Week 1 Course 1 - Define output layers of the model

Hi, im getting this error

AttributeError Traceback (most recent call last)
----> 1 utils.test_final_model(final_model)

~/work/release/W1_Assignment/utils.py in test_final_model(final_model)
273 {
274 “name”: “layer_3_activation_check”,
→ 275 “result”: test_output.layers[4].activation,
276 “expected”: tf.keras.activations.sigmoid,
277 “error_message”: ‘wine_quality layer has an incorrect activation. Please check implementation.’

AttributeError: ‘NoneType’ object has no attribute 'layers

from what the error message says, the error would be that the activation function of wine_quality is not correct, but that line of code, according to the statement, does not require defining the activation. I hope you can help me, thank you!

I think you filed this message in the incorrect category. You filed it against DLS Course 1. I am not familiar with any assignments in any of the DLS courses that deal with “wine quality”.

Yes, sorry i was trying to post it in the Tensor Flow specialization.

You can use the little “Edit Pencil” icon next to the title to move it, rather than recreating it from scratch.

Oh, sorry, I see you already did that. Great!

Hi there,

There must activations used for the layers and the output of the model. This is a normal structure of neural network.