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def test_ohem_hinge_loss():
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pred = torch.tensor([[
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0.5161, 0.5228, 0.7748, 0.0573, 0.1113, 0.8862, 0.1752, 0.9448, 0.0253,
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0.1009, 0.4371, 0.2232, 0.0412, 0.3487, 0.3350, 0.9294, 0.7122, 0.3072,
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0.2942, 0.7679
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]],
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requires_grad=True)
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gt = torch.tensor([8])
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num_video = 1
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loss = OHEMHingeLoss.apply(pred, gt, 1, 1.0, num_video)
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assert_array_almost_equal(
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loss.detach().numpy(), np.array([0.0552]), decimal=4)
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loss.backward(Variable(torch.ones([1])))
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assert_array_almost_equal(
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np.array(pred.grad),
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np.array([[
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0., 0., 0., 0., 0., 0., 0., -1., 0., 0., 0., 0., 0., 0., 0., 0.,
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0., 0., 0., 0.
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]]),
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decimal=4)
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with pytest.raises(ValueError):
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gt = torch.tensor([8, 10])
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loss = OHEMHingeLoss.apply(pred, gt, 1, 1.0, num_video)
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