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⚡️ Speed up method CogView4DenoiseInvocation._convert_timesteps_to_sigmas by 24% #142

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⚡️ Speed up method CogView4DenoiseInvocation._convert_timesteps_to_sigmas by 24% #142

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16 changes: 4 additions & 12 deletions invokeai/app/invocations/cogview4_denoise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,18 +176,10 @@ def _convert_timesteps_to_sigmas(self, image_seq_len: int, timesteps: torch.Tens
# This implementation differs slightly from the original for the sake of simplicity (differs in terminal value
# handling, not quantizing timesteps to integers, etc.).

def calculate_timestep_shift(
image_seq_len: int, base_seq_len: int = 256, base_shift: float = 0.25, max_shift: float = 0.75
) -> float:
m = (image_seq_len / base_seq_len) ** 0.5
mu = m * max_shift + base_shift
return mu

def time_shift_linear(mu: float, sigma: float, t: torch.Tensor) -> torch.Tensor:
return mu / (mu + (1 / t - 1) ** sigma)

mu = calculate_timestep_shift(image_seq_len)
sigmas = time_shift_linear(mu, 1.0, timesteps)
m = (image_seq_len / 256) ** 0.5
mu = m * 0.75 + 0.25

sigmas = mu / (mu + (1.0 / timesteps - 1.0))
return sigmas.tolist()

def _run_diffusion(
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