univi.TrainingConfig

class univi.TrainingConfig(n_epochs: 'int' = 200, batch_size: 'int' = 256, lr: 'float' = 0.001, weight_decay: 'float' = 0.0, device: 'str' = 'cpu', log_every: 'int' = 10, grad_clip: 'Optional[float]' = None, num_workers: 'int' = 0, seed: 'int' = 0, early_stopping: 'bool' = False, patience: 'int' = 20, min_delta: 'float' = 0.0, best_epoch_warmup: 'int' = 0)

Bases: object

__init__(n_epochs=200, batch_size=256, lr=0.001, weight_decay=0.0, device='cpu', log_every=10, grad_clip=None, num_workers=0, seed=0, early_stopping=False, patience=20, min_delta=0.0, best_epoch_warmup=0)

Methods

__init__([n_epochs, batch_size, lr, ...])

Attributes

batch_size
best_epoch_warmup
device
early_stopping
grad_clip
log_every
lr
min_delta
n_epochs
num_workers
patience
seed
weight_decay