token = input("Enter your token:")
if token == '': print('The token you entered may be invalid. Please try again.')
else: print('OK')

# Prepare an environment and import everything we need
!pip install toloka-kit==0.1.3 import datetime
import json
import time import toloka.client as toloka
import toloka.client.project.template_builder as tb

# Create a Toloka client instance
# All API calls will pass through it
toloka_client = toloka.TolokaClient(token, 'PRODUCTION') # or switch to SANDBOX # We check the money available in your account, which also checks the validity of the OAuth token
requester = toloka_client.get_requester()
# How much money do you need for one question
PRICE_PER_TASK = 0.2
tasks_num = int(input("Enter the number of questions:"))
print('You have enough money on your account - ', requester.balance >= tasks_num * PRICE_PER_TASK)

# Download datasets
!curl https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v2.0.json --output train-v2.0.json
!curl https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v2.0.json --output dev-v2.0.json with open('dev-v2.0.json') as f: data = json.load(f) with open('train-v2.0.json') as f: train_data = json.load(f)

{ 'title': data['data'][0]['title'], # Printing only the first paragraph for review 'paragraphs': [data['data'][0]['paragraphs'][0]]
}

{'title': 'Normans', 'paragraphs': [{'qas': [{'question': 'In what country is Normandy located?', 'id': '56ddde6b9a695914005b9628', 'answers': [{'text': 'France', 'answer_start': 159}, {'text': 'France', 'answer_start': 159}, {'text': 'France', 'answer_start': 159}, {'text': 'France', 'answer_start': 159}], 'is_impossible': False}, {'question': 'When were the Normans in Normandy?', 'id': '56ddde6b9a695914005b9629', 'answers': [{'text': '10th and 11th centuries', 'answer_start': 94}, {'text': 'in the 10th and 11th centuries', 'answer_start': 87}, {'text': '10th and 11th centuries', 'answer_start': 94}, {'text': '10th and 11th centuries', 'answer_start': 94}], 'is_impossible': False}, {'question': 'From which countries did the Norse originate?', 'id': '56ddde6b9a695914005b962a', 'answers': [{'text': 'Denmark, Iceland and Norway', 'answer_start': 256}, {'text': 'Denmark, Iceland and Norway', 'answer_start': 256}, {'text': 'Denmark, Iceland and Norway', 'answer_start': 256}, {'text': 'Denmark, Iceland and Norway', 'answer_start': 256}], 'is_impossible': False}, {'question': 'Who was the Norse leader?', 'id': '56ddde6b9a695914005b962b', 'answers': [{'text': 'Rollo', 'answer_start': 308}, {'text': 'Rollo', 'answer_start': 308}, {'text': 'Rollo', 'answer_start': 308}, {'text': 'Rollo', 'answer_start': 308}], 'is_impossible': False}, {'question': 'What century did the Normans first gain their separate identity?', 'id': '56ddde6b9a695914005b962c', 'answers': [{'text': '10th century', 'answer_start': 671}, {'text': 'the first half of the 10th century', 'answer_start': 649}, {'text': '10th', 'answer_start': 671}, {'text': '10th', 'answer_start': 671}], 'is_impossible': False}, {'plausible_answers': [{'text': 'Normans', 'answer_start': 4}], 'question': "Who gave their name to Normandy in the 1000's and 1100's", 'id': '5ad39d53604f3c001a3fe8d1', 'answers': [], 'is_impossible': True}, {'plausible_answers': [{'text': 'Normandy', 'answer_start': 137}], 'question': 'What is France a region of?', 'id': '5ad39d53604f3c001a3fe8d2', 'answers': [], 'is_impossible': True}, {'plausible_answers': [{'text': 'Rollo', 'answer_start': 308}], 'question': 'Who did King Charles III swear fealty to?', 'id': '5ad39d53604f3c001a3fe8d3', 'answers': [], 'is_impossible': True}, {'plausible_answers': [{'text': '10th century', 'answer_start': 671}], 'question': 'When did the Frankish identity emerge?', 'id': '5ad39d53604f3c001a3fe8d4', 'answers': [], 'is_impossible': True}], 'context': 'The Normans (Norman: Nourmands; French: Normands; Latin: Normanni) were the people who in the 10th and 11th centuries gave their name to Normandy, a region in France. They were descended from Norse ("Norman" comes from "Norseman") raiders and pirates from Denmark, Iceland and Norway who, under their leader Rollo, agreed to swear fealty to King Charles III of West Francia. Through generations of assimilation and mixing with the native Frankish and Roman-Gaulish populations, their descendants would gradually merge with the Carolingian-based cultures of West Francia. The distinct cultural and ethnic identity of the Normans emerged initially in the first half of the 10th century, and it continued to evolve over the succeeding centuries.'}]}

