Skip to content
Related Articles

Related Articles

Save Article
Improve Article
Save Article
Like Article

Python – tensorflow.math.reduce_mean()

  • Last Updated : 11 Aug, 2021

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

reduce_mean() is used to find mean of elements across dimensions of a tensor.

 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

Syntax: tensorflow.math.reduce_mean( 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




# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4], dtype = tf.float64)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reduce_mean(a)
 
# Printing the result
print('Result: ', res)

Output:

Input:  tf.Tensor([1. 2. 3. 4.], shape=(4, ), dtype=float64)
Result:  tf.Tensor(2.5, shape=(), dtype=float64)

Example 2:

Python3




# importing the library
import tensorflow as tf
 
# Initializing the input tensor
a = tf.constant([[1, 2], [3, 4]], dtype = tf.float64)
 
# Printing the input tensor
print('Input: ', a)
 
# Calculating result
res = tf.math.reduce_mean(a, axis = 1, keepdims = True)
 
# Printing the result
print('Result: ', res)

Output:

Input:  tf.Tensor(
[[1. 2.]
 [3. 4.]], shape=(2, 2), dtype=float64)
Result:  tf.Tensor(
[[1.5]
 [3.5]], shape=(2, 1), dtype=float64)



My Personal Notes arrow_drop_up
Recommended Articles
Page :