TensorFlow 1 version
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View source on GitHub
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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 | |
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A Tensor of type output_type.
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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
TensorFlow 1 version
View source on GitHub