TensorFlow GradCAM – model.fit() – ValueError: Shapes (None, 1) and (None, 2) are incompatible


As part of assignment 4, Coursera CV TF course, my code fails in model.fit()

# shuffle and create batches before training


with error:

ValueError: Shapes (None, 1) and (None, 2) are incompatible

Any hint at where problem might come from? I suspect bad format or type for train_batches:

train_data = tfds.load('cats_vs_dogs', split='train[:80%]', as_supervised=True) 
augmented_training_data = train_data.map(augmentimages)
train_batches = augmented_training_data.batch(32)


Although I am not familiar with the exact code of the architecture, I suspect it is this line:


You may be using categorical_crossentropy instead of binary_crossentropy for binary classification with 1 neuron at the output, but this is only an assumption considering I do not have the code and architecture to look at; in fact I am 99% that the issue is from there.

Answered By – Timbus Calin

Answer Checked By – Mildred Charles (AngularFixing Admin)

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