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Returns the index with the largest value across axes of a tensor.
Aliases:
tf.math.argmax(
input,
axis=None,
output_type=tf.dtypes.int64,
name=None
)
Used in the guide:
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
: ATensor
. 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
: ATensor
. 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 optionaltf.DType
from:tf.int32, tf.int64
. Defaults totf.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