def schedule_training(self, data, suffix=''): # pylint: disable=W0613
"""
Schedule a new training task for example-based grading.
"""
assessment = self.get_assessment_module('example-based-assessment')
student_item_dict = self.get_student_item_dict()
if assessment:
examples = assessment["examples"]
try:
workflow_uuid = ai_api.train_classifiers(
create_rubric_dict(self.prompts, self.rubric_criteria_with_labels),
convert_training_examples_list_to_dict(examples),
student_item_dict.get('course_id'),
student_item_dict.get('item_id'),
assessment["algorithm_id"]
)
return {
'success': True,
'workflow_uuid': workflow_uuid,
'msg': self._(u"Training scheduled with new Workflow UUID: {uuid}".format(uuid=workflow_uuid))
}
except AIError as err:
return {
'success': False,
'msg': self._(u"An error occurred scheduling classifier training: {error}".format(error=err))
}
else:
return {
'success': False,
'msg': self._(u"Example Based Assessment is not configured for this location.")
}
def _validate_assessment_examples(rubric_dict, assessments):
"""
Validate assessment training examples.
Args:
rubric_dict (dict): The serialized rubric model.
assessments (list of dict): List of assessment dictionaries.
Returns:
tuple (is_valid, msg) where
is_valid is a boolean indicating whether the assessment is semantically valid
and msg describes any validation errors found.
"""
for asmnt in assessments:
if asmnt['name'] == 'student-training':
examples = convert_training_examples_list_to_dict(asmnt['examples'])
# Delegate to the student training API to validate the
# examples against the rubric.
errors = validate_training_examples(rubric_dict, examples)
if errors:
return False, "\n".join(errors)
return True, u''
def validate_assessment_examples(rubric_dict, assessments, _):
"""
Validate assessment training examples.
Args:
rubric_dict (dict): The serialized rubric model.
assessments (list of dict): List of assessment dictionaries.
_ (function): The service function used to get the appropriate i18n text
Returns:
tuple (is_valid, msg) where
is_valid is a boolean indicating whether the assessment is semantically valid
and msg describes any validation errors found.
"""
for asmnt in assessments:
if asmnt['name'] == 'student-training':
examples = convert_training_examples_list_to_dict(
asmnt['examples'])
# Must have at least one training example
if len(examples) == 0:
return False, _(
u"Learner training must have at least one training example."
)
# Delegate to the student training API to validate the
# examples against the rubric.
errors = validate_training_examples(rubric_dict, examples)
if errors:
return False, "; ".join(errors)
return True, u''
def _validate_assessment_examples(rubric_dict, assessments):
"""
Validate assessment training examples.
Args:
rubric_dict (dict): The serialized rubric model.
assessments (list of dict): List of assessment dictionaries.
Returns:
tuple (is_valid, msg) where
is_valid is a boolean indicating whether the assessment is semantically valid
and msg describes any validation errors found.
"""
for asmnt in assessments:
if asmnt['name'] == 'student-training':
examples = convert_training_examples_list_to_dict(asmnt['examples'])
# Delegate to the student training API to validate the
# examples against the rubric.
errors = validate_training_examples(rubric_dict, examples)
if errors:
return False, "\n".join(errors)
return True, u''
def validate_assessment_examples(rubric_dict, assessments, _):
"""
Validate assessment training examples.
Args:
rubric_dict (dict): The serialized rubric model.
assessments (list of dict): List of assessment dictionaries.
_ (function): The service function used to get the appropriate i18n text
Returns:
tuple (is_valid, msg) where
is_valid is a boolean indicating whether the assessment is semantically valid
and msg describes any validation errors found.
"""
for asmnt in assessments:
if asmnt['name'] == 'student-training':
examples = convert_training_examples_list_to_dict(asmnt['examples'])
# Must have at least one training example
if len(examples) == 0:
return False, _(
u"Learner training must have at least one training example."
)
# Delegate to the student training API to validate the
# examples against the rubric.
errors = validate_training_examples(rubric_dict, examples)
if errors:
return False, "; ".join(errors)
return True, u''
def schedule_training(self, data, suffix=''): # pylint: disable=W0613
"""
Schedule a new training task for example-based grading.
"""
assessment = self.get_assessment_module('example-based-assessment')
student_item_dict = self.get_student_item_dict()
if assessment:
examples = assessment["examples"]
try:
workflow_uuid = ai_api.train_classifiers(
create_rubric_dict(self.prompts, self.rubric_criteria_with_labels),
convert_training_examples_list_to_dict(examples),
student_item_dict.get('course_id'),
student_item_dict.get('item_id'),
assessment["algorithm_id"]
)
return {
'success': True,
'workflow_uuid': workflow_uuid,
'msg': self._(u"Training scheduled with new Workflow UUID: {uuid}".format(uuid=workflow_uuid))
}
except AIError as err:
return {
'success': False,
'msg': self._(u"An error occurred scheduling classifier training: {error}".format(error=err))
}
else:
return {
'success': False,
'msg': self._(u"Example Based Assessment is not configured for this location.")
}
def training_path_and_context(self):
"""
Return the template path and context used to render the student training step.
Returns:
tuple of `(path, context)` where `path` is the path to the template and
`context` is a dict.
