tf.keras.activations.hard_sigmoid
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Hard sigmoid activation function.
tf.keras.activations.hard_sigmoid(
x
)
A faster approximation of the sigmoid activation.
For example:
a = tf.constant([-3.0,-1.0, 0.0,1.0,3.0], dtype = tf.float32)
b = tf.keras.activations.hard_sigmoid(a)
b.numpy()
array([0. , 0.3, 0.5, 0.7, 1. ], dtype=float32)
Arguments |
|---|
x
|
Input tensor.
|
Returns |
|---|
The hard sigmoid activation, defined as:
if x < -2.5: return 0if x > 2.5: return 1if -2.5 <= x <= 2.5: return 0.2 * x + 0.5
|
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.keras.activations.hard_sigmoid\n\n\u003cbr /\u003e\n\n|-------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 1 version](/versions/r1.15/api_docs/python/tf/keras/activations/hard_sigmoid) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.3.0/tensorflow/python/keras/activations.py#L378-L402) |\n\nHard sigmoid activation function.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.activations.hard_sigmoid`](/api_docs/python/tf/keras/activations/hard_sigmoid)\n\n\u003cbr /\u003e\n\n tf.keras.activations.hard_sigmoid(\n x\n )\n\nA faster approximation of the sigmoid activation.\n\n#### For example:\n\n a = tf.constant([-3.0,-1.0, 0.0,1.0,3.0], dtype = tf.float32)\n b = tf.keras.activations.hard_sigmoid(a)\n b.numpy()\n array([0. , 0.3, 0.5, 0.7, 1. ], dtype=float32)\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Arguments --------- ||\n|-----|---------------|\n| `x` | Input tensor. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| The hard sigmoid activation, defined as: \u003cbr /\u003e - `if x \u003c -2.5: return 0` - `if x \u003e 2.5: return 1` - `if -2.5 \u003c= x \u003c= 2.5: return 0.2 * x + 0.5` ||\n\n\u003cbr /\u003e"]]
TensorFlow 1 version
View source on GitHub