AttributeError: 'int' object has no attribute 'shape', Course2, Week2

Course Q&A Deep Learning Specialization Improving Deep Neural Networks: Hyperparameter tun
1 
<ipython-input-63-2caeb7a27c84> in <module>
     15     assert np.sum(np.sum(mini_batches[k][0] - mini_batches[k][0][0], axis=0)) == ((nx * (nx - 1) / 2 ) * mini_batch_size), "Wrong values. It happens if the order of X rows(features) changes"
     16 if ( m % mini_batch_size > 0):
---> 17     assert mini_batches[n_batches - 1][0].shape == (nx, m % mini_batch_size), f"Wrong shape in the last minibatch. {mini_batches[n_batches - 1][0].shape} != {(nx, m % mini_batch_size)}"
     18 
     19 assert np.allclose(mini_batches[0][0][0][0:3], [294912,  86016, 454656]), "Wrong values. Check the indexes used to form the mini batches"

AttributeError: 'int' object has no attribute 'shape'```

I get the above error in minibatch implementation. This was asked before but not solved.
2

type(mini_batches[n_batches - 1][0]) should be numpy.ndarray. Python int object doesn’t have shape attribute and hence the problem.

3

I understand the error source, I just don’t understand how to get rid of it. Is the validation code incorrect or does my implementation of how I deal with the last batch buggy?

4

The last 2 statements are wrong since you’re not creating mini batches but scalars that represent the size of mini batches.

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