tf.compat.v2.argmax

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

View aliases

Compat aliases for migration

`tf.compat.v2.math.argmax`

tf.compat.v2.argmax(
    input, axis=None, output_type=tf.dtypes.int64, name=None
)

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[2]) 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]

Args: 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).

Returns
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[4] = 166.32 which is the largest element of a across axis 0