from torch.utils.tensorboard import SummaryWriter
summary_name = '{}s2s-e{}d{}h{}'.format(args.tensorboard_dir,
args.n_enc, args.n_dec,
args.n_head)
if args.use_cnn:
summary_name += 'cnn'
tensorboard_writer = SummaryWriter(summary_name)
cfg = {
'model_path': args.model_path,
'lr': args.lr,
'label_smooth': args.label_smooth,
'weight_decay': args.weight_decay,
'teacher_force': args.teacher_force,
'n_warmup': args.n_warmup,
'n_const': args.n_const,
'b_input': args.b_input,
'b_update': args.b_update,
'n_print': args.n_print
}
datasets = (tr_reader, cv_reader)
train_model(model,
datasets,
args.n_epoch,
device,
cfg,
loss_norm=args.loss_norm,
grad_norm=args.grad_norm,
fp16=args.fp16,
tensorboard_writer=tensorboard_writer)
time_win=args.time_win)
cv_reader = ScpStreamReader(args.valid_scp,
args.valid_target,
downsample=args.downsample,
mean_sub=args.mean_sub,
max_len=args.max_len,
max_utt=args.max_utt,
fp16=args.fp16)
cfg = {
'model_path': args.model_path,
'lr': args.lr,
'label_smooth': args.label_smooth,
'weight_decay': args.weight_decay,
'teacher_force': args.teacher_force,
'n_warmup': args.n_warmup,
'n_const': args.n_const,
'b_input': args.b_input,
'b_update': args.b_update,
'n_print': args.n_print
}
datasets = (tr_reader, cv_reader)
train_model(model,
datasets,
args.n_epoch,
device,
cfg,
loss_norm=args.loss_norm,
grad_norm=args.grad_norm,
fp16=args.fp16)