用户使用momentum optimizer时出现cast op输入不存在错误

[sneaxiy]

用户反馈在使用momentum optimizer时append backward出现cast op错误，用其他optimizer未出现错误。

Paddle版本release 1.2。

code:

def balanced_cross_entropy_bootstrap_loss(prediction, gt_org, average_flag = True, bootstrapped_threshold=0.95):
    class_num = prediction.shape[1]
    #get gt_mask
    gt = fluid.layers.reshape(gt_org, [0, 1, gt_org.shape[-2], gt_org.shape[-1]])

    gt_mask = (gt==0).astype('float32')
    for i in range(1, class_num):
        gt_mask_i = (gt==i).astype('float32')
        gt_mask = fluid.layers.concat([gt_mask, gt_mask_i], axis=1)

    #get valid_mask
    valid_mask =  (gt < class_num).astype('float32')
    valid_mask = fluid.layers.expand(valid_mask, [1, class_num, 1, 1])
    #bootstrap
    prediction = prediction.astype('float32')
    pred = fluid.layers.argmax(prediction, axis=1).astype('float32')
    pred = fluid.layers.reshape(pred, [0, 1, pred.shape[-2], pred.shape[-1]])
    bootstrap_valid1 = (pred == gt).astype('float32')
    bootstrap_valid1 = fluid.layers.expand(bootstrap_valid1, [1, class_num, 1, 1])
    bootstrap_valid2 = (prediction > bootstrapped_threshold).astype('float32')
    bootstrap_valid = fluid.layers.elementwise_mul(bootstrap_valid2, bootstrap_valid1)
    bootstrap_mask = (1.0 - bootstrap_valid).astype('float32')
    #print(bootstrap_mask)
    #print(valid_mask)
    valid_mask = fluid.layers.elementwise_mul(bootstrap_mask, valid_mask).astype('float32')

    #get valid gt_mask
    #gt_mask = fluid.layers.elementwise_mul(gt_mask, valid_mask).astype('float32')

    #get balanced weight
    count_num = fluid.layers.reduce_sum(gt_mask, dim=[2, 3]).astype('float32')
    count_num = fluid.layers.elementwise_max(count_num, fluid.layers.assign(np.array([0.00001], dtype=np.float32)))
    balanced_weight = 1 - count_num/fluid.layers.reduce_sum(count_num, dim=1).astype('float32') #count_num [n,c]
    balanced_gt_mask = fluid.layers.elementwise_mul(gt_mask, balanced_weight, axis=0).astype('float32') #gt_mask=[n,c,h,w] balanced_weight=[n,c]

    prediction = fluid.layers.softmax(prediction).astype('float32')
    prediction = fluid.layers.elementwise_max(prediction, fluid.layers.assign(np.array([0.00001], dtype=np.float32)))
    prediction = fluid.layers.log(prediction).astype('float32')
    loss_mask = fluid.layers.elementwise_mul(prediction, balanced_gt_mask, axis=0)

    if average_flag:
        valid_loss = fluid.layers.reduce_mean(fluid.layers.elementwise_mul(loss_mask, valid_mask))
        #valid_loss = fluid.layers.reduce_mean(loss_mask)
    else:
        valid_loss = fluid.layers.reduce_sum(fluid.layers.elementwise_mul(loss_mask, valid_mask, axis=0))
    return    valid_mask,  -1*valid_loss

错误log（编译期错误）：

The input of cast op must be set.

解决方案：将某些不需要梯度的变量设置为stop_gradient=True，例如

bootstrap_mask.stop_gradient = True
valid_mask.stop_gradient = True