tf.compat.v1.math.sigmoid | TensorFlow v2.16.1 (original) (raw)
tf.compat.v1.math.sigmoid
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Computes sigmoid of x element-wise.
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tf.compat.v1.math.sigmoid(
x, name=None
)
Formula for calculating \(\mathrm{sigmoid}(x) = y = 1 / (1 + \exp(-x))\).
For \(x \in (-\infty, \infty)\), \(\mathrm{sigmoid}(x) \in (0, 1)\).
Example Usage:
If a positive number is large, then its sigmoid will approach to 1 since the formula will be y = <large_num> / (1 + <large_num>)
x = tf.constant([0.0, 1.0, 50.0, 100.0])
tf.math.sigmoid(x)
<tf.Tensor: shape=(4,), dtype=float32,
numpy=array([0.5, 0.7310586, 1.0, 1.0], dtype=float32)>
If a negative number is large, its sigmoid will approach to 0 since the formula will be y = 1 / (1 + <large_num>)
x = tf.constant([-100.0, -50.0, -1.0, 0.0])
tf.math.sigmoid(x)
<tf.Tensor: shape=(4,), dtype=float32, numpy=
array([0.0000000e+00, 1.9287499e-22, 2.6894143e-01, 0.5],
dtype=float32)>
| Args | |
|---|---|
| x | A Tensor with type float16, float32, float64, complex64, orcomplex128. |
| name | A name for the operation (optional). |
| Returns |
|---|
| A Tensor with the same type as x. |
Usage Example:
x = tf.constant([-128.0, 0.0, 128.0], dtype=tf.float32)
tf.sigmoid(x)
<tf.Tensor: shape=(3,), dtype=float32,
numpy=array([0. , 0.5, 1. ], dtype=float32)>
scipy compatibility
Equivalent to scipy.special.expit