def reset_ml_subs_to_in(): """ Reset submissions marked ML to instructor if there are not enough instructor submissions to grade This happens if the instructor skips too many submissions """ counter = 0 unique_locations = [ x['location'] for x in list(Submission.objects.values('location').distinct()) ] for location in unique_locations: subs_graded, subs_pending = staff_grading_util.count_submissions_graded_and_pending_instructor( location) subs_pending_total = Submission.objects.filter( location=location, state=SubmissionState.waiting_to_be_graded, preferred_grader_type="ML").order_by( '-date_created')[:settings.MIN_TO_USE_ML] if ((subs_graded + subs_pending) < settings.MIN_TO_USE_ML and subs_pending_total.count() > subs_pending): for sub in subs_pending_total: if sub.next_grader_type == "ML" and sub.get_unsuccessful_graders( ).count() == 0: staff_grading_util.set_ml_grading_item_back_to_instructor( sub) counter += 1 if (counter + subs_graded + subs_pending) > settings.MIN_TO_USE_ML: break if counter > 0: statsd.increment( "open_ended_assessment.grading_controller.expire_submissions.reset_ml_subs_to_in", tags=["counter:{0}".format(counter)]) log.debug("Reset {0} submission from ML to IN".format(counter))
def reset_ml_subs_to_in(): """ Reset submissions marked ML to instructor if there are not enough instructor submissions to grade This happens if the instructor skips too many submissions """ counter=0 unique_locations=[x['location'] for x in list(Submission.objects.values('location').distinct())] for location in unique_locations: subs_graded, subs_pending = staff_grading_util.count_submissions_graded_and_pending_instructor(location) subs_pending_total= Submission.objects.filter( location=location, state=SubmissionState.waiting_to_be_graded, preferred_grader_type="ML" ).order_by('-date_created')[:settings.MIN_TO_USE_ML] if ((subs_graded+subs_pending) < settings.MIN_TO_USE_ML and subs_pending_total.count() > subs_pending): for sub in subs_pending_total: if sub.next_grader_type=="ML" and sub.get_unsuccessful_graders().count()==0: staff_grading_util.set_ml_grading_item_back_to_instructor(sub) counter+=1 if (counter+subs_graded + subs_pending)> settings.MIN_TO_USE_ML: break if counter>0: statsd.increment("open_ended_assessment.grading_controller.expire_submissions.reset_ml_subs_to_in", tags=["counter:{0}".format(counter)]) log.debug("Reset {0} submission from ML to IN".format(counter))
def handle_submission(sub): """ Handles a new submission. Decides what the next grader should be and saves it. Input: sub - A Submission object from controller.models Output: True/False status code """ try: #Run some basic sanity checks on submission. Also check to see if student is banned, and fail them if they are. sub.next_grader_type = "BC" sub.save() transaction.commit_unless_managed() timing_functions.initialize_timing(sub.id) success, check_dict = basic_check_util.simple_quality_check(sub.student_response, sub.initial_display, sub.student_id, sub.skip_basic_checks) if not success: log.exception("could not run basic checks on {0}".format(sub.student_response)) #add additional tags needed to create a grader object check_dict = grader_util.add_additional_tags_to_dict(check_dict, sub.id) if check_dict['score']==0: success, max_rubric_scores = rubric_functions.generate_targets_from_rubric(sub.rubric) log.debug(max_rubric_scores) if success: check_dict['rubric_scores_complete'] = True check_dict['rubric_scores'] = [0 for i in xrange(0,len(max_rubric_scores))] log.debug(check_dict) #Create and handle the grader, and return grader_util.create_and_handle_grader_object(check_dict) #If the checks result in a score of 0 (out of 1), then the submission fails basic sanity checks #Return to student and don't process further if check_dict['score'] == 0: return True else: sub.state = SubmissionState.waiting_to_be_graded #Assign whether grader should be ML or IN based on number of graded examples. subs_graded_by_instructor, subs_pending_instructor = staff_grading_util.count_submissions_graded_and_pending_instructor( sub.location) #TODO: abstract out logic for assigning which grader to go with. grader_settings_path = os.path.join(settings.GRADER_SETTINGS_DIRECTORY, sub.grader_settings) grader_settings = grader_util.get_grader_settings(grader_settings_path) if grader_settings['grader_type'] == "ML": success= ml_grading_util.check_for_all_model_and_rubric_success(sub.location) if(((subs_graded_by_instructor + subs_pending_instructor) >= settings.MIN_TO_USE_ML) and success): sub.next_grader_type = "ML" else: sub.next_grader_type = "IN" elif grader_settings['grader_type'] == "PE": #Ensures that there will be some