def create_model_miniimagenet(args, config, architecture, ENCODER_CONFIG=None):
# Create Model
if args.model == "MAML" or args.model == "MetaSGD":
# Meta SGD or MAML
if config['is_meta_sgd']:
model = MetaSGD(architecture,
config['update_lr'],
config['update_step'],
is_regression=False)
else:
model = Meta(architecture,
config['update_lr'],
config['update_step'],
is_regression=False)
elif args.model == "LEO":
model = LEO(config)
elif args.model == "MLwM":
model = MLwM(ENCODER_CONFIG, architecture, config['update_lr'], config['update_step'],\
is_regression=False)
else:
NotImplementedError
return model
def create_model_embed_miniimagenet(args,
config,
architecture,
ENCODER_CONFIG=None):
if args.model == "MAML" or args.model == "MetaSGD":
# Meta SGD or MAML
if config['is_meta_sgd']:
model = MetaSGD(architecture,
config['update_lr'],
config['update_step'],
is_regression=False,
is_image_feature=False)
else:
model = Meta(architecture,
config['update_lr'],
config['update_step'],
is_regression=False,
is_image_feature=False)
elif args.model == "LEO":
model = LEO(config)
elif args.model == "SIB":
model = SIB(args.n_way, config)
elif args.model == "Prototypes_embedded":
model = PrototypeNet_embedded(args.n_way, config)
elif args.model == "MLwM":
# MLwM with MAML or MetaSGD
model = MLwM(ENCODER_CONFIG, architecture, config['update_lr'], config['update_step'],\
is_regression=False)
else:
NotImplementedError
return model
def create_model_poseregression(args,
config,
architecture,
ENCODER_CONFIG=None):
# Create Model
if args.model == "MAML" or args.model == "MetaSGD":
# Meta SGD or MAML
if config['is_meta_sgd']:
model = MetaSGD(architecture,
config['update_lr'],
config['update_step'],
is_regression=True)
else:
model = Meta(architecture,
config['update_lr'],
config['update_step'],
is_regression=True)
elif args.model == "MLwM":
model = MLwM(config, architecture, config['update_lr'], config['update_step'],\
is_regression=True)
elif args.model == "CNP":
model = CNP(config, is_regression=True)
else:
NotImplementedError
return model
encoded_img_size,
is_regression=True)
else:
architecture = set_config(config['CONFIG_CONV_4_MAML'],
args.n_way,
config['img_size'],
is_regression=True)
# Create Model
if args.model == "MAML":
model = Meta(architecture,
config['update_lr'],
config['update_step'],
is_regression=True)
elif args.model == "MLwM":
model = MLwM(ENCODER_CONFIG, architecture, config['update_lr'], config['update_step'],\
is_regression=True, is_kl_loss=True, beta_kl=config['beta_kl'])
else:
NotImplementedError
# Train
train(model, config, save_model_path)
# load model path
if args.model_save_root_dir == args.model_load_dir:
load_model_path = latest_load_model_filepath(args)
else:
load_model_path = args.model_load_dir
# Test
test(model, load_model_path, save_model_path)