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Make tqdm calls notebook-compatible - follow-up

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anton-l
2022-07-18 18:43:18 +02:00
parent 1820024005
commit 36b459f6e6
2 changed files with 2 additions and 2 deletions
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2
src/diffusers/pipelines/glide/pipeline_glide.py
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@@ -817,7 +817,7 @@ class GlidePipeline(DiffusionPipeline):
num_trained_timesteps = self.upscale_scheduler.timesteps
inference_step_times = range(0, num_trained_timesteps, num_trained_timesteps // num_inference_steps_upscale)
for t in tqdm.tqdm(reversed(range(num_inference_steps_upscale)), total=num_inference_steps_upscale):
for t in tqdm(reversed(range(num_inference_steps_upscale)), total=num_inference_steps_upscale):
# 1. predict noise residual
with torch.no_grad():
time_input = torch.tensor([inference_step_times[t]] * image.shape[0], device=torch_device)

2
src/diffusers/pipelines/pndm/pipeline_pndm.py
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@@ -53,7 +53,7 @@ class PNDMPipeline(DiffusionPipeline):
image = self.scheduler.step_prk(model_output, t, image, num_inference_steps)["prev_sample"]
timesteps = self.scheduler.get_time_steps(num_inference_steps)
for t in tqdm.tqdm(range(len(timesteps))):
for t in tqdm(range(len(timesteps))):
t_orig = timesteps[t]
model_output = self.unet(image, t_orig)