Python – tensorflow.math.multiply()
TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks. multiply() is used to find element wise x*y. It supports broadcasting.
Syntax: tf.math.multiply(x, y, name)
Parameter:
- x: It’s the input tensor. Allowed dtype for this tensor are bfloat16, half, float32, float64, uint8, int8, uint16, int16, int32, int64, complex64, complex128.
- y: It’s the input tensor of same dtype as x.
- name(optional): It defines the name for the 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 a = tf.constant([. 2 , . 5 , . 7 , 1 ], dtype = tf.float64) b = tf.constant([. 1 , . 3 , 1 , 5 ], dtype = tf.float64) # Printing the input tensor print ( 'a: ' , a) print ( 'b: ' , b) # Calculating result res = tf.math.multiply(x = a, y = b) # Printing the result print ( 'Result: ' , res) |
Output:
a: tf.Tensor([0.2 0.5 0.7 1. ], shape=(4, ), dtype=float64) b: tf.Tensor([0.1 0.3 1. 5. ], shape=(4, ), dtype=float64) Result: tf.Tensor([0.02 0.15 0.7 5. ], shape=(4, ), dtype=float64)
Example 2: Complex number multiplication
Python3
# importing the library import tensorflow as tf # Initializing the input tensor a = tf.constant([ - 2 + 3j , - 5 + 4j , 7 + 2j , 1 + 7j ], dtype = tf.complex128) b = tf.constant([ - 1 + 2j , - 6 + 8j , 8 + 2j , 0 + 1j ], dtype = tf.complex128) # Printing the input tensor print ( 'a: ' , a) print ( 'b: ' , b) # Calculating result res = tf.math.multiply(x = a, y = b) # Printing the result print ( 'Result: ' , res) |
Output:
a: tf.Tensor([-2.+3.j -5.+4.j 7.+2.j 1.+7.j], shape=(4, ), dtype=complex128) b: tf.Tensor([-1.+2.j -6.+8.j 8.+2.j 0.+1.j], shape=(4, ), dtype=complex128) Result: tf.Tensor([-4. -7.j -2.-64.j 52.+30.j -7. +1.j], shape=(4, ), dtype=complex128)
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