# How performers will see the task
radio_group_field = tb.fields.RadioGroupFieldV1( data=tb.data.OutputData(path='is_possible'), label='Does the text contain an asnwer?', validation=tb.conditions.RequiredConditionV1(), options=[ tb.fields.GroupFieldOption(label='Yes', value='yes'), tb.fields.GroupFieldOption(label='No', value='no') ]
)
helper = tb.helpers.IfHelperV1( condition=tb.conditions.EqualsConditionV1( to='yes', data=tb.data.OutputData(path='is_possible') ), then=tb.fields.TextareaFieldV1( data=tb.data.OutputData(path='answer'), label='Paste an answer', validation=tb.conditions.RequiredConditionV1() )
) project_interface = toloka.project.view_spec.TemplateBuilderViewSpec( config=tb.TemplateBuilder( view=tb.view.ListViewV1( items=[ tb.view.TextViewV1(label='Text', content=tb.data.InputData(path='text')), tb.view.TextViewV1(label='Question', content=tb.data.InputData(path='question')), tb.view.ListViewV1(items=[radio_group_field, helper]) ] ) )
) public_instruction = open('marking_public_instruction.html').read().strip() # Set up the project
marking_project = toloka.project.Project( assignments_issuing_type=toloka.project.Project.AssignmentsIssuingType.AUTOMATED, public_name='Find the answer in the text', public_description='Read the text and find the text fragment that answers the question', public_instructions=public_instruction, # Set up the task: view, input, and output parameters task_spec=toloka.project.task_spec.TaskSpec( input_spec={ 'text': toloka.project.field_spec.StringSpec(), 'question': toloka.project.field_spec.StringSpec(), 'question_id': toloka.project.field_spec.StringSpec(required=False) }, output_spec={ 'answer': toloka.project.field_spec.StringSpec(required=False), 'is_possible': toloka.project.field_spec.StringSpec(allowed_values=['yes', 'no']) }, view_spec=project_interface, ),
) # Call the API to create a new project
# If you have already created all pools and projects you can just get it using toloka_client.get_project('your marking project id')
marking_project = toloka_client.create_project(marking_project)
print(f'Created marking project with id {marking_project.id}')
print(f'To view the project, go to: https://toloka.yandex.com/requester/project/{marking_project.id}')

# Set up the training pool
marking_training = toloka.training.Training( project_id=marking_project.id, private_name='SQUAD2.0 training', may_contain_adult_content=True, assignment_max_duration_seconds=10000, mix_tasks_in_creation_order=True, shuffle_tasks_in_task_suite=True, training_tasks_in_task_suite_count=3, task_suites_required_to_pass=1, retry_training_after_days=1, inherited_instructions=True, public_instructions='',
) marking_training = toloka_client.create_training(marking_training)
print(f'Created training with id {marking_training.id}')
print(f'To view the training, go to: https://toloka.yandex.com/requester/project/{marking_project.id}/training/{marking_training.id}')

