I trying to use this https://cloud.google.com/ml/reference/rest/v1beta1/projects/predict function.
By following this https://cloud.google.com/ml/docs/quickstarts/prediction example I uploaded deployable version of mnist code, created model and version for it. Now I want to get some prediction results from it from python code.
By reading this function description I don't understand how I supposed to run it. I don't see where is it's parameters description and how they should look like.
For example I used this code to create learning task:
credentials = GoogleCredentials.get_application_default()
ml = discovery.build('ml','v1beta1', credentials=credentials)
projectID = 'projects/{}'.format('testml')
jobDict = { 'jobId': 'test_job_3', 'trainingInput': { 'scaleTier': 'BASIC', 'packageUris': [ 'gs://testml-ml/
cloudmldist/1479282298/trainer-0.0.0.tar.gz' ], 'pythonModule': 'trainer.task', 'args': [ '--train_dir=gs://testml-ml/
test_job3_results' ], 'region': 'us-central1' } }
request = ml.projects().jobs().create(parent = projectID, body = jobDict)
response = request.execute()
I were calling jobs.create function with parameters: parent and body.
I don't understand from the documentation what parameters is needed for projects.predict function and how to build them. There is written about output format, but input arguments skipped.
Perhaps you're confused because predict takes a wrapper as the argument, that HTTP body you see listed. This is the wrapper, in HTTP request format, containing a list of instances. The format of the instances is determined by the model you built; predict is simply a communication channel. You put that after "?data=" in your prediction request.