archinetai/audio-diffusion-pytorch-trainer

Error Locating Target

ModeratePrawn opened this issue ยท 3 comments

Hello,

I upgraded the trainer and audio diffusion to the latest releases. I am now getting this error when trying to run experiments:

[2022-10-19 09:47:41,538][main][INFO] - Instantiating model <main.module_base.Model>.
Error executing job with overrides: ['exp=base_youtube_l_3.yaml']
Error locating target 'audio_diffusion_pytorch.VDistribution', see chained exception above.
full_key: model.model.diffusion_sigma_distribution

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.

I deleted the conda environment and reinstalled all of the requirements from scratch, and I am still getting the above. Any help would be appreciated.

Thanks,
MP

You have to use diffusion_type='vk' with audio_diffusion_pytorch.VKDistribution, I still have to delete those old experiments that are not up to date

The old experiments have been archived and the new updated, you should be able to run the current version.

Seems to be working now! Thank you!

[2022-10-19 12:41:18,081][main][INFO] - Logging hyperparameters!
[2022-10-19 12:41:18,122][main][INFO] - Starting training.
โ”โ”โ”โ”โ”ณโ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”ณโ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”ณโ”โ”โ”โ”โ”โ”โ”โ”โ”“
โ”ƒ โ”ƒ Name โ”ƒ Type โ”ƒ Params โ”ƒ
โ”กโ”โ”โ”โ•‡โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ•‡โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ”โ•‡โ”โ”โ”โ”โ”โ”โ”โ”โ”ฉ
โ”‚ 0 โ”‚ model โ”‚ AudioDiffusionModel โ”‚ 640 M โ”‚
โ”‚ 1 โ”‚ model.unet โ”‚ UNet1d โ”‚ 640 M โ”‚
โ”‚ 2 โ”‚ model.diffusion โ”‚ VDiffusion โ”‚ 640 M โ”‚
โ”‚ 3 โ”‚ model_ema โ”‚ EMA โ”‚ 1.3 B โ”‚
โ”‚ 4 โ”‚ model_ema.ema_model โ”‚ AudioDiffusionModel โ”‚ 640 M โ”‚
โ””โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
Trainable params: 640 M
Non-trainable params: 640 M
Total params: 1.3 B
Total estimated model params size (MB): 5.1 K