training_tasks = [ toloka.task.Task( input_values={ 'question_id': '56be85543aeaaa14008c9063', 'question': 'When did Beyonce start becoming popular?', 'text': 'Beyoncé Giselle Knowles-Carter (/biːˈjɒnseɪ/ bee-YON-say) (born September 4, 1981) is an American singer, songwriter, record producer and actress. Born and raised in Houston, Texas, she performed in various singing and dancing competitions as a child, and rose to fame in the late 1990s as lead singer of R&B girl-group Destiny's Child. Managed by her father, Mathew Knowles, the group became one of the world's best-selling girl groups of all time. Their hiatus saw the release of Beyoncé's debut album, Dangerously in Love (2003), which established her as a solo artist worldwide, earned five Grammy Awards and featured the Billboard Hot 100 number-one singles "Crazy in Love" and "Baby Boy".' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_possible': 'yes', 'answer': 'in the late 1990s'})], message_on_unknown_solution='the answer can be found after "and rose to fame..."', infinite_overlap=True, pool_id=marking_training.id ), toloka.task.Task( input_values={ 'question_id': '56be86cf3aeaaa14008c9076', 'question': 'After her second solo album, what other entertainment venture did Beyonce explore?', 'text': 'Following the disbandment of Destiny's Child in June 2005, she released her second solo album, B'Day (2006), which contained hits "Déjà Vu", "Irreplaceable", and "Beautiful Liar". Beyoncé also ventured into acting, with a Golden Globe-nominated performance in Dreamgirls (2006), and starring roles in The Pink Panther (2006) and Obsessed (2009). Her marriage to rapper Jay Z and portrayal of Etta James in Cadillac Records (2008) influenced her third album, I Am... Sasha Fierce (2008), which saw the birth of her alter-ego Sasha Fierce and earned a record-setting six Grammy Awards in 2010, including Song of the Year for "Single Ladies (Put a Ring on It)". Beyoncé took a hiatus from music in 2010 and took over management of her career; her fourth album 4 (2011) was subsequently mellower in tone, exploring 1970s funk, 1980s pop, and 1990s soul. Her critically acclaimed fifth studio album, Beyoncé (2013), was distinguished from previous releases by its experimental production and exploration of darker themes.' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_possible': 'yes', 'answer': 'acting'})], message_on_unknown_solution='the answer can be found before "... with a Golden Globe-nominated performance in Dreamgirls (2006), and starring roles in The Pink Panther (2006) and Obsessed (2009)"', infinite_overlap=True, pool_id=marking_training.id ), toloka.task.Task( input_values={ 'question_id': '5a8d7bf7df8bba001a0f9ab1', 'question': 'What category of game is Legend of Zelda: Australia Twilight?', 'text': 'The Legend of Zelda: Twilight Princess (Japanese: ゼルダの伝説 トワイライトプリンセス, Hepburn: Zeruda no Densetsu: Towairaito Purinsesu?) is an action-adventure game developed and published by Nintendo for the GameCube and Wii home video game consoles. It is the thirteenth installment in the The Legend of Zelda series. Originally planned for release on the GameCube in November 2005, Twilight Princess was delayed by Nintendo to allow its developers to refine the game, add more content, and port it to the Wii. The Wii version was released alongside the console in North America in November 2006, and in Japan, Europe, and Australia the following month. The GameCube version was released worldwide in December 2006.[b]' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_possible': 'no'})], message_on_unknown_solution='There is no game called Legend of Zelda: Australia Twilight', infinite_overlap=True, pool_id=marking_training.id )
] tasks_op = toloka_client.create_tasks_async(training_tasks)
toloka_client.wait_operation(tasks_op)

marking_pool = toloka.pool.Pool( project_id=marking_project.id, private_name='Pool 1', may_contain_adult_content=True, will_expire=datetime.datetime.utcnow() + datetime.timedelta(days=365), reward_per_assignment=0.02, auto_accept_solutions=False, auto_accept_period_day=3, assignment_max_duration_seconds=60*20, defaults=toloka.pool.Pool.Defaults( default_overlap_for_new_task_suites=3 ), filter=toloka.filter.Languages.in_('EN'),
) marking_pool.set_mixer_config(real_tasks_count=4, golden_tasks_count=1, training_tasks_count=0) # 5 tasks per page # We require at least 1 training task to be completed on the first attempt
marking_pool.quality_control.training_requirement=toloka.quality_control.QualityControl.TrainingRequirement(training_pool_id=marking_training.id, training_passing_skill_value=30) # Increase overlap for the task if the assignment was rejected
marking_pool.quality_control.add_action( collector=toloka.collectors.AssignmentsAssessment(), conditions=[toloka.conditions.AssessmentEvent == toloka.conditions.AssessmentEvent.REJECT], action=toloka.actions.ChangeOverlap(delta=1, open_pool=True)
) # Ban performer if its quality in the binary classification of the existence of the answer is lower than for a random choice
marking_pool.quality_control.add_action( collector=toloka.collectors.GoldenSet(), conditions=[ toloka.conditions.GoldenSetCorrectAnswersRate < 50.0, toloka.conditions.GoldenSetAnswersCount > 4 ], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration=1, duration_unit=toloka.user_restriction.DurationUnit.DAYS, private_comment='Golden set' )
) # Ban performer who answers too fast
marking_pool.quality_control.add_action( collector=toloka.collectors.AssignmentSubmitTime(history_size=5, fast_submit_threshold_seconds=120), conditions=[toloka.conditions.FastSubmittedCount > 2], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration_unit=toloka.user_restriction.DurationUnit.PERMANENT, private_comment='Fast responses' )
) # Another criteria to ban performer who answers too fast
marking_pool.quality_control.add_action( collector=toloka.collectors.AssignmentSubmitTime(fast_submit_threshold_seconds=60), conditions=[toloka.conditions.FastSubmittedCount > 0], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration_unit=toloka.user_restriction.DurationUnit.PERMANENT, private_comment='Fast responses' )
) marking_pool = toloka_client.create_pool(marking_pool)
print(f'Created pool with id {marking_pool.id}')
print(f'To view the pool, go to: https://toloka.yandex.com/requester/project/{marking_project.id}/pool/{marking_pool.id}')

