Function _e_batch_norm_grad

operators.py:385–387

(op, grad)

    return trainer_ops.e_batch_norm(inputs,scale,offset,mean,variance,epsilon=epsilon,eid_low=(eid&0xFFFFFFFF),eid_high=(eid>>32),times=times)
@ops.RegisterGradient("EBatchNorm")
def _e_batch_norm_grad(op, grad):
    with tf.name_scope("EBatchNormGrad"), tf.xla.experimental.jit_scope(compile_ops=False):
        return trainer_ops.e_batch_norm_grad(grad,op.inputs[0],op.inputs[1],op.inputs[2],op.inputs[3],op.inputs[4],op.get_attr('epsilon'),eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[0],trainer_ops.e_batch_norm_grad(grad,op.inputs[0],op.inputs[1],op.inputs[2],op.inputs[3],op.inputs[4],op.get_attr('epsilon'),eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[1],trainer_ops.e_batch_norm_grad(grad,op.inputs[0],op.inputs[1],op.inputs[2],op.inputs[3],op.inputs[4],op.get_attr('epsilon'),eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[2],trainer_ops.e_batch_norm_grad(grad,op.inputs[0],op.inputs[1],op.inputs[2],op.inputs[3],op.inputs[4],op.get_attr('epsilon'),eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[3],trainer_ops.e_batch_norm_grad(grad,op.inputs[0],op.inputs[1],op.inputs[2],op.inputs[3],op.inputs[4],op.get_attr('epsilon'),eid_low=op.get_attr("eid_low"), eid_high=op.get_attr("eid_high"),times = op.get_attr("times"))[4]

def e_abs(inputs):
    global eid,times