'There is no checkpoint/model path. Use arg --cp-path to indicate the path!'
)
if os.path.isfile(args.out_path):
os.remove(args.out_path)
print(args.out_path + ' Removed')
if args.cuda:
device = get_freer_gpu()
if args.model_la == 'lstm':
model_la = model_.cnn_lstm()
elif args.model_la == 'resnet':
model_la = model_.ResNet()
elif args.model_la == 'resnet_pca':
model_la = model_.ResNet_pca()
elif args.model_la == 'lcnn_9':
model_la = model_.lcnn_9layers()
elif args.model_la == 'lcnn_29':
model_la = model_.lcnn_29layers_v2()
elif args.model_la == 'lcnn_9_pca':
model_la = model_.lcnn_9layers_pca()
elif args.model_la == 'lcnn_29_pca':
model_la = model_.lcnn_29layers_v2_pca()
elif args.model_la == 'lcnn_9_icqspec':
model_la = model_.lcnn_9layers_icqspec()
elif args.model_la == 'lcnn_9_prodspec':
model_la = model_.lcnn_9layers_prodspec()
elif args.model_la == 'lcnn_9_CC':
model_la = model_.lcnn_9layers_CC(ncoef=args.ncoef_la)
elif args.model_la == 'lcnn_29_CC':
max_nb_frames=args.n_frames,
n_cycles=args.valid_n_cycles)
valid_loader = torch.utils.data.DataLoader(
valid_dataset,
batch_size=args.valid_batch_size,
shuffle=False,
worker_init_fn=set_np_randomseed)
else:
valid_loader = None
if args.model == 'lstm':
model = model_.cnn_lstm(nclasses=args.n_classes)
elif args.model == 'resnet':
model = model_.ResNet(nclasses=args.n_classes)
elif args.model == 'resnet_pca':
model = model_.ResNet_pca(nclasses=args.n_classes)
elif args.model == 'lcnn_9':
model = model_.lcnn_9layers(nclasses=args.n_classes)
elif args.model == 'lcnn_29':
model = model_.lcnn_29layers_v2(nclasses=args.n_classes)
elif args.model == 'lcnn_9_pca':
model = model_.lcnn_9layers_pca(nclasses=args.n_classes)
elif args.model == 'lcnn_29_pca':
model = model_.lcnn_29layers_v2_pca(nclasses=args.n_classes)
elif args.model == 'lcnn_9_icqspec':
model = model_.lcnn_9layers_icqspec(nclasses=args.n_classes)
elif args.model == 'lcnn_9_prodspec':
model = model_.lcnn_9layers_prodspec(nclasses=args.n_classes)
elif args.model == 'lcnn_9_CC':
model = model_.lcnn_9layers_CC(nclasses=args.n_classes,
ncoef=args.ncoef,
if os.path.isfile(args.out_path):
os.remove(args.out_path)
print(args.out_path + ' Removed')
print('Cuda Mode is: {}'.format(args.cuda))
print('Selected model is: {}'.format(args.model))
if args.cuda:
device = get_freer_gpu()
if args.model == 'lstm':
model = model_.cnn_lstm()
elif args.model == 'resnet':
model = model_.ResNet()
elif args.model == 'resnet_pca':
model = model_.ResNet_pca()
elif args.model == 'lcnn_9':
model = model_.lcnn_9layers()
elif args.model == 'lcnn_29':
model = model_.lcnn_29layers_v2()
elif args.model == 'lcnn_9_pca':
model = model_.lcnn_9layers_pca()
elif args.model == 'lcnn_29_pca':
model = model_.lcnn_29layers_v2_pca()
elif args.model == 'lcnn_9_icqspec':
model = model_.lcnn_9layers_icqspec()
elif args.model == 'lcnn_9_prodspec':
model = model_.lcnn_9layers_prodspec()
elif args.model == 'lcnn_9_CC':
model = model_.lcnn_9layers_CC(ncoef=args.ncoef,
init_coef=args.init_coef)
