[FIXED] ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 2, the array at index 0 has size 3

Issue

I am getting the error ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 2, the array at index 0 has size 3 and the array at index 1 has size 1 while running the below code.

for i in range(6):
    print('current b', current_batch)
   
    current_pred = model.predict(current_batch)[0]
    print('current pred', current_pred)
    
    test_predictions.append(current_pred) 
    print('current batch', current_batch)
    print('current batch => ', current_batch[:,1:,:])
    
    current_batch = np.append(current_batch[:,1:,:], [[current_pred]], axis=1)

getting this error

Can anyone please explain me why this is happening.

Thanks,

Solution

As the traceback shows, np.append is actually using np.concatenate. Did you read (study) the docs for either function? Understand what they say about dimensions?

From the display [[current_pred]], converted to array will be (1,1,1) shape. Do you understand that?

current_batch[:,1:,:] is, as best I can tell from the small image (1,5,3)

You are asking to join on axis 1, which is 1 and 5, ok. But it's saying that the last dimension, axis 2, doesn't match. That 1 does not equal 3. Do you understand that?

List append as you do with test_predictions.append(current_pred) works well in an iteration.

np.append does not work well. Even when it works, it is slow. And here it doesn't work, because you aren't taking sufficient care to match dimensions.

Answered By - hpaulj