Problem with SparseTensor in EdgeConv

[ikvara]

Hi, I'm trying to fit a simple model with EdgeConv layer on dataset in Mixed mode and I get an error with the SparseTensor.

Here is my implementation:
`class StressMixedModeDataset(spektral.data.Dataset):
def init(self, data_type, **kwargs):
self.a = None
self.data_type = data_type
super().init(**kwargs)

def read(self):
    if self.data_type=='train':
        with open('train_mixed.pkl', "rb") as fr:   
            output = pckl.load(fr)
    elif self.data_type=='val':
        with open('val_mixed.pkl', "rb") as fr:   
            output = pckl.load(fr)

    self.a = output[0]
    node_feats = output[1]
    edge_feats = output[2]
    y_labels = output[3]

    GraphList = []
    for x, y in zip(node_feats, y_labels):
      x = np.asarray(x)
      y = np.asarray(y)

      GraphList.append(spektral.data.graph.Graph(x=x, e=edge_feats, y=y))

    return GraphList

class Net(tf.keras.models.Model):
def init(self):
super().init()

    self.conv = spektral.layers.EdgeConv(args.n_channels)
    self.output_layer = tf.keras.layers.Dense(6)

def call(self, inputs):
    x, a, e = inputs

    print(type(a))
    x = self.conv([x, a])
    outs = self.output_layer(x)

    return outs

def main(args):
train = StressMixedModeDataset('train')
val = StressMixedModeDataset('val')

print(type(train.a))
print(type(val.a))

loader_tr = spektral.data.loaders.MixedLoader(train, batch_size=args.batch_size)
loader_va = spektral.data.loaders.MixedLoader(val, batch_size=args.batch_size)

model = Net()
model.compile(optimizer=tf.optimizers.Adam(), loss = 'mse')

epochs = args.epochs 
model.fit(loader_tr.load(), 
        validation_data = loader_va.load(),
        steps_per_epoch=loader_tr.steps_per_epoch, 
        validation_steps=loader_va.steps_per_epoch,
        epochs=epochs,
        verbose=2,
        )

if name == "main":
args = parser.parse_args([] if "file" not in globals() else None)
main(args)`

The adjacency matrix is a sparse matrix and is thus converted to SparseTensor. However, from what it prints I see that somewhere it gets broken.
<class 'scipy.sparse.coo.coo_matrix'> <class 'scipy.sparse.coo.coo_matrix'> <class 'tensorflow.python.framework.sparse_tensor.SparseTensor'> Epoch 1/10 <class 'tensorflow.python.framework.ops.Tensor'>

Then I get the following error:
`File "/usr/local/lib/python3.7/dist-packages/spektral/layers/convolutional/message_passing.py", line 105, in call *
x, a, e = self.get_inputs(inputs)
File "/usr/local/lib/python3.7/dist-packages/spektral/layers/convolutional/message_passing.py", line 181, in get_inputs *
assert K.is_sparse(a), "A must be a SparseTensor"

AssertionError: A must be a SparseTensor`

Can you please help? What am I doing wrong?

[ikvara]

Oh, I see where the problem was. The MixedLoader requires different approach to training. I'm sorry for bothering!

[danielegrattarola]

Hey no problem, I'm glad you were able to solve the issue

cheers