**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

#    
#  Parameters
- `x`: Input tensor to be multiplied. 
- `y`: Input tensor that multiplies. `y` must have the same data type as `x`.
- `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 library
import tensorflow as tf

#define the input tensors
x=tf.constant([4,8,1,5],dtype=tf.int64)
y=tf.constant([9,3,7,6],dtype=tf.int64)

#print input tensors
print('x: ',x)
print('y: ',y)

#multiply the tensors
result=tf.math.multiply(x,y)

#print the result
print('Result: ',result)

### Output
The code above will give the following output.
```Python
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)
```

How to multiply tensors using Tensorflow

Tensorflow’s tensorflow.math.multiply() function multiplies tensors, essential for machine learning models, ensuring operational consistency with input types.