Performing matrix multiplication with TensorFlow in Python

Python TensorFlow Building and Training a Simple Model: Exercise-3 with Solution

Write a Python program that creates a TensorFlow operation to perform matrix multiplication between two tensors.

Sample Solution:

Python Code:

import tensorflow as tf

# Create two example tensors
ts1 = tf.constant([[1, 3], [5, 7]], dtype=tf.float32)
ts2 = tf.constant([[2, 4], [6, 8]], dtype=tf.float32)

print("Original matrices")
print(ts1.numpy())
print(ts2.numpy())
# Perform matrix multiplication
result_tensor = tf.matmul(ts1, ts2)

# Print the result
print("\nMatrix Multiplication Result:")
print(result_tensor.numpy())

Output:

Original matrices
[[1. 3.]
 [5. 7.]]
[[2. 4.]
 [6. 8.]]

Matrix Multiplication Result:
[[20. 28.]
 [52. 76.]]

Explanation(Output):

In the exercise above -

• Import TensorFlow as tf.
• Create two example tensors, ts1 and ts2, using tf.constant(). These tensors represent 2x2 matrices.
• Perform matrix multiplication between tensor1 and tensor2 using tf.matmul(). This operation computes the dot product of the two matrices.
• Finally, we print the matrix multiplication result.

Go to:

• TensorFlow building and training a simple model Exercises Home ↩
• Python TensorFlow Exercises Home ↩

PREV : Defining a TensorFlow constant Tensor for Neural Network Weights.
NEXT : Building a Feedforward neural network in TensorFlow.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.