Google ML Engine: Submit a training job via REST API - google-cloud-ml

Question

I'm trying to start a training job via a REST API request using the Census example project from Googles github. I'm able to submit a job, but it always fails as I'm unable to state where the training and evaluation (testing) files are kept, and the documentation is really lacking on this - it just states args[]. When I check the logs in Google ML, the following errors appear:
task.py: error: the following arguments are required: --train-files, --eval-files
The replica master 0 exited with a non-zero status of 2.
This is my formulated REST request:
{
"jobId": "training_12",
"trainingInput": {
"scaleTier": "BASIC",
"packageUris": ["gs://MY_BUCKET/census.tar.gz"],
"pythonModule": "trainer.task",
"args": ["--train_files gs://MY_BUCKET/adult.data.csv", "--eval_files gs://MY_BUCKET/adult.test.csv"],
"region": "europe-west1",
"jobDir": "gs://MY_BUCKET/",
"runtimeVersion": "1.4",
"pythonVersion": "3.5"
}
}
Under the args I've tried many different ways of stating where the train and eval files are, but I have been unable to get it to work. Just for clarification, I have to use the REST API for this use case - not the CLI.
Thanks
-- Update --
I've tried to have the args as --train-files and --eval-files, this still does not work.
-- Update 2 --
I've been able to solve this problem by formulating the args as:
"args": [
"--train-files",
"gs://MY_BUCKET/adult.data.csv",
"--eval-files",
"gs://MY_BUCKET/adult.test.csv",
"--train-steps",
"100",
"--eval-steps",
"10"],
Now, I'm getting a new error and the logs don't seem to give any more information: "The replica master 0 exited with a non-zero status of 1."
The logs have actually done some training, and I suspect this is something related to the saving of the job, but I'm unsure.

Answer 1

I see that you already found the solution to your issue with args when submitting a Training Job in Google Cloud ML Engine. However, let me share with you some documentation pages where you will find all the required information regarding this topic.
In this first page about formatting configuration parameters (under the Python tab), you can see that the args field is populated like:
'args': ['--arg1', 'value1', '--arg2', 'value2'],
Therefore, the correct approach to define args is writing them as key-value pairs as independent strings.
Additionally, this other page containing general information about Training jobs, explains that the training service accepts arguments as a list of strings with the format:
['--my_first_arg', 'first_arg_value', '--my_second_arg', 'second_arg_value']
That is the reason why the last formatting you shared (below) is the correct one:
"args": [
"--train-files",
"gs://BUCKET/FILE",
"--eval-files",
"gs://BUCKET/FILE_2",
"--train-steps",
"100",
"--eval-steps",
"10"]