a66a9216d2d3fd193782640b4e9eb4f50f4b3697,opt_einsum.py,,_path_optimal,#,67

Before Change

        current = new

    // If we have not found anything return single einsum contraction
    if len(new) == 0:
        return [tuple(range(len(input_sets)))]

    new.sort()
    path = new[0][1]
    return path


def _path_opportunistic(input_sets, output_set, idx_dict, memory_limit):

After Change

            cost, positions, remaining = curr

            // The memory limited case
            idx_contract = set("").union(*remaining)
            new_cost = _compute_size_by_dict(idx_contract, idx_dict)
            if len(idx_contract - output_set) > 0:
                new_cost *= 2
            new_cost *= len(remaining) - 1
            new_cost += cost
            new_pos = positions + [tuple(range(len(remaining)))]
            memory_limited.append((new_cost, new_pos, []))
                     
            for con in comb_iter:

Instances