Stay organized with collections
Save and categorize content based on your preferences.
tensorflow::ops::Expm1
#include <math_ops.h>
Computes exp(x) - 1 element-wise.
Summary
i.e. exp(x) - 1 or e^(x) - 1, where x is the input tensor. e denotes Euler's number and is approximately equal to 2.718281.
x = tf.constant(2.0)
tf.math.expm1(x) ==> 6.389056
x = tf.constant([2.0, 8.0])
tf.math.expm1(x) ==> array([6.389056, 2979.958], dtype=float32)
x = tf.constant(1 + 1j)
tf.math.expm1(x) ==> (0.46869393991588515+2.2873552871788423j)
Args:
Returns:
Public attributes
Public functions
node
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.
Last updated 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tensorflow::ops::Expm1 Class Reference\n\ntensorflow::ops::Expm1\n======================\n\n`#include \u003cmath_ops.h\u003e`\n\nComputes `exp(x) - 1` element-wise.\n\nSummary\n-------\n\ni.e. `exp(x) - 1` or `e^(x) - 1`, where `x` is the input tensor. `e` denotes Euler's number and is approximately equal to 2.718281.\n\n\n```gdscript\n x = tf.constant(2.0)\n tf.math.expm1(x) ==\u003e 6.389056\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n x = tf.constant([2.0, 8.0])\n tf.math.expm1(x) ==\u003e array([6.389056, 2979.958], dtype=float32)\n```\n\n\u003cbr /\u003e\n\n\n```gdscript\n x = tf.constant(1 + 1j)\n tf.math.expm1(x) ==\u003e (0.46869393991588515+2.2873552871788423j)\n \n```\n\n\u003cbr /\u003e\n\nArgs:\n\n- scope: A [Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output): The y tensor.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [Expm1](#classtensorflow_1_1ops_1_1_expm1_1a8b296111e0b616c52bb1ac32c54a6d7a)`(const ::`[tensorflow::Scope](/versions/r2.14/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.14/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` x)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------|\n| [operation](#classtensorflow_1_1ops_1_1_expm1_1a7a9850515f4ea6fbf373787463eb09df) | [Operation](/versions/r2.14/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n| [y](#classtensorflow_1_1ops_1_1_expm1_1a05fbc6afc7aea30c2af304ea0f47dbf4) | `::`[tensorflow::Output](/versions/r2.14/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n\n| ### Public functions ||\n|-----------------------------------------------------------------------------------------------------------------|------------------------|\n| [node](#classtensorflow_1_1ops_1_1_expm1_1a8f37d6ec3ccfb35f8989f12b006ef8f3)`() const ` | `::tensorflow::Node *` |\n| [operator::tensorflow::Input](#classtensorflow_1_1ops_1_1_expm1_1a9ea90c07657a9520b10ba34cf017fe7a)`() const ` | |\n| [operator::tensorflow::Output](#classtensorflow_1_1ops_1_1_expm1_1a0adfeeb72d4fe4c11e5d03a6fd39facc)`() const ` | |\n\nPublic attributes\n-----------------\n\n### operation\n\n```text\nOperation operation\n``` \n\n### y\n\n```text\n::tensorflow::Output y\n``` \n\nPublic functions\n----------------\n\n### Expm1\n\n```gdscript\n Expm1(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input x\n)\n``` \n\n### node\n\n```gdscript\n::tensorflow::Node * node() const \n``` \n\n### operator::tensorflow::Input\n\n```gdscript\n operator::tensorflow::Input() const \n``` \n\n### operator::tensorflow::Output\n\n```gdscript\n operator::tensorflow::Output() const \n```"]]
