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⚡️ Speed up method CogView4DenoiseInvocation._prepare_cfg_scale by 27% #141

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⚡️ Speed up method CogView4DenoiseInvocation._prepare_cfg_scale by 27% #141

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15 changes: 7 additions & 8 deletions invokeai/app/invocations/cogview4_denoise.py
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Original file line number Diff line number Diff line change
Expand Up @@ -158,15 +158,14 @@ def _prepare_cfg_scale(self, num_timesteps: int) -> list[float]:
Returns:
list[float]: _description_
"""
if isinstance(self.cfg_scale, float):
cfg_scale = [self.cfg_scale] * num_timesteps
elif isinstance(self.cfg_scale, list):
assert len(self.cfg_scale) == num_timesteps
cfg_scale = self.cfg_scale
cfg_scale = self.cfg_scale
if type(cfg_scale) is float:
return [cfg_scale] * num_timesteps
elif type(cfg_scale) is list:
assert len(cfg_scale) == num_timesteps
return cfg_scale
else:
raise ValueError(f"Invalid CFG scale type: {type(self.cfg_scale)}")

return cfg_scale
raise ValueError(f"Invalid CFG scale type: {type(cfg_scale)}")

def _convert_timesteps_to_sigmas(self, image_seq_len: int, timesteps: torch.Tensor) -> list[float]:
# The logic to prepare the timestep / sigma schedule is based on:
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