My job completes with no error. The logs show "accuracy", "auc", and other statistical measures of my model. ML-engine creates a package subdirectory, and a tar under that, as expected. But, there's no export directory, checkpoint, eval, graph or any other artifact that I'm accustom to seeing when I train locally. Am I missing something simple with the command I'm using to call the service?
gcloud ml-engine jobs submit training $JOB_NAME \
--job-dir $OUTPUT_PATH \
--runtime-version 1.0 \
--module-name trainer.task \
--package-path trainer/ \
--region $REGION \
-- \
--model_type wide \
--train_data $TRAIN_DATA \
--test_data $TEST_DATA \
--train_steps 1000 \
--verbose-logging true
The logs show this: model directory = /tmp/tmpS7Z2bq But I was expecting my model to go to the GCS bucket I defined in $OUTPUT_PATH.
I'm following the steps under "Run a single-instance trainer in the cloud" from the getting started docs.
Maybe you could show where and how you declare the $OUTPUT_PATH?
Also the model directory, might be the directory within the $OUTPUT_PATH where you could find the model of that specific Job.