for d in train_data['data']: if len(golden_tasks) == tasks_num / 2: break for paragraph in d['paragraphs']: if len(golden_tasks) == tasks_num / 2: break for question in paragraph['qas']: if len(golden_tasks) == tasks_num / 2: break golden_tasks.append( toloka.task.Task( input_values={ 'text': paragraph['context'], 'question': question['question'], 'question_id': question['id'] }, known_solutions = [toloka.task.BaseTask.KnownSolution(output_values={'is_possible': 'no' if question['is_impossible'] else 'yes'})], pool_id = marking_pool.id ) ) tasks = []
for d in data['data']: if len(tasks) >= tasks_num: break for paragraph in d['paragraphs']: if len(tasks) >= tasks_num: break for question in paragraph['qas']: if len(tasks) == tasks_num: break tasks.append( toloka.task.Task( input_values={ 'text': paragraph['context'], 'question': question['question'], 'question_id': question['id'] }, pool_id = marking_pool.id, ) )

# Restrict size of the golden set and create tasks
tasks_op = toloka_client.create_tasks_async(golden_tasks + tasks, allow_defaults=True)
toloka_client.wait_operation(tasks_op)

# How performers will see the task
helper = tb.helpers.IfHelperV1( condition=tb.conditions.EqualsConditionV1(to='yes', data=tb.data.InputData(path='is_possible')), then=tb.view.TextViewV1(label='Answer', content=tb.data.InputData(path='answer')), else_=tb.view.TextViewV1(label='Answer', content='No answer in the text')
)
radio_group_field = tb.fields.RadioGroupFieldV1( data=tb.data.OutputData(path='is_correct'), label='Is the answer correct?', validation=tb.conditions.RequiredConditionV1(), options=[ tb.fields.GroupFieldOption(label='Yes', value='yes'), tb.fields.GroupFieldOption(label='No', value='no') ]
)
verificaction_project_interface = toloka.project.view_spec.TemplateBuilderViewSpec( config=tb.TemplateBuilder( view=tb.view.ListViewV1( items=[ tb.view.TextViewV1(label='Text', content=tb.data.InputData(path='text')), tb.view.TextViewV1(label='Question', content=tb.data.InputData(path='question')), helper, radio_group_field ] ) )
) public_instruction = open('verification_public_instruction.html').read().strip() # Set up the project
verification_project = toloka.project.Project( assignments_issuing_type=toloka.project.Project.AssignmentsIssuingType.AUTOMATED, public_name='Check if the answer is correct', public_description='Read the text, the question, and the answer. Check if the answer is correct', public_instructions=public_instruction, # Set up the task: view, input, and output parameters task_spec=toloka.project.task_spec.TaskSpec( input_spec={ 'text': toloka.project.field_spec.StringSpec(), 'question': toloka.project.field_spec.StringSpec(), 'question_id': toloka.project.field_spec.StringSpec(required=False), 'assignment_id': toloka.project.field_spec.StringSpec(required=False), 'answer': toloka.project.field_spec.StringSpec(required=False), 'is_possible': toloka.project.field_spec.StringSpec(allowed_values=['yes', 'no']) }, output_spec={'is_correct': toloka.project.field_spec.StringSpec(allowed_values=['yes', 'no'])}, view_spec=verificaction_project_interface, ),
)
verification_project = toloka_client.create_project(verification_project)
print(f'Created verification project with id {verification_project.id}')
print(f'To view the project, go to: https://toloka.yandex.com/requester/project/{verification_project.id}')

