Python TensorFlow matrix initialization and print

Last update on August 28 2025 12:34:52 (UTC/GMT +8 hours)

Python TensorFlow Basic: Exercise-8 with Solution

Write a Python program that defines a TensorFlow variable to store a matrix of random values. Initialize and print the variable.

Sample Solution:

Python Code:

import tensorflow as tf

# Define the shape of the matrix
matrix_shape = (3, 3)

# Create a TensorFlow variable with random values
# Tensors are multi-dimensional arrays with a uniform type (called a dtype ).
random_matrix = tf.Variable(tf.random.normal(shape=matrix_shape))

# Print the initialized variable
print("Initialized Variable:")
print(random_matrix.numpy())

Output:

Initialized Variable:
[[-0.580494    0.07652978 -0.5241451 ]
 [ 1.2946662   0.0206589  -1.4023237 ]
 [ 0.16084932 -1.0415876   1.2840588 ]]

Explanation:

In the exercise above -

import tensorflow as tf - This line imports the TensorFlow library.
matrix_shape = (3, 3) - Define the shape of the matrix.
random_matrix = tf.Variable(tf.random.normal(shape=matrix_shape)) - Create a TensorFlow variable with random values.

tf.random.normal(shape=matrix_shape) generates random values following a normal (Gaussian) distribution with the specified shape (in this case, a 3x3 matrix).
tf.Variable() is used to create a TensorFlow variable that can be updated during training. We initialize it with the random values.

print(random_matrix.numpy()) - Retrieve the values stored in the TensorFlow variable. In TensorFlow 2.x with eager execution, we can access the values directly using .numpy().

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