Although I wrote all the necessary codes and got the “All tests passed!” feedback on my Submission, the Submission rating is 0/100.
There is no feedback for why I got 0 points. The only feedback is “Error while grading submission. Please check your submission.”.
Although I was submitting at different times, the problem was still not solved.
Before each submissions I reset the kernel and rerun the codes.
When I pressed validate button, after a while following message shows up:
“Connection Failed: A connection to the notebook server could not be established. The notebook will continue trying to reconnect. Check your network connection or notebook server configuration.”
I would be very happy if this issue is dealt with.
Now I tried again and this time it gave the following error. I don’t know if This may help who trying to fix the problem.
[ValidateApp | INFO] Validating ‘/home/jovyan/work/submitted/courseraLearner/W3A2/Image_segmentation_Unet_v1.ipynb’
[ValidateApp | INFO] Executing notebook with kernel: python3
2021-04-25 22:18:00.734535: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library ‘libcudart.so.10.1’; dlerror: libcudart.so.10.1: cannot open shared object file: No such file or directory
2021-04-25 22:18:00.734575: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2021-04-25 22:18:02.956517: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library ‘libcuda.so.1’; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2021-04-25 22:18:02.956579: W tensorflow/stream_executor/cuda/cuda_driver.cc:312] failed call to cuInit: UNKNOWN ERROR (303)
2021-04-25 22:18:02.964107: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (somehost): /proc/driver/nvidia/version does not exist
2021-04-25 22:18:02.964679: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-04-25 22:18:03.057115: I tensorflow/core/platform/profile_utils/cpu_utils.cc:104] CPU Frequency: 3000000000 Hz
2021-04-25 22:18:03.058295: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f4935709db0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-04-25 22:18:03.058349: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
2021-04-25 22:18:28.072354: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:172] Filling up shuffle buffer (this may take a while): 459 of 500
2021-04-25 22:18:28.927300: I tensorflow/core/kernels/data/shuffle_dataset_op.cc:221] Shuffle buffer filled.
[ValidateApp | ERROR] Timeout waiting for execute reply (30s).
[ValidateApp | ERROR] Interrupting kernel
2021-04-25 22:19:10.416955: W tensorflow/core/kernels/data/cache_dataset_ops.cc:798] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset will be discarded. This can happen if you have an input pipeline similar to dataset.cache().take(k).repeat(). You should use dataset.take(k).cache().repeat() instead.
2021-04-25 22:19:10.634776: W tensorflow/core/kernels/data/cache_dataset_ops.cc:798] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset will be discarded. This can happen if you have an input pipeline similar to dataset.cache().take(k).repeat(). You should use dataset.take(k).cache().repeat() instead.
Success! Your notebook passes all the tests.
Thanks for your elaborate documentation. As mentioned here I have reported this issue to people working on the backend of deeplearning.ai. I have included this topic in my report.
Hey @hanseref if you look at the very last line it says all tests passed. You should have gotten a full score. Can you confirm ?
As for the message itself, I suspect it is because code blocks have timeout on them, when it runs out it displays back as this log you are seeing, but also passing all the tests. The reason you are able to pass the tests despite this log is because these code blocks (against which you are getting this) are not required for grading.
Although It writes at the last line “Success! Your notebook passes all the tests.”, the scor result was 0/100.
btw, I submitted my work 7 times until now, 6 times of 7 I got the error which is “Error while grading submission. Please check your submission.”
Thanks.
