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# @package __global__
# This is the training loop solver
# for the base MusicGen model (text-to-music)
# on monophonic audio sampled at 32 kHz
defaults:
- musicgen/default
- /model: lm/musicgen_lm
- override /dset: audio/default
- _self_
autocast: true
autocast_dtype: float16
# EnCodec large trained on mono-channel music audio sampled at 32khz
# with a total stride of 640 leading to 50 frames/s.
# rvq.n_q=4, rvq.bins=2048, no quantization dropout
# (transformer_lm card and n_q must be compatible)
compression_model_checkpoint: //pretrained/facebook/encodec_32khz
channels: 1
sample_rate: 32000
deadlock:
use: true # deadlock detection
dataset:
batch_size: 192 # 32 GPUs
sample_on_weight: false # Uniform sampling all the way
sample_on_duration: false # Uniform sampling all the way
generate:
lm:
use_sampling: true
top_k: 250
top_p: 0.0
optim:
epochs: 500
optimizer: dadam
lr: 1
ema:
use: true
updates: 10
device: cuda
logging:
log_tensorboard: true
schedule:
lr_scheduler: cosine
cosine:
warmup: 4000
lr_min_ratio: 0.0
cycle_length: 1.0
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