TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning neural networks.
scalar_mul() is used to multiply a tensor with a scalar.
Syntax: tf.math.scalar_mul( scalar, x, name )
Parameters:
- scalar: It is a 0-D scalar tensor of known shape.
- x: It’s a tensor that need to be scaled.
- name(optional): It defines the name for operation.
Returns:
It returns a tensor of same dtype as x.
Example 1:
Python3
# importing the library import tensorflow as tf # Initializing the input tensor scalar = ( 5 ) a = tf.constant([ 2.5 , 5.5 , 1.5 , 6.5 ], dtype = tf.float64) # Printing the input tensor print ( 'scalar: ' , scalar) print ( 'a: ' , a) # Calculating result res = tf.math.scalar_mul(scalar, a) # Printing the result print ( 'Result: ' , res) |
Output:
scalar: 5 a: tf.Tensor([2.5 5.5 1.5 6.5], shape=(4, ), dtype=float64) Result: tf.Tensor([12.5 27.5 7.5 32.5], shape=(4, ), dtype=float64)
Example 2: This example uses complex tensor.
Python3
# importing the library import tensorflow as tf # Initializing the input tensor scalar = ( 5 ) a = tf.constant([ 2.5 + 3j , 5.5 + 1j , 1.5 + 7j , 6.5 + 8j ], dtype = tf.complex128) # Printing the input tensor print ( 'scalar: ' , scalar) print ( 'a: ' , a) # Calculating result res = tf.math.scalar_mul(scalar, a) # Printing the result print ( 'Result: ' , res) |
Output:
scalar: 5 a: tf.Tensor([2.5+3.j 5.5+1.j 1.5+7.j 6.5+8.j], shape=(4, ), dtype=complex128) Result: tf.Tensor([12.5+15.j 27.5 +5.j 7.5+35.j 32.5+40.j], shape=(4, ), dtype=complex128)