def fanin_init_weights_like()

in utils/pytorch_util.py [0:0]

• 12 lines of code
• 3 McCabe index (conditional complexity)

def fanin_init_weights_like(tensor):
    size = tensor.size()
    if len(size) == 2:
        fan_in = size[0]
    elif len(size) > 2:
        fan_in = np.prod(size[1:])
    else:
        raise Exception("Shape must be have dimension at least 2.")
    bound = 1. / np.sqrt(fan_in)
    new_tensor = torch.FloatTensor(tensor.size())
    new_tensor.uniform_(-bound, bound)
    return new_tensor