Unable to get the result from Google machine learning Cloud REST API - machine-learning

Question

I am trying to run a job using Google Cloud Machine Learning REST-API ml.jobs.project.create
The latest job that I submitted has job id 'drivermonitoring20180109335'. Here on completion of the job, message 'job completed successfully' is displayed but I cannot see any desired output file in the specified location. Output logs can be seen in fig1
Also I would like to keep in-front of you my few observations while running this job id:
i) Running the job took very less time in comparison to any other job that I executed before.
ii) While running jobs before, every job earlier was executed via two different tasks viz a)master-replica-0 and b)service (refer fig2) but this job didn't have master-replica-0 task(refer fig3) I tried to Google the issue, but was unable to find any solution related to the issue.
So I can infer that the task that I was trying to run is being scheduled but the python script that I am trying to run is never scheduled to be executed.
Kindly let me know if you require more screenshots or if you want to have a look at the project structure to help with the issue.
Thanks in advance.
EDIT 1: Added JSON while making API call
POST https://ml.googleapis.com/v1/projects/drivermonitoringsystem/jobs?key={YOUR_API_KEY}
{
"trainingInput": {
"pythonModule": "trainer.retrain",
"args": [
"--bottleneck_dir=ModelTraining/tf_files/bottlenecks \
--model_dir=ModelTraining/tf_files/models/ \
--architecture=mobilenet_0.50_224 \
--output_graph=gs://<BUCKET_NAME>/tf_files/retrained_graph.pb \
--output_labels=gs://<BUCKET_NAME>/tf_files/retrained_labels.txt \
--image_dir=gs://<BUCKET_NAME>/dataset224x224/"
],
"region": "us-central1",
"packageUris": [
"gs://<BUCKET_NAME>/ModelTraining4.tar.gz"
],
"jobDir": "gs://<BUCKET_NAME>/tf_files/",
"runtimeVersion": "1.4"
},
"jobId": "job_id201801101535"
}

Answer 1

I have just run myself some sample jobs using both the gcloud command and the REST API, and everything has just worked fine in both of the cases. It looks like, in your case, the job was never executed, as there is no cluster created for processing the job itself (that is why master-replica-0 is missing).
The jobs that you had run previously and which had worked were launched also using the REST API, or instead with gcloud or a Client Library?
Here I share an example JSON I used when making the API call to ml.projects.jobs.create through the API Explorer link you shared, I suggest you try adapting it to your requirements and check if you got any missing field:
POST https://ml.googleapis.com/v1/projects/<YOUR_PROJECT>/jobs?key={YOUR_API_KEY}
{
"jobId": "<JOB_ID>",
"trainingInput": {
"jobDir": "gs://<LOCATION_TO_STORE_OUTPUTS>",
"runtimeVersion": "1.4",
"region": "<REGION>",
"packageUris": [
"gs://<PATH_TO_YOUR_TRAINER>/trainer-0.0.0.tar.gz"
],
"pythonModule": "<PYTHON_MODULE_TO_RUN>",
"args": [
"--train-files",
"gs://<PATH_TO_YOUR_TRAINING_DATA>/data.csv",
"--eval-files",
"gs://<PATH_TO_YOUR_TEST_DATA>/test.csv",
"--train-steps",
"100",
"--eval-steps",
"10",
"--verbosity",
"DEBUG"
]
}
}
Change TrainingInput to PredictionInput (and the appropriate child fields) if you are trying to run a prediction job instead of a training one, as in this example.