tf.math.exp

Computes exponential of x element-wise. \(y = e^x\).

View aliases

Main aliases

tf.exp

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.exp

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

Used in the notebooks

Used in the guide	Used in the tutorials
Understanding masking & padding	Scalable model compression Convolutional Variational Autoencoder Learned data compression Multiple changepoint detection and Bayesian model selection Modeling COVID-19 spread in Europe and the effect of interventions

This function computes the exponential of the input tensor element-wise. i.e. math.exp(x) or \(e^x\), where x is the input tensor. \(e\) denotes Euler's number and is approximately equal to 2.718281. Output is positive for any real input.

x = tf.constant(2.0)
tf.math.exp(x)
<tf.Tensor: shape=(), dtype=float32, numpy=7.389056>

x = tf.constant([2.0, 8.0])
tf.math.exp(x)
<tf.Tensor: shape=(2,), dtype=float32,
numpy=array([   7.389056, 2980.958   ], dtype=float32)>

For complex numbers, the exponential value is calculated as

\[ e^{x+iy} = {e^x} {e^{iy} } = {e^x} ({\cos (y) + i \sin (y)}) \]

For 1+1j the value would be computed as:

\[ e^1 (\cos (1) + i \sin (1)) = 2.7182817 \times (0.5403023+0.84147096j) \]

x = tf.constant(1 + 1j)
tf.math.exp(x)
<tf.Tensor: shape=(), dtype=complex128,
numpy=(1.4686939399158851+2.2873552871788423j)>

Args
x	A tf.Tensor. Must be one of the following types: bfloat16, half, float32, float64, complex64, complex128.
name	A name for the operation (optional).

Returns
A tf.Tensor. Has the same type as x.

numpy compatibility

Equivalent to np.exp