**AttributeError: ‘Tensor’ object has no attribute ‘numpy’** errors because a parameter **run_eagerly** value is set as **False.** There are two versions of the TensorFlow module, Tensorflow 1. x and Tensorflow 2. x. In Tensorflow 1. x, we have to manually set this parameter, but in Tensorflow 2.0, it is, by default, **True.**

**Solution 1 : Enable eager_execution (Only for Tenorflow 1.x)**

If you are using TensorFlow 1. x, we need to explicitly invoke **eager_execution.**

```
tf.enable_eager_execution(config=None, device_policy=None,
execution_mode=None)
```

**Solution 2 : invoke run_functions_eagerly (For Tensorflow 2.x)**

Set the **tf.enable_eager_execution()** function to **True.**

`tf.config.run_functions_eagerly(run_eagerly)`

**Solution 3**

Another solution to **fix **the **AttributeError: ‘Tensor’ object has no attribute ‘numpy’ error, **convert a **Tensor** to a **NumPy** **array** using the **.numpy()** method of the **Tensor** **object**.

```
import tensorflow as tf
tensor = tf.constant([[11, 21], [19, 46]])
array = tensor.numpy()
print(array)
```

**Output**

`[[11, 21], [19, 46]]`

In this code, first, we imported the **tensorflow** **library **and defined a tensor using the **tf.constant() **method.

To convert a **tensor** to a **numpy** **array**, we used the **tensor.numpy()** function.

If you run the above code, we won’t get any error, instead, it will return this output: `'[[11, 21], [19, 46]]'`

.

That’s pretty much it.

Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.