Python – tensorflow.math.reduce_max()
Last Updated :
14 May, 2021
TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
reduce_max() is used to find maximum of elements across dimensions of a tensor.
Syntax: tensorflow.math.reduce_max( input_tensor, axis, keepdims, name)
Parameters:
- input_tensor: It is numeric tensor to reduce.
- axis(optional): It represent the dimensions to reduce. It’s value should be in range [-rank(input_tensor), rank(input_tensor)). If no value is given for this all dimensions are reduced.
- keepdims(optional): It’s default value is False. If it’s set to True it will retain the reduced dimension with length 1.
- name(optional): It defines the name for the operation.
Returns: It returns a tensor.
Example 1:
Python3
import tensorflow as tf
a = tf.constant([ 1 , 2 , 3 , 4 ], dtype = tf.float64)
print ( 'Input: ' , a)
res = tf.math.reduce_max(a)
print ( 'Result: ' , res)
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Output:
Input: tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
Result: tf.Tensor(4.0, shape=(), dtype=float64)
Example 2:
Python3
import tensorflow as tf
a = tf.constant([[ 1 , 2 ], [ 3 , 4 ]], dtype = tf.float64)
print ( 'Input: ' , a)
res = tf.math.reduce_max(a, axis = 1 , keepdims = True )
print ( 'Result: ' , res)
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Output:
Input: tf.Tensor(
[[1. 2.]
[3. 4.]], shape=(2, 2), dtype=float64)
Result: tf.Tensor(
[[2.]
[4.]], shape=(2, 1), dtype=float64)
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