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Sleeping
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defaults:
- _self_
- exp: null
seed: 12345
train: True
length: 262144
sample_rate: 48000
logs_dir: "./logs"
log_every_n_steps: 1000
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.Datamodule
dataset:
_target_: remfx.datasets.GuitarFXDataset
sample_rate: ${sample_rate}
root: ${oc.env:DATASET_ROOT}
length: ${length}
chunk_size_in_sec: 3
num_chunks: 10
val_split: 0.2
batch_size: 16
num_workers: 8
pin_memory: 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
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