GraphView.clone does not clone tensor

import aidge_core
import aidge_backend_cpu

def initFiller(model, array_value):
    # Initialize parameters (weights and biases)
    for node in model.get_nodes():
        if node.type() == "Producer":
            prod_op = node.get_operator()
            value = prod_op.get_output(0)
            value.set_backend("cpu")
            tuple_out = node.output(0)[0]
            if tuple_out[0].type() == "FC" and tuple_out[1] == 1:
                # FC weight
                aidge_core.constant_filler(value, array_value)
            elif tuple_out[0].type() == "FC" and tuple_out[1] == 2:
                # FC bias
                aidge_core.constant_filler(value, array_value)
            else:
                pass


fc = aidge_core.FC(in_channels=6, out_channels=6, name="InputNode")

model = aidge_core.sequential([fc])

initFiller(model, 0.0)

model.compile("cpu", aidge_core.dtype.float32, dims=[[1, 6, 1, 1]])

clone_model=model.clone()

initFiller(clone_model, 1.0)

for node in model.get_nodes():
    if node.type() == "Producer":
        prod_op = node.get_operator()
        value = prod_op.get_output(0)
        value.set_backend("cpu")
        tuple_out = node.output(0)[0]
        # No conv in current network
        if tuple_out[0].type() == "FC" and tuple_out[1] == 1:
            # FC weight
            print(value)

Output:

{
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000},
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000},
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000},
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000},
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000},
  { 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000}
}

Expected output was 0.0 ...