espnet.asr.pytorch_backend.asr.CustomUpdater

source

class espnet.asr.pytorch_backend.asr.CustomUpdater(model, grad_clip_threshold, train_iter, optimizer, device, ngpu, grad_noise=False, accum_grad=1, use_apex=False, use_ddp=False)

Bases: StandardUpdater

Custom Updater for Pytorch.

• Parameters:
  • model (torch.nn.Module) – The model to update.
  • grad_clip_threshold (float) – The gradient clipping value to use.
  • train_iter (chainer.dataset.Iterator) – The training iterator.
  • optimizer (torch.optim.optimizer) – The training optimizer.
  • device (torch.device) – The device to use.
  • ngpu (int) – The number of gpus to use.
  • use_apex (bool) – The flag to use Apex in backprop.
  • use_ddp (bool) – The flag to use DDP for multi-GPU training.

Initliaze Custom Updater.

update()

Update Method.

update_core()

Update routine of the CustomUpdater (main).