Skip to content
Related Articles
Python | tensorflow.math.argmax() method
• Last Updated : 04 Jun, 2020

TensorFlow is open-source python library designed by Google to develop Machine Learning models  and deep learning  neural networks. argmax() is a method present in tensorflow math module. This method is used to find the maximum value across the axes.

```Syntax:
tensorflow.math.argmax(
input,axes,output_type,name
)

Arguments:
1. input: It is a tensor. Allowed dtypes for this tensor are float32,
float64, int32, uint8, int16, int8, complex64, int64, qint8,
quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64.
2. axes: It is also a vector. It describes the axes to reduce the tensor.
Allowed dtype are int32 and int64. Also [-rank(input),rank(input)) is the range allowed.
axes=0 is used for vector.
3. output_type: It defines the dtype in which returned result should be.
Allowed values are int32, int64 and the default value is int64.
4. name: It is an optional argument which defines name for the operation.

Return:
A tensor of output_type which contains the indices of the maximum value along the axes.
```

Example 1:

## Python3

 `# importing the library``import` `tensorflow as tf`` ` `# initializing the constat tensor``a ``=` `tf.constant([``5``,``10``,``5.6``,``7.9``,``1``,``50``]) ``# 50 is the maximum value at index 5`` ` `# getting the maximum value index tensor``b ``=` `tf.math.argmax(``input` `=` `a)`` ` `# printing the tensor``print``(``'tensor: '``,b)`` ` `# Evaluating the value of tensor``c ``=` `tf.keras.backend.``eval``(b)`` ` `#printing the value``print``(``'value: '``,c)`

Output:

```tensor:  tf.Tensor(5, shape=(), dtype=int64)
value: 5
```

Example 2:

This example uses a tensor of shape(3,3).

## Python3

 `# importing the library``import` `tensorflow as tf`` ` `# initializing the constat tensor``a ``=` `tf.constant(value ``=` `[``9``,``8``,``7``,``3``,``5``,``4``,``6``,``2``,``1``],shape ``=` `(``3``,``3``))`` ` `# printing the initialized tensor``print``(a)`` ` `# getting the maximum value indices tensor``b ``=` `tf.math.argmax(``input` `=` `a)`` ` `# printing the tensor``print``(``'Indices Tensor: '``,b)`` ` `# Evaluating the tesor value``c ``=` `tf.keras.backend.``eval``(b)`` ` `# printing the value``print``(``'Indices: '``,c)`

Output:

```tf.Tensor(
[[9 8 7]
[3 5 4]
[6 2 1]], shape=(3, 3), dtype=int32)
Indices tensor: tf.Tensor([0 0 0], shape=(3,), dtype=int64)
Indices: [0 0 0]
# maximum value along the axes are 9,8,7 at indices 0,0,0 respectively.
```

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course

My Personal Notes arrow_drop_up