Had the same issue for C4W1A2
Thanks for letting us know @Jh_K, please refer to my earlier reply for a workaround.
Raymond
Great! Problem solved. Thank you
Thanks @rmwkwok . The workaround is helpful. I am able to save the files now. Thanks
Also the same issue, I assumed there should be announcement of some kind to not even try completing any assignments until it is resolved?
Hi, folks!
If this temporary hack didn’t work for you, kindly refer to that post . You will need to submit your info as mentioned there.
Best,
Saif.
We can see that several days passed without solution.
@Associacao_Laborator @VikingMonkey Have you tried this?
Hi, yes it worked. Thx!
Today I have no problem but I got a new problem in Art_Generation_with_Neural_Style_Transfer exercice. The kernel die here:
# Assign the content image to be the input of the VGG model.
# Set a_C to be the hidden layer activation from the layer we have selected
preprocessed_content = tf.Variable(tf.image.convert_image_dtype(content_image, tf.float32))
a_C = vgg_model_outputs(preprocessed_content)
In fact, it dies after executin the cell:
content_target = vgg_model_outputs(content_image) # Content encoder
style_targets = vgg_model_outputs(style_image) # Style encoder
It doesn’t solve the problem. I had an exercise downstream that I was not able to test. I submitted without that final test but everything turned to be ok, I passed with 100%.
Ok, it sounds like all your “graded” functions are correct, but there may be something else going wrong. E.g. did you add any debugging print statements in any of the lower level functions that get called from the higher level loops? That would cause the memory image of the notebook to grow quickly and that’s one possible thing that can cause the kernel to die.
Hi. I didn’t do any debugging.
Please show us a screenshot of what it looks like when it fails, including the output of the cell that was running at the time …
Above I put the content of the cell that results in a problem. What I see is a red notification saying the kernel is dead. That cell that causes the trouble has an output that seems correct but the output of the next cell is the result of the kernel having died, not recognizing functions, etc, namely tf.