MelodyFlow / audiocraft /grids /musicgen /musicgen_stereo_finetune_32khz.py
Gael Le Lan
Initial commit
9d0d223
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from pathlib import Path
from ._explorers import LMExplorer
from ...environment import AudioCraftEnvironment
@LMExplorer
def explorer(launcher):
partitions = AudioCraftEnvironment.get_slurm_partitions(['team', 'global'])
launcher.slurm_(gpus=32, partition=partitions)
launcher.bind_(solver='musicgen/musicgen_base_32khz')
# replace this by the desired music dataset, which needs to be stereo
launcher.bind_(dset='audio/example')
fsdp = {'autocast': False, 'fsdp.use': True}
medium = {'model/lm/model_scale': 'medium'}
large = {'model/lm/model_scale': 'large'}
cfg_low = {'classifier_free_guidance.training_dropout': 0.2}
wd_low = {'conditioners.description.t5.word_dropout': 0.2}
adam = {'optim.optimizer': 'adamw', 'optim.lr': 1e-4}
stereo = {
'codebooks_pattern.delay.delays': [0, 0, 1, 1, 2, 2, 3, 3],
'transformer_lm.n_q': 8,
'interleave_stereo_codebooks.use': True,
'channels': 2,
}
# You must follow the instructions in docs/MUSICGEN.md about the creation
# of the proper fine tuning checkpoints. We will assume they are stored under
# ~/checkpoints/{mode_name}.
checkpoints = Path.home() / 'checkpoints'
launcher.bind_(fsdp, stereo, {'optim.epochs': 100})
launcher.slurm_(gpus=32).bind_(label='32gpus')
with launcher.job_array():
sub = launcher.bind({'continue_from': str(checkpoints / 'stereo_finetune_musicgen-small.th')})
sub()
launcher.slurm_(gpus=64).bind_(label='64gpus')
with launcher.job_array():
sub = launcher.bind({'continue_from': str(checkpoints / 'stereo_finetune_musicgen-medium.th')})
sub(medium, adam)
launcher.slurm_(gpus=96).bind_(label='96gpus')
with launcher.job_array():
sub = launcher.bind({'continue_from': str(checkpoints / 'stereo_finetune_musicgen-large.th')})
sub(large, cfg_low, wd_low, adam, {'optim.max_norm': 3})