verification_training = toloka.training.Training( project_id=verification_project.id, private_name='SQUAD2.0 training', may_contain_adult_content=True, assignment_max_duration_seconds=10000, mix_tasks_in_creation_order=True, shuffle_tasks_in_task_suite=True, training_tasks_in_task_suite_count=5, task_suites_required_to_pass=1, retry_training_after_days=1, inherited_instructions=True, public_instructions='',
) verification_training = toloka_client.create_training(verification_training)
print(f'Created training with id {verification_training.id}')
print(f'To view the training, go to: https://toloka.yandex.com/requester/project/{verification_project.id}/training/{verification_training.id}')

training_tasks = [ toloka.task.Task( input_values={ 'question_id': '', 'question': 'Who wrote later papers studying problems solvable by Turning machines?', 'answer': 'Hisao Yamada', 'is_possible': 'yes', 'text': 'Earlier papers studying problems solvable by Turing machines with specific bounded resources include John Myhill's definition of linear bounded automata (Myhill 1960), Raymond Smullyan's study of rudimentary sets (1961), as well as Hisao Yamada's paper on real-time computations (1962). Somewhat earlier, Boris Trakhtenbrot (1956), a pioneer in the field from the USSR, studied another specific complexity measure. As he remembers:' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_correct': 'no'})], message_on_unknown_solution='The text is about earlier papers not later ones', infinite_overlap=True, pool_id=verification_training.id ), toloka.task.Task( input_values={ 'question_id': '', 'question': 'Who wrote the paper "Reductibility Among Combinatorial Problems" in 1974?', 'answer': 'Richard Karp', 'is_possible': 'yes', 'text': 'In 1967, Manuel Blum developed an axiomatic complexity theory based on his axioms and proved an important result, the so-called, speed-up theorem. The field really began to flourish in 1971 when the US researcher Stephen Cook and, working independently, Leonid Levin in the USSR, proved that there exist practically relevant problems that are NP-complete. In 1972, Richard Karp took this idea a leap forward with his landmark paper, "Reducibility Among Combinatorial Problems", in which he showed that 21 diverse combinatorial and graph theoretical problems, each infamous for its computational intractability, are NP-complete.' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_correct': 'no'})], message_on_unknown_solution='"Reductibility Among Combinatorial Problems" was written in 1972', infinite_overlap=True, pool_id=verification_training.id ), toloka.task.Task( input_values={ 'question_id': '', 'question': 'What category of game is Legend of Zelda: Australia Twilight?', 'answer': '', 'is_possible': 'no', 'text': 'The Legend of Zelda: Twilight Princess (Japanese: ゼルダの伝説 トワイライトプリンセス, Hepburn: Zeruda no Densetsu: Towairaito Purinsesu?) is an action-adventure game developed and published by Nintendo for the GameCube and Wii home video game consoles. It is the thirteenth installment in the The Legend of Zelda series. Originally planned for release on the GameCube in November 2005, Twilight Princess was delayed by Nintendo to allow its developers to refine the game, add more content, and port it to the Wii. The Wii version was released alongside the console in North America in November 2006, and in Japan, Europe, and Australia the following month. The GameCube version was released worldwide in December 2006.[b]' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_correct': 'yes'})], message_on_unknown_solution='There is no game called Legend of Zelda: Australia Twilight', infinite_overlap=True, pool_id=verification_training.id ), toloka.task.Task( input_values={ 'question_id': '', 'question': 'What is the name of the state that the megaregion expands to in the east?', 'answer': 'Las Vegas', 'is_possible': 'yes', 'text': 'The 8- and 10-county definitions are not used for the greater Southern California Megaregion, one of the 11 megaregions of the United States. The megaregion's area is more expansive, extending east into Las Vegas, Nevada, and south across the Mexican border into Tijuana.' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_correct': 'no'})], message_on_unknown_solution='The state is actually called Nevada', infinite_overlap=True, pool_id=verification_training.id ), toloka.task.Task( input_values={ 'question_id': '', 'question': 'Which city is the most populous in California?', 'answer': 'Los Angeles', 'is_possible': 'yes', 'text': 'Within southern California are two major cities, Los Angeles and San Diego, as well as three of the country's largest metropolitan areas. With a population of 3,792,621, Los Angeles is the most populous city in California and the second most populous in the United States. To the south and with a population of 1,307,402 is San Diego, the second most populous city in the state and the eighth most populous in the nation.' }, known_solutions=[toloka.task.BaseTask.KnownSolution(output_values={'is_correct': 'yes'})], message_on_unknown_solution='"With a population of 3,792,621, Los Angeles is the most populous city in California"', infinite_overlap=True, pool_id=verification_training.id )
] tasks_op = toloka_client.create_tasks_async(training_tasks)
toloka_client.wait_operation(tasks_op)

