huggingface / diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
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stabilityai/stable-diffusion-2-base DDIM config is not compatible with current DDIM implementation #7217

Open Zeqiang-Lai opened 6 months ago

Zeqiang-Lai commented 6 months ago

Describe the bug

Assume 30 inference steps.

There are two 925, and the number of inference steps is 31. tensor([958, 925, 925, 892, 859, 826, 793, 760, 727, 694, 661, 628, 595, 562, 529, 496, 463, 430, 397, 364, 331, 298, 265, 232, 199, 166, 133, 100, 67, 34, 1], device='cuda:0')

{
  "_class_name": "DDIMScheduler",
  "_diffusers_version": "0.8.0",
  "beta_end": 0.012,
  "beta_schedule": "scaled_linear",
  "beta_start": 0.00085,
  "clip_sample": false,
  "num_train_timesteps": 1000,
  "set_alpha_to_one": false,
  "skip_prk_steps": true,
  "steps_offset": 1,
  "trained_betas": null
}

The correct one should be. tensor([958, 925, 892, 859, 826, 793, 760, 727, 694, 661, 628, 595, 562, 529, 496, 463, 430, 397, 364, 331, 298, 265, 232, 199, 166, 133, 100, 67, 34, 1], device='cuda:0')


{
  "_class_name": "DDIMScheduler",
  "_diffusers_version": "0.25.0",
  "beta_end": 0.012,
  "beta_schedule": "scaled_linear",
  "beta_start": 0.00085,
  "clip_sample": false,
  "clip_sample_range": 1.0,
  "dynamic_thresholding_ratio": 0.995,
  "num_train_timesteps": 1000,
  "prediction_type": "epsilon",
  "rescale_betas_zero_snr": false,
  "sample_max_value": 1.0,
  "set_alpha_to_one": false,
  "steps_offset": 1,
  "thresholding": false,
  "timestep_spacing": "leading",
  "trained_betas": null
}

Reproduction

See above

Logs

No response

System Info

Version: 0.26.3

Who can help?

No response

sayakpaul commented 6 months ago

Cc: @yiyixuxu

yiyixuxu commented 6 months ago

can you share a reproducible script?

github-actions[bot] commented 5 months ago

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