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tfa.activations.mish

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Mish: A Self Regularized Non-Monotonic Neural Activation Function.

tfa.activations.mish(
 x: tfa.types.TensorLike
) -> tf.Tensor

Computes mish activation:

\[ \mathrm{mish}(x) = x \cdot \tanh(\mathrm{softplus}(x)). \]

See Mish: A Self Regularized Non-Monotonic Neural Activation Function.

Usage:

x = tf.constant([1.0, 0.0, 1.0])
tfa.activations.mish(x)
<tf.Tensor: shape=(3,), dtype=float32, numpy=array([0.865098..., 0. , 0.865098...], dtype=float32)>

Args

x A Tensor. Must be one of the following types: bfloat16, float16, float32, float64.

Returns

A Tensor. Has the same type as x.

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Last updated 2023年07月12日 UTC.