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[lavender-flow] use flow match euler scheduler #8799
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
@@ -428,13 +429,14 @@ def __call__( | |||
prompt_embeds = torch.cat([negative_prompt_embeds, prompt_embeds], dim=0) | |||
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# 4. Prepare timesteps | |||
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sigmas = np.linspace(1.0, 1 / num_inference_steps, num_inference_steps) |
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I added this just to get 1:1 with the original implementation, I don't think it's needed here, the difference should be very small, but I didn't test for smaller number of steps
cc @cloneofsimo
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Thanks. Just a single comment.
torch.tensor([t / 1000]) | ||
.expand(latent_model_input.shape[0]) | ||
.to(latents.device, dtype=latents.dtype) |
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We could unpack this code a bit and perhaps add a comment on why we're dividing by 1000. This is mainly because we're moving away from our normal pipeline implementations a bit which our users are used to reading and referring to.
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done! feel free to merge into your PR now
Thanks a lot for your help, Yiyi! |
part of #8796
you can use this to test once this PR is fixed #8798