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Fix DDIM on Windows not using int64 for timesteps (#819)

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Hamish Friedlander 2022-10-18 23:06:46 +13:00 committed by GitHub
parent 728a3f3ec1
commit a3efa433ea
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1 changed files with 2 additions and 2 deletions
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src/diffusers/schedulers/scheduling_ddim.py
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@ -149,7 +149,7 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
# setable values
self.num_inference_steps = None
self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy())
self.timesteps = torch.from_numpy(np.arange(0, num_train_timesteps)[::-1].copy().astype(np.int64))
def scale_model_input(self, sample: torch.FloatTensor, timestep: Optional[int] = None) -> torch.FloatTensor:
"""
@ -192,7 +192,7 @@ class DDIMScheduler(SchedulerMixin, ConfigMixin):
step_ratio = self.config.num_train_timesteps // self.num_inference_steps
# creates integer timesteps by multiplying by ratio
# casting to int to avoid issues when num_inference_step is power of 3
timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy()
timesteps = (np.arange(0, num_inference_steps) * step_ratio).round()[::-1].copy().astype(np.int64)
self.timesteps = torch.from_numpy(timesteps).to(device)
self.timesteps += offset