verification_pool = toloka.pool.Pool( project_id=verification_project.id, private_name='Pool 1', may_contain_adult_content=True, will_expire=datetime.datetime.utcnow() + datetime.timedelta(days=365), reward_per_assignment=0.01, auto_accept_solutions=True, assignment_max_duration_seconds=60*20, defaults=toloka.pool.Pool.Defaults( default_overlap_for_new_task_suites=5 ), filter=toloka.filter.Languages.in_('EN'),
) verification_pool.set_mixer_config(real_tasks_count=5, golden_tasks_count=0, training_tasks_count=0)
verification_pool.set_captcha_frequency('MEDIUM') # Ban performer who answers too fast
verification_pool.quality_control.add_action( collector=toloka.collectors.AssignmentSubmitTime(history_size=5, fast_submit_threshold_seconds=100), conditions=[toloka.conditions.FastSubmittedCount > 2], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration_unit=toloka.user_restriction.DurationUnit.PERMANENT, private_comment='Fast responses' )
) # Ban performer who answers too fast
verification_pool.quality_control.add_action( collector=toloka.collectors.AssignmentSubmitTime(fast_submit_threshold_seconds=45), conditions=[toloka.conditions.FastSubmittedCount > 0], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration_unit=toloka.user_restriction.DurationUnit.PERMANENT, private_comment='Fast responses' )
) # Ban performer by captcha criteria
verification_pool.quality_control.add_action( collector=toloka.collectors.Captcha(history_size=5), conditions=[toloka.conditions.FailRate >= 60], action=toloka.actions.RestrictionV2( scope=toloka.user_restriction.UserRestriction.PROJECT, duration=3, duration_unit=toloka.user_restriction.DurationUnit.DAYS, private_comment='Captcha' )
) verification_pool = toloka_client.create_pool(verification_pool)
print(f'Created pool with id {verification_pool.id}')
print(f'To view the training, go to: https://toloka.yandex.com/requester/project/{verification_project.id}/pool/{verification_pool.id}')

def wait_pool_for_close(pool): sleep_time = 60 pool = toloka_client.get_pool(pool.id) while not pool.is_closed(): print( f't{datetime.datetime.now().strftime("%H:%M:%S")}t' f'Pool {pool.id} has status {pool.status}.' ) time.sleep(sleep_time) pool = toloka_client.get_pool(pool.id) def prepare_verification_tasks(): verification_tasks = [] # Tasks that we will send for verification request = toloka.search_requests.AssignmentSearchRequest( status=toloka.assignment.Assignment.SUBMITTED, # Only take completed tasks that haven't been accepted or rejected pool_id=marking_pool.id, ) # Create and store new tasks for assignment in toloka_client.get_assignments(request): for task, solution in zip(assignment.tasks, assignment.solutions): verification_tasks.append( toloka.task.Task( input_values={ 'text': task.input_values['text'], 'question': task.input_values['question'], 'question_id': task.input_values['question_id'], 'is_possible': solution.output_values['is_possible'], 'answer': solution.output_values.get('answer', '').strip(), 'assignment_id': assignment.id, }, pool_id=verification_pool.id, ) ) print(f'Generate {len(verification_tasks)} new verification tasks') return verification_tasks def run_verification_pool(verification_tasks): verification_tasks_op = toloka_client.create_tasks_async( verification_tasks, toloka.task.CreateTasksParameters(allow_defaults=True) ) toloka_client.wait_operation(verification_tasks_op) verification_tasks_result = [task for task in toloka_client.get_tasks(pool_id=verification_pool.id) if not task.known_solutions] task_to_assignment = {} for task in verification_tasks_result: task_to_assignment[task.id] = task.input_values['assignment_id'] # Open the verification pool run_pool2_operation = toloka_client.open_pool(verification_pool.id) run_pool2_operation = toloka_client.wait_operation(run_pool2_operation) print(f'Verification pool status - {run_pool2_operation.status}') return task_to_assignment def get_aggregation_results(pool_id): print('Start aggregation in the verification pool') aggregation_operation = toloka_client.aggregate_solutions_by_pool( type='DAWID_SKENE', pool_id=pool_id, fields=[toloka.aggregation.PoolAggregatedSolutionRequest.Field(name='is_correct')] ) aggregation_operation = toloka_client.wait_operation(aggregation_operation) print('Results aggregated') return list(toloka_client.get_aggregated_solutions(aggregation_operation.id)) def set_answers_status(verification_results): print('Started adding results to marking tasks') assignment_results = dict() for r in verification_results: if r.task_id not in task_to_assignment: continue assignment_id = task_to_assignment[r.task_id] assignment_result = assignment_results.get(assignment_id, 0) # Increase the number of correct tasks in assignment if r.output_values['is_correct'] == 'yes': assignment_result += 1 assignment_results[assignment_id] = assignment_result for assignment_id, correct_num in assignment_results.items(): assignment = toloka_client.get_assignment(assignment_id) if assignment.status.value == 'SUBMITTED': # If 4 or 5 tasks in the assignment was marked as correct then we will accept the assignment if correct_num >= 4: toloka_client.accept_assignment(assignment_id, 'Well done!') else: toloka_client.reject_assignment(assignment_id, 'Incorrect answers') print('Finished adding results to marking tasks')

