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# lightning.pytorch==2.2.5
seed_everything: 0
trainer:
accelerator: gpu
strategy: ddp_find_unused_parameters_true
devices: 8
num_nodes: 1
precision: 32
logger:
class_path: lightning.pytorch.loggers.WandbLogger
init_args:
name: mel_big
save_dir: vq_audio_simvq_bert_mel/8k_ration_20_loss
version: null
offline: false
dir: null
id: null
anonymous: null
project: endresult_tmp
log_model: false
experiment: null
prefix: ''
checkpoint_name: null
job_type: null
config: null
entity: null
reinit: null
tags: null
group: null
notes: null
magic: null
config_exclude_keys: null
config_include_keys: null
mode: null
allow_val_change: null
resume: null
force: null
tensorboard: null
sync_tensorboard: null
monitor_gym: null
save_code: null
fork_from: null
resume_from: null
settings: null
callbacks:
- class_path: lightning.pytorch.callbacks.ModelCheckpoint
init_args:
dirpath: vq_audio_simvq_bert_mel/8k_ration_20_loss
filename: null
monitor: null
verbose: false
save_last: null
save_top_k: -1
save_weights_only: false
mode: min
auto_insert_metric_name: true
every_n_train_steps: null
train_time_interval: null
every_n_epochs: null
save_on_train_epoch_end: null
enable_version_counter: true
- class_path: lightning.pytorch.callbacks.LearningRateMonitor
init_args:
logging_interval: step
log_momentum: false
log_weight_decay: false
fast_dev_run: false
max_epochs: 50
min_epochs: null
max_steps: -1
min_steps: null
max_time: null
limit_train_batches: null
limit_val_batches: null
limit_test_batches: null
limit_predict_batches: null
overfit_batches: 0.0
val_check_interval: null
check_val_every_n_epoch: 1
num_sanity_val_steps: 0
log_every_n_steps: 100
enable_checkpointing: null
enable_progress_bar: null
enable_model_summary: null
accumulate_grad_batches: 1
gradient_clip_val: null
gradient_clip_algorithm: null
deterministic: null
benchmark: null
inference_mode: true
use_distributed_sampler: true
profiler: null
detect_anomaly: false
barebones: false
plugins: null
sync_batchnorm: false
reload_dataloaders_every_n_epochs: 0
default_root_dir: null
model:
class_path: taming.models.vq_audio_simvq_mel.VQModel
init_args:
ddconfig:
causal: true
dimension: 512
ratios:
- 8
- 8
- 4
- 4
lossconfig:
target: taming.modules.losses.stft_simvq_mel.VQSTFTWithDiscriminator
params:
disc_conditional: false
disc_in_channels: 1
disc_start: 0
codebook_enlarge_ratio: 0
codebook_enlarge_steps: 2000
sample_rate: 24000
commit_weight: 1000.0
gen_loss_weight: 1.0
mel_loss_coeff: 45.0
mrd_loss_coeff: 1.0
quantconfig: null
sample_rate: 24000
target_bandwidths: null
audio_normalize: false
segment: None
ckpt_path: null
ignore_keys: []
colorize_nlabels: null
monitor: null
learning_rate: 0.0001
warmup_epochs: 1.0
scheduler_type: None
min_learning_rate: 0
use_ema: true
stage: null
data:
class_path: taming.data.speechtokenizer_24k.SpeechTokenizerDataModule
init_args:
batch_size: 6
num_workers: 8
train_path:
- /mnt/nfs3/zhangjinouwen/dataset/rep/rep_small_mel_hubert_train.txt
- /mnt/nfs3/zhangjinouwen/dataset/rep/rep_middle_mel_hubert_train.txt
- /mnt/nfs3/zhangjinouwen/dataset/rep/rep_Emila1_mel_hubert_train.txt
- /mnt/nfs3/zhangjinouwen/dataset/rep/rep_vc_mel_hubert_train.txt
val_path: /mnt/nfs3/zhangjinouwen/dataset/rep/rep_small_wav_eval.txt
optimizer: null
lr_scheduler: null
ckpt_path: null
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