To perform elementwise multiplication on tensors, you can use either of the following:

`a*b`

`tf.multiply(a, b)`

Here is a full example of elementwise multiplication using both methods.

import tensorflow as tf import numpy as np # Build a graph graph = tf.Graph() with graph.as_default(): # A 2x3 matrix a = tf.constant(np.array([[ 1, 2, 3], [10,20,30]]), dtype=tf.float32) # Another 2x3 matrix b = tf.constant(np.array([[2, 2, 2], [3, 3, 3]]), dtype=tf.float32) # Elementwise multiplication c = a * b d = tf.multiply(a, b) # Run a Session with tf.Session(graph=graph) as session: (output_c, output_d) = session.run([c, d]) print("output_c") print(output_c) print("\noutput_d") print(output_d)

Prints out the following:

```
output_c
[[ 2. 4. 6.]
[ 30. 60. 90.]]
output_d
[[ 2. 4. 6.]
[ 30. 60. 90.]]
```