How to multiply tensors using Tensorflow
Tensorflow is an open-source Python framework that is mainly used to build and train machine learning models. Tensorflow provides a range of functions to deal with data structures, such as single dimension or multi-dimensional arrays known as tensors.
Tensor multiplication is an important part of building machine learning models, as all data (images or sounds) is represented in the form of tensors. The tensorflow.math.multiply() function is used for this purpose.
Syntax
tensorflow.math.multiply(x, y, name)
Parameters
x: Input tensor to be multiplied.y: Input tensor that multiplies.ymust have the same data type asx.name: Defines the name of the operation. This parameter is optional.
Return value
The function returns a tensor object with the data type of the input tensors.
Code
#import libraryimport tensorflow as tf#define the input tensorsx=tf.constant([4,8,1,5],dtype=tf.int64)y=tf.constant([9,3,7,6],dtype=tf.int64)#print input tensorsprint('x: ',x)print('y: ',y)#multiply the tensorsresult=tf.math.multiply(x,y)#print the resultprint('Result: ',result)
Output
The code above will give the following output.
x: tf.Tensor([4 8 1 5], shape=(4,), dtype=int64)
y: tf.Tensor([9 3 7 6], shape=(4,), dtype=int64)
Result: tf.Tensor([36 24 7 30], shape=(4,), dtype=int64)