tensor([[ 0, 0, 0,
..., 0, 0,
0],
[ 0, 133148282176512, 0,
..., 0, 544373700175071744,
3978033069303296],
[283817417514181632, 4470614405284095, 4470614278539776,
..., 96757024170496, 4472813428539647,
4636747909554688],
...,
[ 62998, 1757, 3143,
..., 23576, 34277,
37654],
[ 62999, 13636, 20836,
..., 28260, 33679,
59455],
[ 63000, 61593, 54526,
..., 10903, 60347,
57793]], device='cuda:0')
gpu_id=0
use_gpu=True
seed=[999]
data_path=../data/
inter_splitting_label=x_label
filter_out_cod_start_users=True
is_multimodal_model=True
checkpoint_dir=saved
save_recommended_topk=True
recommend_topk=recommend_topk/
embedding_size=64
weight_decay=0.0
req_training=True
epochs=1000
stopping_step=20
train_batch_size=2048
learner=adam
learning_rate=[0.001]
learning_rate_scheduler=[1.0, 50]
eval_step=1
training_neg_sample_num=1
use_neg_sampling=True
use_full_sampling=False
NEG_PREFIX=neg__
USER_ID_FIELD=userID
ITEM_ID_FIELD=itemID
TIME_FIELD=timestamp
field_separator=
metrics=['Recall', 'NDCG', 'Precision', 'MAP']
topk=[5, 10, 20, 50]
valid_metric=Recall@20
eval_batch_size=4096
use_raw_features=False
max_txt_len=32
max_img_size=256
vocab_size=30522
type_vocab_size=2
hidden_size=4
pad_token_id=0
max_position_embeddings=512
layer_norm_eps=1e-12
hidden_dropout_prob=0.1
end2end=False
hyper_parameters=['aggr_mode', 'reg_weight', 'learning_rate', 'seed']
inter_file_name=elec.inter
vision_feature_file=image_feat.npy
text_feature_file=text_feat.npy
user_graph_dict_file=user_graph_dict.npy
feat_embed_dim=64
n_mm_layers=1
n_layers=2
knn_k=10
mm_image_weight=0.1
aggr_mode=['add']
reg_weight=[0.0001]
info=normal-seed_None
model=DRAGON
dataset=elec
valid_metric_bigger=True
device=cuda
19 Jul 16:13 INFO elec
The number of users: 192403
Average actions of users: 8.779426516218562
The number of items: 63001
Average actions of items: 26.81208234789924
The number of inters: 1689188
The sparsity of the dataset: 99.98606462355167%
19 Jul 16:13 INFO
====Training====
elec
The number of users: 192403
Average actions of users: 6.519861956414401
The number of items: 62989
Average actions of items: 19.91523916874375
The number of inters: 1254441
The sparsity of the dataset: 99.98964920548602%
19 Jul 16:13 INFO
====Validation====
elec
The number of users: 192403
Average actions of users: 1.098194934590417
The number of items: 47923
Average actions of items: 4.4090728877574445
The number of inters: 211296
The sparsity of the dataset: 99.99770841780649%
19 Jul 16:13 INFO
====Testing====
elec
The number of users: 192403
Average actions of users: 1.161369625213744
The number of items: 48794
Average actions of items: 4.57947698487519
The number of inters: 223451
The sparsity of the dataset: 99.99761985156943%
19 Jul 16:14 INFO
=================================
19 Jul 16:14 INFO =========1/1: Parameters:['aggr_mode', 'reg_weight', 'learning_rate', 'seed']=('add', 0.0001, 0.001, 999)=======
Traceback (most recent call last):
File "main.py", line 34, in <module>
quick_start(model=args.model, dataset=args.dataset, config_dict=config_dict, save_model=True, seed=args.seed, alpha1=args.alpha1, alpha2=args.alpha2, eta=args.eta, estart=args.estart, alter=True if 'alter' in args.info else False)
File "xxx/MMRec/src/utils/quick_start.py", line 77, in quick_start
model = get_model(config['model'])(config, train_data).to(config['device'])
File "xxx/MMRec/src/models/dragon.py", line 75, in __init__
indices, image_adj = self.get_knn_adj_mat(self.image_embedding.weight.detach())
File "xxx/MMRec/src/models/dragon.py", line 173, in get_knn_adj_mat
return indices, self.compute_normalized_laplacian(indices, adj_size)
File "xxx/MMRec/src/models/dragon.py", line 176, in compute_normalized_laplacian
adj = torch.sparse.FloatTensor(indices, torch.ones_like(indices[0]), adj_size)
RuntimeError: found negative index -562949566989948 for dim 1