Function _e_maximum_grad

model_demo/DeepCrossing/operators.py:303–305

(op, grad)

    return trainer_ops.e_minimum(input1,input2,eid_low=(eid&0xFFFFFFFF),eid_high=(eid>>32),times=times)
@ops.RegisterGradient("EMinimum")
def _e_maximum_grad(op, grad):
    with tf.name_scope("EMinimumGrad"), tf.xla.experimental.jit_scope(compile_ops=False):
        return trainer_ops.e_minimum_grad(grad,op.inputs[0],op.inputs[1],eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[0],trainer_ops.e_minimum_grad(grad,op.inputs[0],op.inputs[1],eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[1]

def e_maximum(input1,input2):
    global eid,times