"""
# Retrieve the status of the workflow.
# If no submissions have been created yet, the status will be None.
workflow_status = self.get_workflow_info().get('status')
problem_closed, reason, start_date, due_date = self.is_closed(
step="student-training")
context = {}
template = 'openassessmentblock/student_training/student_training_unavailable.html'
# add allow_latex field to the context
context['allow_latex'] = self.allow_latex
if not workflow_status:
return template, context
# If the student has completed the training step, then show that the step is complete.
# We put this condition first so that if a student has completed the step, it *always*
# shows as complete.
# We're assuming here that the training step always precedes the other assessment steps
# (peer/self) -- we may need to make this more flexible later.
if workflow_status == 'cancelled':
template = 'openassessmentblock/student_training/student_training_cancelled.html'
elif workflow_status and workflow_status != "training":
template = 'openassessmentblock/student_training/student_training_complete.html'
# If the problem is closed, then do not allow students to access the training step
elif problem_closed and reason == 'start':
context['training_start'] = start_date
template = 'openassessmentblock/student_training/student_training_unavailable.html'
elif problem_closed and reason == 'due':
context['training_due'] = due_date
template = 'openassessmentblock/student_training/student_training_closed.html'
# If we're on the training step, show the student an example
# We do this last so we can avoid querying the student training API if possible.
else:
training_module = self.get_assessment_module('student-training')
if not training_module:
return template, context
if due_date < DISTANT_FUTURE:
context['training_due'] = due_date
# Report progress in the student training workflow (completed X out of Y)
context['training_num_available'] = len(
training_module["examples"])
context[
'training_num_completed'] = student_training.get_num_completed(
self.submission_uuid)
context[
'training_num_current'] = context['training_num_completed'] + 1
# Retrieve the example essay for the student to submit
# This will contain the essay text, the rubric, and the options the instructor selected.
examples = convert_training_examples_list_to_dict(
training_module["examples"])
example = student_training.get_training_example(
self.submission_uuid, {
'prompt': self.prompt,
'criteria': self.rubric_criteria_with_labels
}, examples)
if example:
context['training_essay'] = create_submission_dict(
{'answer': example['answer']}, self.prompts)
context['training_rubric'] = {
'criteria': example['rubric']['criteria'],
'points_possible': example['rubric']['points_possible']
}
template = 'openassessmentblock/student_training/student_training.html'
else:
logger.error(
"No training example was returned from the API for student "
"with Submission UUID {}".format(self.submission_uuid))
template = "openassessmentblock/student_training/student_training_error.html"
return template, context
def training_path_and_context(self):
"""
Return the template path and context used to render the student training step.
Returns:
tuple of `(path, context)` where `path` is the path to the template and
`context` is a dict.
"""
# Retrieve the status of the workflow.
# If no submissions have been created yet, the status will be None.
workflow_status = self.get_workflow_info().get('status')
problem_closed, reason, start_date, due_date = self.is_closed(step="student-training")
context = {}
template = 'openassessmentblock/student_training/student_training_unavailable.html'
# add allow_latex field to the context
context['allow_latex'] = self.allow_latex
if not workflow_status:
return template, context
# If the student has completed the training step, then show that the step is complete.
# We put this condition first so that if a student has completed the step, it *always*
# shows as complete.
# We're assuming here that the training step always precedes the other assessment steps
# (peer/self) -- we may need to make this more flexible later.
if workflow_status == 'cancelled':
template = 'openassessmentblock/student_training/student_training_cancelled.html'
elif workflow_status and workflow_status != "training":
template = 'openassessmentblock/student_training/student_training_complete.html'
# If the problem is closed, then do not allow students to access the training step
elif problem_closed and reason == 'start':
context['training_start'] = start_date
template = 'openassessmentblock/student_training/student_training_unavailable.html'
elif problem_closed and reason == 'due':
context['training_due'] = due_date
template = 'openassessmentblock/student_training/student_training_closed.html'
# If we're on the training step, show the student an example
# We do this last so we can avoid querying the student training API if possible.
else:
training_module = self.get_assessment_module('student-training')
if not training_module:
return template, context
if due_date < DISTANT_FUTURE:
context['training_due'] = due_date
# Report progress in the student training workflow (completed X out of Y)
context['training_num_available'] = len(training_module["examples"])
context['training_num_completed'] = student_training.get_num_completed(self.submission_uuid)
context['training_num_current'] = context['training_num_completed'] + 1
# Retrieve the example essay for the student to submit
# This will contain the essay text, the rubric, and the options the instructor selected.
examples = convert_training_examples_list_to_dict(training_module["examples"])
example = student_training.get_training_example(
self.submission_uuid,
{
'prompt': self.prompt,
'criteria': self.rubric_criteria_with_labels
},
examples
)
if example:
context['training_essay'] = create_submission_dict({'answer': example['answer']}, self.prompts)
context['training_rubric'] = {
'criteria': example['rubric']['criteria'],
'points_possible': example['rubric']['points_possible']
}
template = 'openassessmentblock/student_training/student_training.html'
else:
logger.error(
"No training example was returned from the API for student "
"with Submission UUID {}".format(self.submission_uuid)
)
template = "openassessmentblock/student_training/student_training_error.html"
return template, context
