processor package¶
Submodules¶
processor.processor module¶
- processor.processor.do_inference(cfg, model, val_loader, num_query)¶
- processor.processor.do_train(cfg, model, center_criterion, train_loader, val_loader, optimizer, optimizer_center, scheduler, loss_fn, num_query)¶
- Args:
training function inputs
cfg: configuration file, passed from /config/configs.py or /default.py
model: initialized deep model
center_criterion: could be enabled if using center loss, implemented for further updating
train_loader: training dataloader
val_loader: validation dataloader
optimizer: SGD or ADAM optimizer
optimizer_center: SGD or ADAM optimizer for center loss
scheduler: updating scheduler
loss_fn: loss function for learning
num_query: number of learning samples
Returns:
processor.processor_bk module¶
- processor.processor_bk.do_inference(cfg, model, val_loader, num_query)¶
- processor.processor_bk.do_train(cfg, model, center_criterion, train_loader, val_loader, optimizer, optimizer_center, scheduler, loss_fn, num_query)¶