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Specifications and Common Mistakes

- Specifications and Common Mistakes:

- Misspellings or punctuation mistakes,incorrect formulas, abnormal display.

- Incorrect links, empty cells, or wrong formats.

- Chinese characters in English context.

- Minor inconsistencies between the UI and descriptions.

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Risk Warnings

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Content Compliance

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mindspore.nn.ReLU

class mindspore.nn.ReLU

Rectified Linear Unit activation function.

Applies the rectified linear unit function element-wise.

$$\text{ReLU}(x)=(x{)}^{+}=max(0,x),$$

It returns element-wise $max(0,x)$, specially, the neurons with the negative output will be suppressed and the active neurons will stay the same.

The picture about ReLU looks like this ReLU.

Inputs:

• x (Tensor) - The input of ReLU. The data type is Number. The shape is $(N,\ast )$ where $\ast$ means, any number of additional dimensions.

Outputs:

Tensor, with the same type and shape as the x.

Raises

TypeError – If dtype of x is not a number.

Supported Platforms:

Ascend GPU CPU

Examples

>>> x = Tensor(np.array([-1, 2, -3, 2, -1]), mindspore.float16)
>>> relu = nn.ReLU()
>>> output = relu(x)
>>> print(output)
[0. 2. 0. 2. 0.]