def main(args):
device = torch.device('cuda' if args.use_cuda else 'cpu')
args.sample_rate = {
'8k':8000,
'16k':16000,
'24k':24000,
'48k':48000,
}[args.sample_rate]
model = Model(
left_context=args.left_context,
right_context=args.right_context,
hidden_layers=args.rnn_layers,
hidden_units=args.rnn_units,
input_dim=args.input_dim,
output_dim=args.output_dim,
kernel_size=args.kernel_size,
kernel_num=args.kernel_num,
dropout=args.dropout)
if not args.log_dir:
writer = SummaryWriter(os.path.join(args.exp_dir, 'tensorboard'))
else:
writer = SummaryWriter(args.log_dir)
model.to(device)
if not args.decode:
train(model, FLAGS, device, writer)
reload_for_eval(model, FLAGS.exp_dir, FLAGS.use_cuda)
decode(model, args, device)
def main(args):
device = torch.device('cuda' if args.use_cuda else 'cpu')
args.sample_rate = {
'8k': 8000,
'16k': 16000,
'24k': 24000,
'48k': 48000,
}[args.sample_rate]
model = Model(
rnn_layers=args.rnn_layers,
rnn_units=args.rnn_units,
win_len=args.win_len,
win_inc=args.win_inc,
fft_len=args.fft_len,
win_type=args.win_type,
mode=args.target_mode,
)
if not args.log_dir:
writer = SummaryWriter(os.path.join(args.exp_dir, 'tensorboard'))
else:
writer = SummaryWriter(args.log_dir)
model.to(device)
if not args.decode:
train(model, FLAGS, device, writer)
reload_for_eval(model, FLAGS.exp_dir, FLAGS.use_cuda)
decode(model, args, device)
def main(args):
device = torch.device('cuda' if args.use_cuda else 'cpu')
args.sample_rate = {
'8k': 8000,
'16k': 16000,
'24k': 24000,
'48k': 48000,
}[args.sample_rate]
model = Model(overallspks=105, )
if not args.log_dir:
writer = SummaryWriter(os.path.join(args.exp_dir, 'tensorboard'))
else:
writer = SummaryWriter(args.log_dir)
model.to(device)
if not args.decode:
train(model, FLAGS, device, writer)
reload_for_eval(model, FLAGS.exp_dir, FLAGS.use_cuda)
decode(model, args, device)