47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
import unittest
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import torch
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from backbones import TemporalAttention
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class TemporalAttentionTest(unittest.TestCase):
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def test_zero_rbf_bias_has_live_projection_gradient(self) -> None:
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torch.manual_seed(0)
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attention = TemporalAttention(
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n_embd=12,
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n_head=3,
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use_time_rope=False,
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use_rbf_bias=True,
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)
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features = torch.randn(2, 4, 4, 16)
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target = torch.randn(2, 4, 4, 3)
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initial_bias = (
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attention.time_bias_scale.tanh()
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* attention.rbf_proj(features)
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)
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torch.testing.assert_close(initial_bias, torch.zeros_like(initial_bias))
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(initial_bias * target).sum().backward()
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projection_grad = attention.rbf_proj.weight.grad
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self.assertIsNotNone(projection_grad)
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self.assertGreater(projection_grad.abs().sum().item(), 0.0)
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with torch.no_grad():
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attention.rbf_proj.weight.add_(projection_grad, alpha=-1e-3)
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attention.zero_grad(set_to_none=True)
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updated_bias = (
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attention.time_bias_scale.tanh()
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* attention.rbf_proj(features)
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)
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(updated_bias * target).sum().backward()
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scale_grad = attention.time_bias_scale.grad
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self.assertIsNotNone(scale_grad)
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self.assertGreater(scale_grad.abs().item(), 0.0)
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if __name__ == "__main__":
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unittest.main()
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