# TensorFlow constant and variable operations in Python

## Python TensorFlow Basic: Exercise-10 with Solution

Write a Python program that creates a TensorFlow constant and a TensorFlow variable. Add, subtract, multiply and divide them and print the result.

**Sample Solution:**

**Python Code:**

```
import tensorflow as tf
# Create a TensorFlow constant and a TensorFlow variable
# Tensors are multi-dimensional arrays with a uniform type (called a dtype ).
constant_ts = tf.constant(4.0)
initial_value = 5.0
variable_ts = tf.Variable(initial_value)
# Perform mathematical operations
add_result = constant_ts + variable_ts
subtract_result = constant_ts - variable_ts
multiply_result = constant_ts * variable_ts
divide_result = constant_ts / variable_ts
# Print the results
print("Constant:", constant_ts.numpy())
print("Variable (initial value):", initial_value) # Variables are not initialized explicitly in TensorFlow 2.x
print("Addition Result:", add_result.numpy())
print("Subtraction Result:", subtract_result.numpy())
print("Multiplication Result:", multiply_result.numpy())
print("Division Result:", divide_result.numpy())
```

Output:

Constant: 4.0 Variable (initial value): 5.0 Addition Result: 9.0 Subtraction Result: -1.0 Multiplication Result: 20.0 Division Result: 0.8

**Explanation:**

In the exercise above -

- Create a TensorFlow constant named constant_tensor with the value 5.0.
- Create a TensorFlow variable named variable_tensor with an initial value of 3.0.
- Perform addition, subtraction, multiplication, and division operations between the constant and the variable.
- Initialize the variable using tf.compat.v1.global_variables_initializer().run() (for TensorFlow 2.x, use tf.compat.v1.global_variables_initializer().run()).
- Finally, we print the values of the constant, the initialized variable, and the results of mathematical operations.

**Python Code Editor:**

**Previous:** Understanding TensorFlow variables and constants.

**Next:** Updating TensorFlow variables within a session in Python.

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