[Dataset] make rgcn compatible with the latest version of numpy

examples/agnn/agnn_trainer.py

@@ -7,7 +7,10 @@
 """
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/appnp/appnp_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/cagcn/cagcn_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/chebnet/chebnet_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/cogsl/cogsl_trainer.py

@@ -1,6 +1,9 @@
 import os
-# os.environ['CUDA_VISIBLE_DEVICES']='0'
-# os.environ['TL_BACKEND'] = 'paddle'
+# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 
 import sys
 import argparse

examples/compgcn/compgcn_trainer.py

@@ -6,7 +6,10 @@
 # @FileName: compgcn_trainer.py
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.models import CompGCN

examples/deepwalk/deepwalk_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/dgcnn/dgcnn_trainer.py

@@ -7,7 +7,10 @@
 """
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 import tensorlayerx.nn as nn

examples/dgi/dgi_trainer.py

@@ -1,7 +1,9 @@
-import math
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from gammagl.utils import add_self_loops, calc_gcn_norm, mask_to_index, remove_self_loops
 import argparse
 from tqdm import tqdm

examples/drgst/dr_gst.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import copy
 import numpy as np

examples/dropedge/dropedge_trainer.py

@@ -1,7 +1,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/fagcn/fagcn_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/film/film_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from tensorlayerx.model import TrainOneStep, WithLoss

examples/gaan/GaAN_trainer.py

@@ -6,15 +6,18 @@
 @Author  :   yunhe
 """
 
+import os
+# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from tensorlayerx.model import TrainOneStep, WithLoss
 from gammagl.utils import add_self_loops, mask_to_index
 from gammagl.models import GaANModel
 from gammagl.datasets import Planetoid
 import tensorlayerx as tlx
 import argparse
-import os
-# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
 
 class SemiSpvzLoss(WithLoss):
     def __init__(self, net, loss_fn):

examples/gat/gat_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/gatv2/gatv2_trainer.py

@@ -7,7 +7,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/gcn/gcn_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/gcnii/gcnii_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/gen/gen_trainer.py

@@ -1,9 +1,12 @@
 import os
+# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import time
 import argparse
 import numpy as np
-# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
 import tensorlayerx as tlx
 from gammagl.layers.conv import GCNConv
 from gammagl.datasets import Planetoid

examples/gin/gin.py

@@ -1,8 +1,11 @@
-
-import numpy
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
+
+import numpy
 import argparse
 import tensorlayerx as tlx
 from tensorlayerx.model import TrainOneStep, WithLoss

examples/gmm/gmm_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/gprgnn/gprgnn_trainer.py

@@ -1,7 +1,10 @@
 import os
-import os.path as osp
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
+import os.path as osp
 import argparse
 from tqdm import tqdm
 import numpy as np

examples/grace/grace_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from gammagl.utils import add_self_loops, calc_gcn_norm
 import argparse
 from tqdm import tqdm

examples/grade/grade_trainer.py

@@ -1,6 +1,10 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
+
 import tensorlayerx as tlx
 import argparse
 from gammagl.models.grade import GRADE

examples/graphgan/graphgan_trainer.py

@@ -3,7 +3,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from gammagl.models import GraphGAN
 from gammagl.utils import read_embeddings
 from gammagl.datasets import CA_GrQc

examples/graphsage/train_full.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from gammagl.models.graphsage import GraphSAGE_Full_Model
 import argparse
 import tensorlayerx as tlx

examples/han/han_trainer.py

@@ -6,7 +6,10 @@
 # @FileName: han_trainer.py
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 import gammagl.transforms as T

examples/hardgat/hardgat_trainer.py

@@ -8,7 +8,10 @@
 
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 from gammagl.datasets import Planetoid

examples/hcha/hcha_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import argparse
 import tensorlayerx as tlx
 import numpy as np

examples/herec/herec_trainer_aminer.py

@@ -1,7 +1,10 @@
 import argparse
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import os.path as osp
 import tensorlayerx as tlx
 from gammagl.datasets import AMiner

examples/herec/herec_trainer_imdb_dblp.py

@@ -1,7 +1,10 @@
 import argparse
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 import os.path as osp
 import tensorlayerx as tlx
 from gammagl.datasets import IMDB, DBLP

examples/hetero_rgcn/rgcn_trainer.py

@@ -1,6 +1,9 @@
 import os
 # os.environ['CUDA_VISIBLE_DEVICES'] = '0'
-# os.environ['TL_BACKEND'] = 'torch'
+os.environ['TL_BACKEND'] = 'torch'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' 
+# 0:Output all; 1:Filter out INFO; 2:Filter out INFO and WARNING; 3:Filter out INFO, WARNING, and ERROR
+
 from gammagl.datasets.alircd import AliRCD
 import argparse
 import tensorlayerx as tlx