Once the model is deployed into AML compute, the UI doesn't help much on how to consume it and try the service. It simply provides an URI, but a user who just deployed it won't be able to try it unless he invests time on researching docs from scratch.
This is a clear paper-cut because it is blocking the path for a fast getting started experience.
This is the only info provided so far for consumption:
That "Consume" page section should help on sample code on the following areas and showing client code for Python apps, .NET apps, Java apps, Node-JS apps, etc.:
End-user app consuming the model service end-point (web app, etc.)
How to load the service object from the URI
How to consume it with sample data and code similar to the following:
import json
import pandas as pd
# the sample below contains the data for an employee that is not an attrition risk
sample = pd.DataFrame(data=[{'Age': 41, 'BusinessTravel': 'Travel_Rarely', 'DailyRate': 1102, 'Department': 'Sales', 'DistanceFromHome': 1, 'Education': 2, 'EducationField': 'Life Sciences', 'EnvironmentSatisfaction': 2, 'Gender': 'Female', 'HourlyRate': 94, 'JobInvolvement': 3, 'JobLevel': 2, 'JobRole': 'Sales Executive', 'JobSatisfaction': 4, 'MaritalStatus': 'Single', 'MonthlyIncome': 5993, 'MonthlyRate': 19479, 'NumCompaniesWorked': 8, 'OverTime': 'No', 'PercentSalaryHike': 11, 'PerformanceRating': 3, 'RelationshipSatisfaction': 1, 'StockOptionLevel': 0, 'TotalWorkingYears': 8, 'TrainingTimesLastYear': 0, 'WorkLifeBalance': 1, 'YearsAtCompany': 6, 'YearsInCurrentRole': 4, 'YearsSinceLastPromotion': 0, 'YearsWithCurrManager': 5}])
# converts the sample to JSON string
sample = pd.DataFrame.to_json(sample)
# deserializes sample to a python object
sample = json.loads(sample)
# serializes sample to JSON formatted string as expected by the scoring script
sample = json.dumps({"data":sample})
prediction = service.run(sample)
print(prediction)
danielsc
commented
4 years ago
Once the model is deployed into AML compute, the UI doesn't help much on how to consume it and try the service. It simply provides an URI, but a user who just deployed it won't be able to try it unless he invests time on researching docs from scratch.
This is a clear paper-cut because it is blocking the path for a fast getting started experience.
This is the only info provided so far for consumption:
That "Consume" page section should help on sample code on the following areas and showing client code for Python apps, .NET apps, Java apps, Node-JS apps, etc.: