TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
sqrt() is used to compute element wise square root.
Syntax: tensorflow.math.sqrt(x, name)
Parameters:
- x: It’s a tensor. Allowed dtypes are bfloat16, half, float32, float64, complex64, complex128.
- 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([ 5 , 7 , 9 , 15 ], dtype = tf.float64)
# Printing the input tensor print ( 'a: ' , a)
# Calculating result res = tf.math.sqrt(a)
# Printing the result print ( 'Result: ' , res)
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Output:
a: tf.Tensor([ 5. 7. 9. 15.], shape=(4, ), dtype=float64) Result: tf.Tensor([2.23606798 2.64575131 3. 3.87298335], shape=(4, ), dtype=float64)
Example 2: Visualization
Python3
# import tensorflow as tf import matplotlib.pyplot as plt
# Initializing the input tensor a = tf.constant([ 5 , 7 , 9 , 15 ], dtype = tf.float64)
# Calculating tangent res = tf.math.sqrt(a)
# Plotting the graph plt.plot(a, res, color = 'green' )
plt.title( 'tensorflow.math.sqrt' )
plt.xlabel( 'Input' )
plt.ylabel( 'Result' )
plt.show() |
Output:
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