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Original file line number Diff line number Diff line change
Expand Up @@ -266,7 +266,8 @@ def f(self, time: torch.Tensor) -> torch.Tensor:
return torch.zeros_like(time)

def g(self, time: torch.Tensor) -> torch.Tensor:
return torch.sqrt(self.c) * self.k**self.time
c = torch.as_tensor(self.c, device=time.device, dtype=time.dtype)
return torch.sqrt(c) * self.k**time

def alpha(self, time: torch.Tensor) -> torch.Tensor:
return torch.ones_like(time)
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,19 @@
NUM_STEPS = [1, 5, 10, 20, 100]


@pytest.mark.unit
def test_sb_noise_schedule_ve_g_uses_input_time_and_preserves_dtype():
noise_schedule = SBNoiseScheduleVE(k=2.0, c=0.5, num_steps=5)
time = torch.tensor([0.0, 0.5, 1.0], dtype=torch.float64)

g = noise_schedule.g(time)

expected = torch.sqrt(torch.tensor(0.5, dtype=time.dtype, device=time.device)) * 2.0**time
torch.testing.assert_close(g, expected)
assert g.dtype == time.dtype
assert g.device == time.device


@pytest.mark.parametrize("num_steps", NUM_STEPS)
@pytest.mark.parametrize("process", ["sde", "ode"])
@pytest.mark.parametrize("noise_schedule_type", ["ve", "vp"])
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