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mindspore.Tensor.soft_shrink

Tensor.soft_shrink(lambd=0.5)

Apply the soft shrink function for a tensor. Calculates the output according to the input elements.

The formula is defined as follows:

$$\begin{array}{r}\text{SoftShrink}(x)=\{\begin{array}{ll}x-\lambda ,& \text{ if }x>\lambda \\ x+\lambda ,& \text{ if }x<-\lambda \\ 0,& \text{ otherwise }\end{array}\end{array}$$

Parameters

lambd (float) – the $\lambda$ must be no less than zero. Default: 0.5.

Returns

Tensor, has the same shape and data type as self.

Raises

• TypeError – If lambd is not a float.

• TypeError – If input_x is not a Tensor.

• TypeError – If dtype of input_x is neither float16 nor float32.

• ValueError – If lambd is less than 0.

Supported Platforms:

Ascend GPU CPU

Examples

>>> from mindspore import Tensor
>>> a = Tensor([[ 0.5297,  0.7871,  1.1754], [ 0.7836,  0.6218, -1.1542]]).astype("float32")
>>> output = a.soft_shrink()
>>> print(output)
[[ 0.02979  0.287    0.676  ]
 [ 0.2837   0.1216  -0.6543 ]]