Course 4 Week 1 project 2

Course Q&A Deep Learning Specialization Convolutional Neural Networks
1

so on the happy_model i have it outputing the correct items in the summary, but it outputing two lines that are not compared in the test so i am failing for test error. here is my summary output and the error
“”"
[‘InputLayer’, [(None, 64, 64, 3)], 0]
[‘ZeroPadding2D’, (None, 70, 70, 3), 0, ((3, 3), (3, 3))]
[‘Conv2D’, (None, 64, 64, 32), 4736, ‘valid’, ‘linear’, ‘GlorotUniform’]
[‘BatchNormalization’, (None, 64, 64, 32), 128]
[‘Activation’, (None, 64, 64, 32), 0]
[‘MaxPooling2D’, (None, 32, 32, 32), 0, (2, 2), (2, 2), ‘valid’]
[‘Flatten’, (None, 32768), 0]
[‘Dense’, (None, 1), 32769, ‘sigmoid’]
Test failed
Expected value

[‘ZeroPadding2D’, (None, 70, 70, 3), 0, ((3, 3), (3, 3))]

does not match the input value:

[‘InputLayer’, [(None, 64, 64, 3)], 0]

AssertionError Traceback (most recent call last)
in
12 [‘Dense’, (None, 1), 32769, ‘sigmoid’]]
13
—> 14 comparator(summary(happy_model), output)

~/work/release/W1A2/test_utils.py in comparator(learner, instructor)
20 “\n\n does not match the input value: \n\n”,
21 colored(f"{a}", “red”))
—> 22 raise AssertionError(“Error in test”)
23 print(colored(“All tests passed!”, “green”))
24

AssertionError: Error in test
“”"

Anyone have any ideas how i can get the InputLayer and Activation?

2

ok i figured out how to get rid of the Activation element in the summary, so the error for that one is gone, but i still cannot figure out how to get ride of the InputSummary element in the summary. Please help

3

Hi dbiber,

Instead of using an Input layer you can use input_shape as a parameter in ZeroPadding2D. You can have a look at this thread:

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