clone¶
- paddle. clone ( x, name=None ) [source]
-
Returns a copy of input Tensor. It will always have a Tensor copy.
In addition, This function is derivable, so gradients will flow back from the output to input.
- Parameters
-
x (Tensor) – The input Tensor.
name (str, optional) – For details, please refer to Name. Generally, no setting is required. Default: None.
- Returns
-
Tensor, A Tensor copied from
input
.
Examples
>>> import paddle >>> import numpy as np >>> x = paddle.ones([2]) >>> x.stop_gradient = False >>> x.retain_grads() >>> clone_x = paddle.clone(x) >>> clone_x.retain_grads() >>> y = clone_x**3 >>> y.backward() >>> print(clone_x.grad.numpy()) [3. 3.] >>> print(x.grad.numpy()) [3. 3.]