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Computes sigmoid of x
element-wise.
tf.math.sigmoid( x, name=None )
Formula for calculating sigmoid(x): y = 1 / (1 + exp(-x))
.
For x \in (-inf, inf) => sigmoid(x) \in (0, 1)
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. , 1. ], 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 | |
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x | A Tensor with type float16 , float32 , float64 , complex64 , or complex128 . |
name | A name for the operation (optional). |
Returns | |
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A Tensor with the same type as x . |
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)>
Equivalent to scipy.special.expit
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/math/sigmoid