tf.math.sigmoid | TensorFlow v2.16.1 (original) (raw)

tf.math.sigmoid

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Computes sigmoid of x element-wise.

View aliases

Main aliases

tf.nn.sigmoid, tf.sigmoid

Compat aliases for migration

SeeMigration guide for more details.

tf.compat.v1.sigmoid

tf.math.sigmoid(
    x, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Logistic regression for binary classification with Core APIs Advanced automatic differentiation Introduction to gradients and automatic differentiation	Convolutional Variational Autoencoder Transfer learning and fine-tuning Classify structured data using Keras preprocessing layers Classify text with BERT Shape Constraints for Ethics with Tensorflow Lattice

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