Hello,
I have a dataset composed of   labels,features,adjacency matrices, laplacian  graphs in numpy format.
I would like to build a torch.utils.data.data_utils.TensorDataset() and torch.utils.data.DataLoader() that can take labels,features,adjacency matrices, laplacian  graphs.
To do so, l have tried the following

import numpy as np
import torch.utils.data as data_utils

# get the numpy data
 labels_train,features_train,adjacency_train,laplacian_train=train
 labels_test,features_test,adjacency_test,laplacian_test=test


# expand dimension
features_train=np.expand_dims(features_train,axis=0)
features_test=np.expand_dims(features_test,axis=0)

adjacency_train=np.expand_dims(adjacency_train,axis=0)
adjacency_test=np.expand_dims(adjacency_test,axis=0)

laplacian_train=np.expand_dims(laplacian_train,axis=0)
laplacian_test=np.expand_dims(laplacian_test,axis=0)

# convert  numy data to torch
labels_train=torch.from_numpy(labels_train)
features_train=torch.from_numpy(features_train)
adjacency_train=torch.from_numpy(adjacency_train)
laplacian_train=torch.from_numpy(laplacian_train)

labels_test=torch.from_numpy(labels_test)
features_test=torch.from_numpy(features_test)
adjacency_test=torch.from_numpy(adjacency_test)
laplacian_test=torch.from_numpy(laplacian_test)

# l get stuck here
train=data_utils.TensorDataset(features_train.float(),labels_train,adjacency_train.float(),laplacian_train.float())

test=data_utils.TensorDataset(features_test.float(),labels_test,adjacency_test.float(),laplacian_test.float())

It doesn’t work because it’s supposed to take only two parameters features_train and labels_train only.
Is there any way to accept more than two parameters ?
What is my purpose ?
Once l have get train and test from data_utils.TensorDataset() l would like to load my data as follow :
train_loader=data_utils.DataLoader(train)
val_loader= data_utils.DataLoader(test)

It doesnt’ work because DataLoader() is supposed to have only target and features_data (not adjacency matrices and laplacian).
I need this setup in order to do the following :
for i,(input,target,adjacency_matrix,laplacian) in enumerate(train_loader):
     # do my training

Thank you for you help
@smth, @ptrblck  is there any cue ?