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Adventures using keras on Google's Cloud ML Engine
with file_io.FileIO('model.h5', mode='r') as input_f:
with file_io.FileIO(job_dir + '/model.h5', mode='w+') as output_f:
The above throws a UnicodeDecodeError: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte
as the .h5 model file is a bytes file. To correct this issue use bytes mode for reading/writing using FileIO:
with file_io.FileIO('model.h5', mode='rb') as input_f:
with file_io.FileIO(job_dir + '/model.h5', mode='wb+') as output_f:
In your example, you setup the logPath but don't use it. Where is logPath used and how does it enable the use of tensorboard in your example?
Awesome example otherwise!
Thanks.
Sorry for disturbing. I have trial account on Google Cloud and got this error when a job was started:
~$ export JOB_NAME="mnist_mlp_train5_$(date +%Y%m%d_%H%M%S)"
~$ export JOB_DIR=gs://$BUCKET_NAME/$JOB_NAME
~$ export REGION=us-east1
~$ gcloud ml-engine jobs submit training $JOB_NAME --job-dir $JOB_DIR --runtime-version 1.0 --module-name trainer.mnist_m
lp --package-path ./trainer --region $REGION -- --train-file gs://$BUCKET_NAME/data/mnist.pkl
Bucket storage:
~$ gsutil ls gs://$BUCKET_NAME/data
gs://.../data/mnist.pkl
Maybe bucket storage is not supported in the trial mode?
Please help me to fix this error.
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