**Diagram**

AttributeError: ‘module’ object has no attribute ‘mul’ error occurs because you **“use the mul attribute, which was renamed in version 2.0 of TensorFlow.”**

To fix the AttributeError: ‘module’ object has no attribute ‘mul’ error, use the **“tf.multiply()”** function instead of **“tf.mul()”** function.

**Reproduce the error**

```
import tensorflow as tf
# Define two tensors
a = tf.constant([1, 2, 3])
b = tf.constant([4, 5, 6])
# Multiply the tensors element-wise
result = tf.mul(a, b)
# Print the result
print(result.numpy())
```

**Output**

**How to fix it?**

Use **tf.multiply** instead of **tf.mul,** as the latter is not a valid attribute in the TensorFlow module (at least in recent versions). If you update your code to the tf.multiply() function, the error should be resolved!

```
import tensorflow as tf
# Define two tensors
a = tf.constant([1, 2, 3])
b = tf.constant([4, 5, 6])
# Multiply the tensors element-wise
result = tf.multiply(a, b)
# Print the result
print(result.numpy())
```

**Output**

`[ 4 10 18]`

That’s it!

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AttributeError: module ‘tensorflow’ has no attribute ‘variable_scope’

AttributeError: module ‘tensorflow’ has no attribute ‘layers’

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AttributeError: module ‘tensorflow’ has no attribute ‘ConfigProto’

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.