Spaces:
Running
Running
File size: 2,477 Bytes
9d0d223 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 |
# @package __global__
# This is the training loop solver
# for the base audio-MAGNeT model (text-to-sound)
# on monophonic audio sampled at 16 kHz
# using a similar EnCodec+LM setup to MAGNeT
defaults:
- audiogen/default
- /model: lm/audiogen_lm
- override /dset: audio/default
- _self_
lm_model: transformer_lm_magnet
solver: audio_magnet
autocast: true
autocast_dtype: float16
# EnCodec large trained on mono-channel music audio sampled at 16khz
# with a total stride of 320 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: //reference/bd44a852/checkpoint.th
channels: 1
sample_rate: 16000
deadlock:
use: true # deadlock detection
dataset:
batch_size: 128 # matching AudioGen paper setup (256 * mix_p=0.5 = 128)
num_workers: 10
segment_duration: 10
min_segment_ratio: 1.0
sample_on_weight: false # Uniform sampling all the way
sample_on_duration: false # Uniform sampling all the way
external_metadata_source: null
# sample mixing augmentation at train time
train:
batch_size: 256 # matching AudioGen paper setup
aug_p: 0.5 # perform audio mixing 50% of the time
mix_p: 0.5 # proportion of batch items mixed together
# important: note that this will reduce the
# actual batch size used at train time
# which will be equal to mix_p * batch_size
mix_snr_low: -5
mix_snr_high: 5
mix_min_overlap: 0.5
optim:
epochs: 100
optimizer: adamw
lr: 5e-4
ema:
use: true
updates: 10
device: cuda
logging:
log_tensorboard: true
schedule:
lr_scheduler: inverse_sqrt
inverse_sqrt:
warmup: 3000
warmup_init_lr: 0.0
codebooks_pattern:
modeling: parallel
parallel:
empty_initial: -1
transformer_lm:
card: 2048
causal: false
subcodes_context: 5
compression_model_framerate: 50 # NOTE: Must match the actual frame rate of the used compression model
segment_duration: 0
span_len: -1
masking:
span_len: 3
generate:
lm:
max_prompt_len: null
max_gen_len: null
remove_prompts: false
use_sampling: true
temp: 3.5
top_k: 0
top_p: 0.8
max_cfg_coef: 20.0
min_cfg_coef: 1.0
decoding_steps: [20, 10, 10, 10]
anneal_temp: true
span_scoring: 'max'
span_arrangement: 'nonoverlap'
prompted_samples: false
samples:
prompted: false
unprompted: true
|