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tf.math.argmax

Returns the index with the largest value across axes of a tensor.

Note that in case of ties the identity of the return value is not guaranteed.

For example:

A=tf.constant([2,20,30,3,6]) # Constant 1-D Tensor
tf.math.argmax(A) # output 2 as index 2 (A) is maximum in tensor A
B=tf.constant([[2,20,30,3,6],[3,11,16,1,8],[14,45,23,5,27]])
tf.math.argmax(B,0) # [2, 2, 0, 2, 2]
tf.math.argmax(B,1) # [2, 2, 1]

input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
axis A Tensor. Must be one of the following types: int32, int64. 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.int32, tf.int64. Defaults to tf.int64.
name A name for the operation (optional).

A Tensor of type output_type.

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 = 166.32 which is the largest element of a across axis 0
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]