INNER CODE UNIT · Python
train_val_pipeline
graphdeeplearning/benchmarking-gnns · main_COLLAB_edge_classification.py:89
def train_val_pipeline(MODEL_NAME, dataset, params, net_params, dirs):
t0 = time.time()
per_epoch_time = []
DATASET_NAME = dataset.name
#assert net_params['self_loop'] == False, "No self-loop support for %s dataset" % DATASET_NAME
if MODEL_NAME in ['GatedGCN']:
if net_params['pos_enc']:
print("[!] Adding graph positional encoding",net_params['pos_enc_dim'])
dataset._add_positional_encodings(net_params['pos_enc_dim'])
print('Time PE:',time.time()-t0)
graph = dataset.graph
evaluator = dataset.evaluator