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defaults: | |
- _self_ | |
- model: null | |
- effects: null | |
seed: 12345 | |
train: True | |
sample_rate: 48000 | |
logs_dir: "./logs" | |
log_every_n_steps: 1000 | |
render_files: True | |
callbacks: | |
model_checkpoint: | |
_target_: pytorch_lightning.callbacks.ModelCheckpoint | |
monitor: "valid_loss" # name of the logged metric which determines when model is improving | |
save_top_k: 1 # save k best models (determined by above metric) | |
save_last: True # additionaly always save model from last epoch | |
mode: "min" # can be "max" or "min" | |
verbose: False | |
dirpath: ${logs_dir}/ckpts/${now:%Y-%m-%d-%H-%M-%S} | |
filename: '{epoch:02d}-{valid_loss:.3f}' | |
datamodule: | |
_target_: remfx.datasets.VocalSetDatamodule | |
train_dataset: | |
_target_: remfx.datasets.VocalSet | |
sample_rate: ${sample_rate} | |
root: ${oc.env:DATASET_ROOT} | |
chunk_size_in_sec: 6 | |
mode: "train" | |
effect_types: ${effects.train_effects} | |
render_files: ${render_files} | |
val_dataset: | |
_target_: remfx.datasets.VocalSet | |
sample_rate: ${sample_rate} | |
root: ${oc.env:DATASET_ROOT} | |
chunk_size_in_sec: 6 | |
mode: "val" | |
effect_types: ${effects.val_effects} | |
render_files: ${render_files} | |
test_dataset: | |
_target_: remfx.datasets.VocalSet | |
sample_rate: ${sample_rate} | |
root: ${oc.env:DATASET_ROOT} | |
chunk_size_in_sec: 6 | |
mode: "test" | |
effect_types: ${effects.val_effects} | |
render_files: ${render_files} | |
batch_size: 16 | |
num_workers: 8 | |
pin_memory: True | |
persistent_workers: True | |
logger: | |
_target_: pytorch_lightning.loggers.WandbLogger | |
project: ${oc.env:WANDB_PROJECT} | |
entity: ${oc.env:WANDB_ENTITY} | |
# offline: False # set True to store all logs only locally | |
job_type: "train" | |
group: "" | |
save_dir: "." | |
trainer: | |
_target_: pytorch_lightning.Trainer | |
precision: 32 # Precision used for tensors, default `32` | |
min_epochs: 0 | |
max_epochs: -1 | |
enable_model_summary: False | |
log_every_n_steps: 1 # Logs metrics every N batches | |
accumulate_grad_batches: 1 | |
accelerator: null | |
devices: 1 | |