tf.compat.v1.nn.crelu
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Computes Concatenated ReLU.
tf.compat.v1.nn.crelu(
features, name=None, axis=-1
)
Concatenates a ReLU which selects only the positive part of the activation with a ReLU which selects only the negative part of the activation. Note that as a result this non-linearity doubles the depth of the activations. Source: Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units. W. Shang, et al.
Args |
|---|
features | A Tensor with type float, double, int32, int64, uint8, int16, or int8. |
name | A name for the operation (optional). |
axis | The axis that the output values are concatenated along. Default is -1. |
Returns |
|---|
A Tensor with the same type as features. |
References |
|---|
| Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units: Shang et al., 2016 (pdf) |
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Last updated 2024-04-26 UTC.
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