def qubo_dict_to_torch()

in utils.py [0:0]

• 10 lines of code
• 4 McCabe index (conditional complexity)

def qubo_dict_to_torch(nx_G, Q, torch_dtype=None, torch_device=None):
    """
    Output Q matrix as torch tensor for given Q in dictionary format.

    Input:
        Q: QUBO matrix as defaultdict
        nx_G: graph as networkx object (needed for node lables can vary 0,1,... vs 1,2,... vs a,b,...)
    Output:
        Q: QUBO as torch tensor
    """

    # get number of nodes
    n_nodes = len(nx_G.nodes)

    # get QUBO Q as torch tensor
    Q_mat = torch.zeros(n_nodes, n_nodes)
    for (x_coord, y_coord), val in Q.items():
        Q_mat[x_coord][y_coord] = val

    if torch_dtype is not None:
        Q_mat = Q_mat.type(torch_dtype)

    if torch_device is not None:
        Q_mat = Q_mat.to(torch_device)

    return Q_mat