toloka_client.open_pool(marking_training.id)
toloka_client.open_pool(verification_training.id)
toloka_client.open_pool(marking_pool.id)

# Run the pipeline
while True: print('nWaiting for marking pool to close') wait_pool_for_close(marking_pool) print(f'Marking pool {marking_pool.id} is finally closed!') # Preparing tasks verification_tasks = prepare_verification_tasks() # Make sure all the tasks are done if not verification_tasks: print('All the tasks in our project are done') break # Add it to the pool and run the pool task_to_assignment = run_verification_pool(verification_tasks) print('nWaiting for verification pool to close') wait_pool_for_close(verification_pool) print(f'Verification pool {verification_pool.id} is finally closed!') # Aggregation operation verification_results = get_aggregation_results(verification_pool.id) # Reject or accept tasks in the segmentation pool set_answers_status(verification_results) print(f'Results received at {datetime.datetime.now()}')

request_for_result = toloka.search_requests.AssignmentSearchRequest( status=toloka.assignment.Assignment.ACCEPTED, pool_id=marking_pool.id, ) answers = dict()
for assignment in toloka_client.get_assignments(request_for_result): for i, sol in enumerate(assignment.solutions): answer = sol.output_values['answer'].strip() if sol.output_values['is_possible'] == 'yes' else '' current_list = answers.get(assignment.tasks[i].input_values['question_id'], []) current_list.append(answer) answers[assignment.tasks[i].input_values['question_id']] = current_list

final_answers = dict()
for key, value in answers.items(): sorted_value = sorted(value, key=lambda x: len(x)) n = len(sorted_value) // 2 if sorted_value[n] == '': final_answers[key] = '' else: final_answers[key] = next(filter(lambda x: x != '', sorted_value))

# Download evaluation script
!curl 'https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/' --output evaluate.py from evaluate import make_qid_to_has_ans, get_raw_scores, apply_no_ans_threshold, apply_no_ans_threshold, make_eval_dict, merge_eval # Implement `score` method using the methods from the evaluation script downloaded from the official SQUAD2.0 website
def score(dataset, preds): na_probs = {k: 0.0 for k in preds} qid_to_has_ans = {k: v for k, v in make_qid_to_has_ans(dataset).items() if k in preds} # Maps qid to True/False has_ans_qids = [k for k, v in qid_to_has_ans.items() if v] no_ans_qids = [k for k, v in qid_to_has_ans.items() if not v] exact_raw, f1_raw = get_raw_scores(dataset, preds) exact_thresh = apply_no_ans_threshold(exact_raw, na_probs, qid_to_has_ans, 1) f1_thresh = apply_no_ans_threshold(f1_raw, na_probs, qid_to_has_ans, 1) out_eval = make_eval_dict(exact_thresh, f1_thresh) if has_ans_qids: has_ans_eval = make_eval_dict(exact_thresh, f1_thresh, qid_list=has_ans_qids) merge_eval(out_eval, has_ans_eval, 'HasAns') if no_ans_qids: no_ans_eval = make_eval_dict(exact_thresh, f1_thresh, qid_list=no_ans_qids) merge_eval(out_eval, no_ans_eval, 'NoAns') print(json.dumps(out_eval, indent=2))

score(data['data'], final_answers)