I have been able to get other things working, but after several hours, I am a little lost.

For

# UNQ_C2

# GRADED FUNCTION: convolutional_block

I copied in the kernal sizes and strides from the example above, and am getting this error.

AssertionError Traceback (most recent call last)

in

12 assert type(A) == EagerTensor, “Use only tensorflow and keras functions”

13 assert tuple(tf.shape(A).numpy()) == (3, 2, 2, 6), “Wrong shape.”

—> 14 assert np.allclose(A.numpy(), convolutional_block_output1), “Wrong values when training=False.”

15 print(A[0])

16

AssertionError: Wrong values when training=False.

I know I can’t copy my code, but from what I understand, I did the parts right above it, and I can’t figure out what I am doing wrong. Is there a way to share part of my code without breaking the rules?

I am having the same issue with

# UNQ_C3

# GRADED FUNCTION: ResNet50

Where I feel like I edited the command lines, but am getting this error

Perhaps with this one, the error will be more obvious

AssertionError Traceback (most recent call last)

in

3 model = ResNet50(input_shape = (64, 64, 3), classes = 6)

4

----> 5 comparator(summary(model), ResNet50_summary)

/tf/W2A1/test_utils.py in comparator(learner, instructor)

14 def comparator(learner, instructor):

15 if len(learner) != len(instructor):

—> 16 raise AssertionError(f’Models does not have the same number of layers {len(learner)} != {len(instructor)}’)

17 for a, b in zip(learner, instructor):

18 if tuple(a) != tuple(b):

AssertionError: Models does not have the same number of layers 173 != 177

Any hints would be great - I’ve been stuck on these two for hours (I actually went and finished the assignment after this one and came back and am still stuck)

Thanks!