CloudML does not log epoch progress (Batch stats missing) The 2019 Stack Overflow Developer Survey Results Are In“gcloud app logs tail” shows week old dataTensorflow dequeue is very slow on Cloud MLWhat does global step mean?gcloud job can't access my files, either they are in GCS or in my cloud shellTensorflow file_io.read_file_to_string says unexpected keyword argument binary_modecloudml R package--bash errors prevent it workingtf.datasets input_fn getting error after 1 epochTraining R Keras Model using cloudml failsSpeeding up TFRecords feed into Keras model on CloudML for GPUSlow performance after syncing storage bucket with gcsfuse
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CloudML does not log epoch progress (Batch stats missing)
The 2019 Stack Overflow Developer Survey Results Are In“gcloud app logs tail” shows week old dataTensorflow dequeue is very slow on Cloud MLWhat does global step mean?gcloud job can't access my files, either they are in GCS or in my cloud shellTensorflow file_io.read_file_to_string says unexpected keyword argument binary_modecloudml R package--bash errors prevent it workingtf.datasets input_fn getting error after 1 epochTraining R Keras Model using cloudml failsSpeeding up TFRecords feed into Keras model on CloudML for GPUSlow performance after syncing storage bucket with gcsfuse
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Why doesn't cloud ML log epoch progress?
The progress appears only once the epoch is completed fully as so:
However, while the epoch is running, we get:
Now the above was just a test, the real dataset has 100x more data than the first example.
I can see that in the first example, it takes ~ 15s per epoch. So I would expect 1500s per epoch on full dataset. However, it just seems to run forever and there is NO LOGGING to see what is actually happening.
Locally, we get a moving bar which fills up as the batches are processed, so why doesn't CLOUDML log batch progress?
google-cloud-platform google-cloud-ml
add a comment |
Why doesn't cloud ML log epoch progress?
The progress appears only once the epoch is completed fully as so:
However, while the epoch is running, we get:
Now the above was just a test, the real dataset has 100x more data than the first example.
I can see that in the first example, it takes ~ 15s per epoch. So I would expect 1500s per epoch on full dataset. However, it just seems to run forever and there is NO LOGGING to see what is actually happening.
Locally, we get a moving bar which fills up as the batches are processed, so why doesn't CLOUDML log batch progress?
google-cloud-platform google-cloud-ml
add a comment |
Why doesn't cloud ML log epoch progress?
The progress appears only once the epoch is completed fully as so:
However, while the epoch is running, we get:
Now the above was just a test, the real dataset has 100x more data than the first example.
I can see that in the first example, it takes ~ 15s per epoch. So I would expect 1500s per epoch on full dataset. However, it just seems to run forever and there is NO LOGGING to see what is actually happening.
Locally, we get a moving bar which fills up as the batches are processed, so why doesn't CLOUDML log batch progress?
google-cloud-platform google-cloud-ml
Why doesn't cloud ML log epoch progress?
The progress appears only once the epoch is completed fully as so:
However, while the epoch is running, we get:
Now the above was just a test, the real dataset has 100x more data than the first example.
I can see that in the first example, it takes ~ 15s per epoch. So I would expect 1500s per epoch on full dataset. However, it just seems to run forever and there is NO LOGGING to see what is actually happening.
Locally, we get a moving bar which fills up as the batches are processed, so why doesn't CLOUDML log batch progress?
google-cloud-platform google-cloud-ml
google-cloud-platform google-cloud-ml
asked Mar 8 at 11:16
GRSGRS
3551830
3551830
add a comment |
add a comment |
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