def test_fetch_next_job(self) -> None:
"""Test the fetch_next_jobs method."""
exp1_id = u'1'
state_name = 'Home'
interaction_id = 'TextInput'
exp2_id = u'2'
job1_id = self._create_classifier_training_job(
feconf.INTERACTION_CLASSIFIER_MAPPING[interaction_id]
['algorithm_id'], interaction_id, exp1_id, 1,
datetime.datetime.utcnow(), [], state_name,
feconf.TRAINING_JOB_STATUS_NEW, {}, 1)
self._create_classifier_training_job(
feconf.INTERACTION_CLASSIFIER_MAPPING[interaction_id]
['algorithm_id'], interaction_id, exp2_id, 1,
datetime.datetime.utcnow(), [], state_name,
feconf.TRAINING_JOB_STATUS_PENDING, {}, 1)
# This will get the job_id of the exploration created in setup.
classifier_services.fetch_next_job()
next_job = classifier_services.fetch_next_job()
# Ruling out the possibility of None for mypy type checking.
assert next_job is not None
self.assertEqual(job1_id, next_job.job_id)
# This will check if 'fetch_next_job' returns None
# when there are no job models to be fetched from
# the job queue.
next_job = classifier_services.fetch_next_job()
self.assertIsNone(next_job)
def test_fetch_next_job(self):
"""Test the fetch_next_jobs method."""
exp1_id = u'1'
state_name = 'Home'
interaction_id = 'TextInput'
exp2_id = u'2'
job1_id = classifier_services.create_classifier_training_job(
feconf.INTERACTION_CLASSIFIER_MAPPING[interaction_id]
['algorithm_id'], interaction_id, exp1_id, 1, state_name, [],
feconf.TRAINING_JOB_STATUS_NEW)
classifier_services.create_classifier_training_job(
feconf.INTERACTION_CLASSIFIER_MAPPING[interaction_id]
['algorithm_id'], interaction_id, exp2_id, 1, state_name, [],
feconf.TRAINING_JOB_STATUS_PENDING)
# This will get the job_id of the exploration created in setup.
classifier_services.fetch_next_job()
next_job = classifier_services.fetch_next_job()
self.assertEqual(job1_id, next_job.job_id)
def post(self):
"""Handles POST requests."""
response = {}
next_job = classifier_services.fetch_next_job()
if next_job is not None:
classifier_services.mark_training_job_pending(next_job.job_id)
response['job_id'] = next_job.job_id
response['algorithm_id'] = next_job.algorithm_id
response['algorithm_version'] = next_job.algorithm_version
response['training_data'] = next_job.training_data
return self.render_json(response)
def test_migrate_state_training_jobs(self):
"""Test the migrate_state_training_jobs method."""
state_name = 'Home'
mock_interaction_classifier_mapping = {
'TextInput': {
'algorithm_id': 'NewTextClassifier',
'algorithm_version': 1
},
}
with self.swap(
feconf,
'INTERACTION_CLASSIFIER_MAPPING',
mock_interaction_classifier_mapping):
classifier_services.migrate_state_training_jobs(
classifier_services.get_state_training_jobs_mapping(
self.exp_id, 1, state_name)
)
state_training_jobs_mapping = (
classifier_services.get_state_training_jobs_mapping(
self.exp_id, 1, 'Home')
)
self.assertIn(
'NewTextClassifier',
state_training_jobs_mapping.algorithm_ids_to_job_ids)
# Check migration of an existing algorithm to a newer version.
mock_interaction_classifier_mapping = {
'TextInput': {
'algorithm_id': 'NewTextClassifier',
'algorithm_version': 2
},
}
with self.swap(
feconf,
'INTERACTION_CLASSIFIER_MAPPING',
mock_interaction_classifier_mapping):
classifier_services.migrate_state_training_jobs(
classifier_services.get_state_training_jobs_mapping(
self.exp_id, 1, state_name))
next_job = classifier_services.fetch_next_job()
self.assertEqual(
mock_interaction_classifier_mapping[
'TextInput']['algorithm_version'],
next_job.algorithm_version
)
def test_migrate_state_training_jobs(self) -> None:
"""Test the migrate_state_training_jobs method."""
state_name = 'Home'
mock_interaction_classifier_mapping = {
'TextInput': {
'algorithm_id': 'NewTextClassifier',
'algorithm_version': 1
},
}
expected_state_training_jobs = (
classifier_services.get_state_training_jobs_mapping(
self.exp_id, 1, state_name))
# Ruling out the possibility of None for mypy type checking.
assert expected_state_training_jobs is not None
with self.swap(feconf, 'INTERACTION_CLASSIFIER_MAPPING',
mock_interaction_classifier_mapping):
classifier_services.migrate_state_training_jobs(
expected_state_training_jobs)
state_training_jobs_mapping = (
classifier_services.get_state_training_jobs_mapping(
self.exp_id, 1, 'Home'))
# Ruling out the possibility of None for mypy type checking.
assert state_training_jobs_mapping is not None
self.assertIn('NewTextClassifier',
state_training_jobs_mapping.algorithm_ids_to_job_ids)
# Check migration of an existing algorithm to a newer version.
mock_interaction_classifier_mapping = {
'TextInput': {
'algorithm_id': 'NewTextClassifier',
'algorithm_version': 2
},
}
with self.swap(feconf, 'INTERACTION_CLASSIFIER_MAPPING',
mock_interaction_classifier_mapping):
classifier_services.migrate_state_training_jobs(
expected_state_training_jobs)
next_job = classifier_services.fetch_next_job()
# Ruling out the possibility of None for mypy type checking.
assert next_job is not None
self.assertEqual(
mock_interaction_classifier_mapping['TextInput']
['algorithm_version'], next_job.algorithm_version)
def post(self):
"""Handles POST requests."""
signature = self.payload.get('signature')
vm_id = self.payload.get('vm_id')
message = self.payload.get('message')
if vm_id == feconf.DEFAULT_VM_ID and not feconf.DEV_MODE:
raise self.UnauthorizedUserException
if not verify_signature(message, vm_id, signature):
raise self.UnauthorizedUserException
response = {}
next_job = classifier_services.fetch_next_job()
if next_job is not None:
classifier_services.mark_training_job_pending(next_job.job_id)
response['job_id'] = next_job.job_id
response['algorithm_id'] = next_job.algorithm_id
response['training_data'] = next_job.training_data
return self.render_json(response)
