def load_model(logger, args, n_entities, n_relations, ckpt=None):
model = KEModel(args,
args.model_name,
n_entities,
n_relations,
args.hidden_dim,
args.gamma,
double_entity_emb=args.double_ent,
double_relation_emb=args.double_rel)
if ckpt is not None:
# TODO: loading model emb only work for genernal Embedding, not for ExternalEmbedding
model.load_state_dict(ckpt['model_state_dict'])
return model
def load_model(logger, args, n_entities, n_relations, ckpt=None):
model = KEModel(args, args.model_name, n_entities, n_relations,
args.hidden_dim, args.gamma,
double_entity_emb=args.double_ent, double_relation_emb=args.double_rel)
if ckpt is not None:
assert False, "We do not support loading model emb for genernal Embedding"
return model
def load_model(logger, args, n_entities, n_relations, ckpt=None):
model = KEModel(args, args.model_name, n_entities, n_relations,
args.hidden_dim, args.gamma,
double_entity_emb=args.double_ent, double_relation_emb=args.double_rel)
if ckpt is not None:
# TODO: loading model emb only work for genernal Embedding, not for ExternalEmbedding
if args.gpu >= 0:
model.load_parameters(ckpt, ctx=mx.gpu(args.gpu))
else:
model.load_parameters(ckpt, ctx=mx.cpu())
logger.info('Load model {}'.format(args.model_name))
return model
