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mindspore.ops.glu

mindspore.ops.glu(x, axis=- 1)

Computes GLU (Gated Linear Unit activation function) of input tensors .

$$GLU(a,b)=a\otimes \sigma (b)$$

where $a$ is the first half of the input matrices and $b$ is the second half.

Here $\sigma$ is the sigmoid function, and $\ast$ is the Hadamard product. See Language Modeling with Gated Convluational Networks.

Parameters

• x (Tensor) – Tensor to be splited. Its dtype is number.Number, and shape is $({\ast }_1,N,{\ast }_2)$ where * means, any number of additional dimensions.

• axis (int, optional) – the dimension on which to split the input. It must be int. Default: -1.

Returns

Tensor, the same dtype as the x, with the shape $({\ast }_1,M,{\ast }_2)$ where $M=N/2$.

Raises

• TypeError – If dtype of x is not number.Number.

• TypeError – If x is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

>>> input = Tensor([[0.1,0.2,0.3,0.4],[0.5,0.6,0.7,0.8]])
>>> output = ops.glu(input)
>>> print(output)
[[0.05744425 0.11973753]
 [0.33409387 0.41398472]]