Note that in case of ties the identity of the return value is not guaranteed.
Usage
import tensorflow as tf
a = [1, 10, 26.9, 2.8, 166.32, 62.3]
b = tf.math.argmax(input = a)
c = tf.keras.backend.eval(b)
# c = 4
# here a[4] = 166.32 which is the largest element of a across axis 0
Args
input
A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64, qint8, quint8, qint32, qint16, quint16, bool.
axis
A Tensor. Must be one of the following types: int16, int32, int64.
int16, int32 or int64, must be in the range [-rank(input), rank(input)).
Describes which axis of the input Tensor to reduce across. For vectors,
use axis = 0.
output_type
An optional tf.DType from: tf.int16, tf.uint16, tf.int32, tf.int64. Defaults to tf.int64.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[]]