Introduction
Are you a beginner in the exciting world of deep learning and trying to build your first neural network using Keras? If so, you might have come across an error message that says “AttributeError: ‘int’ object has no attribute ‘lower'”. Don’t worry; you’re not alone! In this blog post, we’ll delve into the details of this error and provide you with a step-by-step solution to fix it. Let’s get started!
Understanding the Error
The error message you encountered is a common one, and it typically occurs when you mistakenly provide an argument to the Flatten layer in Keras. The Flatten layer is responsible for reshaping the input data, but it doesn’t require any arguments specifying the output shape. By providing an argument, you inadvertently triggered this error.
The Solution
To resolve this error, let’s modify the code snippet you provided. Instead of passing the argument to the Flatten layer, we’ll reshape the data before feeding it into the model. Here’s an updated version of the code:
code
import tensorflow.keras.layers as l
h = i = l.Input(shape=(10, 5))
h = l.Flatten()(h) # Reshape the data correctly
o = l.Dense(50)(h)
model = keras.Model(inputs=i, outputs=o)
model.compile(optimizer='adam', loss='mse')
With this modification, the model should compile without any issues, and you can proceed with training your neural network.
Conclusion
In this blog post, we addressed the ‘AttributeError: ‘int’ object has no attribute ‘lower” error that often occurs when working with the Flatten layer in Keras. We provided a detailed explanation of the error and a step-by-step solution to fix it. Remember, as a beginner in deep learning, encountering errors is a natural part of the learning process. Don’t get discouraged! By understanding and resolving these errors, you’ll gain valuable insights and improve your skills in building neural networks.
We hope this article has been helpful to you in your deep learning journey. If you have any questions or need further assistance, please don’t hesitate to leave a comment below.
