Hi everyone, I am stuck on the final assignment of the specialization. Exercises 1-6 are passing, but Exercise 7 is failing as follows: # UNIT TEST Decoder_test(Decoder, create_look_ahead_mask, create_padding_mask) --------------------------------------------------------------------------- Assert…

I added the below lines of code, at the relevant places: print(f'x after word embeddings:{x}') print(f'x after scale embeddings:{x}') print(f'x after positional encodings:{x}') print(f'x after dropout:{x}') print(f'final x:{x}') Here is the output: x after word embeddings:[[[-0.02472718 -0.038954…

One more thing: I tried print the output x and got this, which looks very close to the desired values, but not exact: x= tf.Tensor( [[[-1.3821416 1.4325931 0.10909806 -0.15954943] [-0.36006218 -0.5374867 -0.81191266 1.7094616 ] [-0.3749532 -0.8820826 -0.44182518 1.6988611 ]] [[-1.158…

Thanks for the test values! I inserted the print statements and the 1st errors occurred in “x after dropout”. I had a look at my code for the dropout layer and compared it with the version from an earlier function. I made a tiny change to the starter code and I just got “All tests passed”. I replac…

Whether += is correct depends on how you initialize the x value.

My starter code is this: # apply a dropout layer to x # use `training=training` x = None I don’t know how you get different. Anyways, congrats on finishing the course.

I rebooted the lab and checked the starter code. Yes, you are right. I must have accidentally copied x = None from the previous starter code.

thank you, super helpful. I had incorrect value in the scaling multiplier.

C5 Week 4 Exercise 7: AssertionError: Wrong values in outd

Course Q&A Deep Learning Specialization Sequence Models

saifkhanengr May 28, 2023, 1:24pm 8

Hmm. In the future, if you need a fresh copy of an assignment, you can do this.

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C5 Week 4 Exercise 7: AssertionError: Wrong values in outd

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