Skip to content
Related Articles

Related Articles

Python – tensorflow.raw_ops.Log()
  • Last Updated : 05 Jun, 2020
GeeksforGeeks - Summer Carnival Banner

TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning  neural networks. TensorFlow raw_ops provides low level access to all TensorFlow operations. Log() is used to find element wise logarithm of x.

Syntax: tf.raw_ops.Log(x, name)

Parameters: 

  • x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, complex64, complex128. 
  • name(optional): It’s defines the name for the operation.
     

Returns:  It returns a tensor of same dtype as x.
 

Note: It only takes keyword arguments.



Example 1:

Python3




# Importing the library
import tensorflow as tf
  
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)
  
# Printing the input tensor
print('Input: ', a)
  
# Calculating logarithm
res = tf.raw_ops.Log(x = a)
  
# Printing the result
print('Result: ', res)

Output:

Input:  tf.Tensor([1. 2. 3. 4. 5.], shape=(5, ), dtype=float64)
Result:  tf.Tensor([0.         0.69314718 1.09861229 1.38629436 1.60943791], shape=(5, ), dtype=float64)


Example 2: Visualization

Python3




# importing the library
import tensorflow as tf
import matplotlib.pyplot as plt
  
# Initializing the input tensor
a = tf.constant([1, 2, 3, 4, 5], dtype = tf.float64)
  
# Calculating logarithm
res = tf.raw_ops.Log(x = a)
  
# Plotting the graph
plt.plot(a, res, color ='green')
plt.title('tensorflow.raw_ops.Log')
plt.xlabel('Input')
plt.ylabel('Result')
plt.show()

Output:

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.

My Personal Notes arrow_drop_up
Recommended Articles
Page :