optimize clip_by_norm

[zhangting2020]

优化点：

• mul + set_value，其中set_value导致大量的memcpy，替换成inplace的操作
• 冗余的clip_norm计算，增加need_grad_norm，仅在tensorboard需要观察该值时再进行计算，否则会引入大量的norm算子
• 冗余的cast，PR代码中的 paddle_dtype打印结果为“float32”，但是实际tensor.dtype得到的是paddle.float32，会导致判断失败，从而引入无意义的cast。另外O2下梯度为fp16，原始写法需要每次将clip_coef_clamped转换成fp16，实际只需要计算一次，其他的梯度直接使用即可，所以添加了clip_coef_clamped_low_precison 变量。

效果：

• O1：0.739 steps/s -> 2.194 steps/s
• O2：1.067 steps/s -> 2.655 steps/s

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