def create_ml_model(student_id, location): #Create enough instructor graded submissions that ML will work for i in xrange(0,settings.MIN_TO_USE_ML): sub=get_sub("IN",student_id,location, "ML") sub.state=SubmissionState.finished sub.save() grade=get_grader("IN") grade.submission=sub grade.save() # Create ML Model ml_model_creation.handle_single_location(location)
def create_ml_model(student_id, location): sub = get_sub("IN", student_id, location, "ML") sub.state = SubmissionState.finished sub.save() pl = PeerLocation(location, student_id) control = SubmissionControl(pl.latest_submission()) # Create enough instructor graded submissions that ML will work. for i in xrange(0, control.minimum_to_use_ai): sub = get_sub("IN", student_id, location, "ML") sub.state = SubmissionState.finished sub.save() grade = get_grader("IN") grade.submission = sub grade.save() # Create ML Model ml_model_creation.handle_single_location(location)
def create_ml_model(student_id, location): sub = get_sub("IN",student_id,location, "ML") sub.state = SubmissionState.finished sub.save() pl = PeerLocation(location, student_id) control = SubmissionControl(pl.latest_submission()) # Create enough instructor graded submissions that ML will work. for i in xrange(0, control.minimum_to_use_ai): sub = get_sub("IN", student_id, location, "ML") sub.state = SubmissionState.finished sub.save() grade = get_grader("IN") grade.submission = sub grade.save() # Create ML Model ml_model_creation.handle_single_location(location)