TensorFlow 1 version | View source on GitHub |
Returns the index with the largest value across axes of a tensor.
tf.math.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