I have a code in which I use the DBP15K dataset via
from torch_geometric.datasets import DBP15K
data = DBP15K(path, args.category, transform=SumEmbedding())[0].to(device)
But according to the documentation of pytorch geometric this one is divided only in train and in test.
I tried to divide it by myself using the function "train_test_split_edges" .
But nothing I tried worked so I wanted to know if some of you already tried to split this dataset.
Finally I just need to split either the test or the train to have the validation.
I just did it like this:
data = DBP15K(path, args.category, transform=SumEmbedding())[0].to(device)
# Divide the tensor into two parts with ratios 0.8 and 0.2
split_index = int(0.8 * data.train_y.shape[1])
train_y, val_y = torch.split(data.train_y, [split_index, data.train_y.shape[1] - split_index], dim=1)
# Display tensor shapes
print(train_y.shape) # torch.Size([2, 3296])
print(val_y.shape) # torch.Size([2, 825])