tf.compat.v1.math.exp
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Computes exponential of x element-wise. \(y = e^x\).
tf.compat.v1.math.exp(
x, name=None
)
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).
|
Equivalent to np.exp
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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.compat.v1.math.exp\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/math_ops.py#L5459-L5506) |\n\nComputes exponential of x element-wise. \\\\(y = e\\^x\\\\). \n\n tf.compat.v1.math.exp(\n x, name=None\n )\n\nThis function computes the exponential of the input tensor element-wise.\ni.e. [`math.exp(x)`](https://www.tensorflow.org/api_docs/python/tf/math/exp) or \\\\(e\\^x\\\\), where `x` is the input tensor.\n\\\\(e\\\\) denotes Euler's number and is approximately equal to 2.718281.\nOutput is positive for any real input. \n\n x = tf.constant(2.0)\n tf.math.exp(x)\n \u003ctf.Tensor: shape=(), dtype=float32, numpy=7.389056\u003e\n\n x = tf.constant([2.0, 8.0])\n tf.math.exp(x)\n \u003ctf.Tensor: shape=(2,), dtype=float32,\n numpy=array([ 7.389056, 2980.958 ], dtype=float32)\u003e\n\nFor complex numbers, the exponential value is calculated as\n\n\\\\\\[\ne\\^{x+iy} = {e\\^x} {e\\^{iy} } = {e\\^x} ({\\\\cos (y) + i \\\\sin (y)})\n\\\\\\]\n\nFor `1+1j` the value would be computed as:\n\n\\\\\\[\ne\\^1 (\\\\cos (1) + i \\\\sin (1)) = 2.7182817 \\\\times (0.5403023+0.84147096j)\n\\\\\\] \n\n x = tf.constant(1 + 1j)\n tf.math.exp(x)\n \u003ctf.Tensor: shape=(), dtype=complex128,\n numpy=(1.4686939399158851+2.2873552871788423j)\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|--------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x` | A [`tf.Tensor`](../../../../tf/Tensor). Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`, `complex64`, `complex128`. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A [`tf.Tensor`](../../../../tf/Tensor). Has the same type as `x`. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nnumpy compatibility\n-------------------\n\n\u003cbr /\u003e\n\nEquivalent to np.exp\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e"]]
View source on GitHub