def gen_updates_sgd(loss, all_parameters, learning_rate):
    all_grads = [theano.grad(loss, param) for param in all_parameters]
    updates = []
    for param_i, grad_i in zip(all_parameters, all_grads):
        updates.append((param_i, param_i - learning_rate * grad_i))
    return updates
dataset/ETHPy150Open ifp-uiuc/anna/anna/layers/layers.py/gen_updates_sgd/original