Updating TensorFlow variables within a session in Python
Python TensorFlow Basic: Exercise-11 with Solution
Write a Python program that demonstrates how to update a TensorFlow variable within a session.
Sample Solution:
Python Code:
import tensorflow as tf
# Create a TensorFlow variable
# Tensors are multi-dimensional arrays with a uniform type (called a dtype ).
initial_value = 2.0
print("Initial Variable:",initial_value)
variable_tensor = tf.Variable(initial_value)
# Define a function that updates the variable
@tf.function
def update_variable(new_value):
variable_tensor.assign(new_value)
# Update the variable within the function
new_value = 7.0
update_variable(new_value)
# Print the updated value
print("Updated Variable:", variable_tensor.numpy())
Output:
Initial Variable: 2.0 Updated Variable: 7.0
Explanation:
In the exercise above -
- Create a TensorFlow variable named “variable_tensor” with an initial value of 3.0.
- Define a Python function “update_variable()” and decorate it with @tf.function. This decorator allows you to define a function containing TensorFlow operations.
- Within the “update_variable()” function, we use the assign method to update the variable's value with a new value.
- Call the "update_variable()" function with a new value of 5.0 to update the variable.
- Finally, we print the updated variable value.
Python Code Editor:
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