# Tensorflow 2 – Using tf.Variable examples

Below are some practical examples of using tf.Variable, which can help you create modifiable tensors in Tensorflow 2.

## Example 1: Creating a New Variable and Assigning New Value

The code:

``````import tensorflow as tf

a = tf.Variable([
[1, 2],
[3, 4]
])
print(a)

# Assign a new value to a
a.assign(value=[
[5, 6],
[7, 8]
])

print(a)``````

Output:

``````<tf.Variable 'Variable:0' shape=(2, 2) dtype=int32, numpy=
array([[1, 2],
[3, 4]], dtype=int32)>
<tf.Variable 'Variable:0' shape=(2, 2) dtype=int32, numpy=
array([[5, 6],
[7, 8]], dtype=int32)>``````

The code:

``````import tensorflow as tf

test_var = tf.Variable([
[0, 0],
[1, 2]
])

# Add a value to test_var
[10, 10],
[0, 0]
])

print(test_var)

# Subtract a value from test_var
test_var.assign_sub([
[5, 5],
[1, 0]
])

print(test_var)``````

Output:

``````<tf.Variable 'Variable:0' shape=(2, 2) dtype=int32, numpy=
array([[10, 10],
[ 1,  2]], dtype=int32)>
<tf.Variable 'Variable:0' shape=(2, 2) dtype=int32, numpy=
array([[5, 5],
[0, 2]], dtype=int32)>``````

## What’s Next?

We’ve gone through a few examples of using tf.Variable. At this point, you should get a better understanding and feel more comfortable when working with it. This knowledge is essential and you will see it a lot. If you’d like to learn more about Python and machine learning stuff, take a look at the following articles:

You can also check out our Machine Learning category page or Python category page for more tutorials and examples.

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