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| # @package __global__ | |
| defaults: | |
| - /solver/default | |
| - /model: score/basic | |
| - override /dset: audio/default | |
| - _self_ | |
| solver: diffusion | |
| sample_rate: ??? | |
| channels: ??? | |
| compression_model_checkpoint: ??? | |
| n_q: ??? # number of codebooks to keep | |
| dataset: | |
| batch_size: 128 | |
| num_workers: 10 | |
| segment_duration: 1 | |
| train: | |
| num_samples: 500000 | |
| valid: | |
| num_samples: 10000 | |
| evaluate: | |
| batch_size: 16 | |
| num_samples: 10000 | |
| generate: | |
| batch_size: 32 | |
| num_samples: 50 | |
| segment_duration: 10 | |
| audio: | |
| sample_rate: ${sample_rate} | |
| loss: | |
| kind: mse | |
| norm_power: 0. | |
| valid: | |
| every: 1 | |
| evaluate: | |
| every: 20 | |
| num_workers: 5 | |
| metrics: | |
| visqol: false | |
| sisnr: false | |
| rvm: true | |
| generate: | |
| every: 25 | |
| num_workers: 5 | |
| checkpoint: | |
| save_last: true | |
| save_every: 25 | |
| keep_last: 10 | |
| keep_every_states: null | |
| optim: | |
| epochs: 20000 | |
| updates_per_epoch: 2000 | |
| lr: 2e-4 | |
| max_norm: 0 | |
| optimizer: adam | |
| adam: | |
| betas: [0.9, 0.999] | |
| weight_decay: 0. | |
| ema: | |
| use: true # whether to use EMA or not | |
| updates: 1 # update at every step | |
| device: ${device} # device for EMA, can be put on GPU if more frequent updates | |
| decay: 0.99 # EMA decay value, if null, no EMA is used | |
| processor: | |
| name: multi_band_processor | |
| use: false | |
| n_bands: 8 | |
| num_samples: 10_000 | |
| power_std: 1. | |
| resampling: | |
| use: false | |
| target_sr: 16000 | |
| filter: | |
| use: false | |
| n_bands: 4 | |
| idx_band: 0 | |
| cutoffs: null | |
| schedule: | |
| repartition: "power" | |
| variable_step_batch: true | |
| beta_t0: 1.0e-5 | |
| beta_t1: 2.9e-2 | |
| beta_exp: 7.5 | |
| num_steps: 1000 | |
| variance: 'beta' | |
| clip: 5. | |
| rescale: 1. | |
| n_bands: null | |
| noise_scale: 1.0 | |
| metrics: | |
| num_stage: 4 | |