0a8e27413d721bf8d753e5e6061cc24f5bf6474f,train.py,,__train_step,#,600

Before Change

            writer.add_scalar("gradient norm", grad_norm, step)
        writer.add_scalar("learning rate", current_lr, step)

    return loss.data[0]


def train_loop(model, data_loaders, optimizer, writer, checkpoint_dir=None):
    if use_cuda:

After Change

            writer.add_scalar("gradient norm", grad_norm, step)
        writer.add_scalar("learning rate", current_lr, step)

    return loss.item()


def train_loop(device, model, data_loaders, optimizer, writer, checkpoint_dir=None):
    if is_mulaw_quantize(hparams.input_type):

Instances