mindspore.ops.glu

mindspore.ops.glu(x, axis=- 1)[source]

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 \(*\) 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]]