calibration essays before peer grading begins! #Calibration essays can be added using command line utility, or through normal instructor grading. if((subs_graded_by_instructor + subs_pending_instructor) >= settings.MIN_TO_USE_PEER): sub.next_grader_type = "PE" else: sub.next_grader_type = "IN" elif grader_settings['grader_type'] == "IN": sub.next_grader_type = "IN" else: log.exception("Invalid grader type specified in settings file.") return False sub.preferred_grader_type=grader_settings['grader_type'] #Do duplicate checks is_duplicate, is_plagiarized, duplicate_id = grader_util.check_is_duplicate_and_plagiarized(sub.student_response, sub.location, sub.student_id, sub.preferred_grader_type) sub.is_duplicate=is_duplicate sub.is_plagiarized = is_plagiarized sub.duplicate_submission_id = duplicate_id sub.has_been_duplicate_checked = True statsd.increment("open_ended_assessment.grading_controller.controller.xqueue_interface.handle_submission.duplicates", tags=[ "duplicate:{0}".format(is_duplicate), "is_plagiarized:{0}".format(is_plagiarized) ]) sub.save() log.debug("Submission object created successfully!") except: log.exception("Submission creation failed!") return False transaction.commit_unless_managed() return True
def handle_submission(sub): """ Handles a new submission. Decides what the next grader should be and saves it. Input: sub - A Submission object from controller.models Output: True/False status code """ try: #Run some basic sanity checks on submission. Also check to see if student is banned, and fail them if they are. sub.next_grader_type = "BC" sub.save() transaction.commit_unless_managed() timing_functions.initialize_timing(sub.id) success, check_dict = basic_check_util.simple_quality_check(sub.student_response, sub.initial_display, sub.student_id, sub.skip_basic_checks) if not success: log.exception("could not run basic checks on {0}".format(sub.student_response)) #add additional tags needed to create a grader object check_dict = grader_util.add_additional_tags_to_dict(check_dict, sub.id) if check_dict['score']==0: success, max_rubric_scores = rubric_functions.generate_targets_from_rubric(sub.rubric) log.debug(max_rubric_scores) if success: check_dict['rubric_scores_complete'] = True check_dict['rubric_scores'] = [0 for i in xrange(0,len(max_rubric_scores))] log.debug(check_dict) #Create and handle the grader, and return grader_util.create_and_handle_grader_object(check_dict) #If the checks result in a score of 0 (out of 1), then the submission fails basic sanity checks #Return to student and don't process further if check_dict['score'] == 0: return True else: sub.state = SubmissionState.waiting_to_be_graded #Assign whether grader should be ML or IN based on number of graded examples. subs_graded_by_instructor, subs_pending_instructor = staff_grading_util.count_submissions_graded_and_pending_instructor( sub.location) #TODO: abstract out logic for assigning which grader to go with. grader_settings_path = os.path.join(settings.GRADER_SETTINGS_DIRECTORY, sub.grader_settings) grader_settings = grader_util.get_grader_settings(grader_settings_path) if grader_settings['grader_type'] == "ML": success= ml_grading_util.check_for_all_model_and_rubric_success(sub.location) if(((subs_graded_by_instructor + subs_pending_instructor) >= settings.MIN_TO_USE_ML) and success): sub.next_grader_type = "ML" else: sub.next_grader_type = "IN" elif grader_settings['grader_type'] == "PE": #Ensures that there will be some calibration essays before peer grading begins! #Calibration essays can be added using command line utility, or through normal instructor grading. if((subs_graded_by_instructor + subs_pending_instructor) >= settings.MIN_TO_USE_PEER): sub.next_grader_type = "PE" else: sub.next_grader_type = "IN" elif grader_settings['grader_type'] == "IN": sub.next_grader_type = "IN" else: log.exception("Invalid grader type specified in settings file.") return False sub.preferred_grader_type=grader_settings['grader_type'] #Do duplicate checks is_duplicate, is_plagiarized, duplicate_id = grader_util.check_is_duplicate_and_plagiarized(sub.student_response, sub.location, sub.student_id, sub.preferred_grader_type) sub.is_duplicate=is_duplicate sub.is_plagiarized = is_plagiarized sub.duplicate_submission_id = duplicate_id statsd.increment("open_ended_assessment.grading_controller.controller.xqueue_interface.handle_submission.duplicates", tags=[ "duplicate:{0}".format(is_duplicate), "is_plagiarized:{0}".format(is_plagiarized) ]) sub.save() log.debug("Submission object created successfully!") except: log.exception("Submission creation failed!") return False transaction.commit_unless_managed() return True