def main():
"""
Personality-Captions Data Collection Task.
This is the task setup used when collecting the Personality-Captions
dataset (https://arxiv.org/abs/1810.10665).
"""
argparser = ParlaiParser(False, False)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
PersonalityCaptionsTeacher.add_cmdline_args(argparser)
argparser.add_argument('-ni',
'--num_images',
type=int,
default=10,
help='number of images to show \
to turker')
argparser.add_argument('-mx_rsp_time',
'--max_resp_time',
default=1800,
type=int,
help='time limit for entering a dialog message')
argparser.add_argument('-mx_onb_time',
'--max_onboard_time',
type=int,
default=300,
help='time limit for turker'
'in onboarding')
argparser.add_argument('--auto-approve-delay',
type=int,
default=3600 * 24 * 5,
help='how long to wait for \
auto approval')
argparser.add_argument('--multiple-personality',
type='bool',
default=False,
help='for getting captions with '
'multiple personalities for same image')
argparser.add_argument(
'--task-type',
type=str,
default='personality',
choices=['personality', 'no_personality', 'caption'],
help='Task Type - specify `personality` for '
'original task, `no_personality` for the same task '
'instructions but with no personality, and '
'`caption` for the task but asking for a normal '
'caption.')
opt = argparser.parse_args()
directory_path = os.path.dirname(os.path.abspath(__file__))
opt['task'] = os.path.basename(directory_path)
if 'data_path' not in opt:
opt['data_path'] = os.getcwd() + '/data/' + opt['task']
opt.update(TASK_TYPE_TO_CONFIG[opt['task_type']])
build_pc_data(opt)
mturk_agent_ids = [COMMENTER]
mturk_manager = MTurkManager(opt=opt,
mturk_agent_ids=mturk_agent_ids,
use_db=True)
personality_generator = PersonalityGenerator(opt)
image_generator = ImageGenerator(opt)
personality_and_image_generator = PersonalityAndImageGenerator(opt)
mturk_manager.setup_server(task_directory_path=directory_path)
try:
mturk_manager.start_new_run()
def run_onboard(worker):
worker.personality_generator = personality_generator
worker.image_generator = image_generator
worker.personality_and_image_generator = personality_and_image_generator
world = RoleOnboardWorld(opt, worker)
world.parley()
world.shutdown()
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.ready_to_accept_workers()
mturk_manager.create_hits()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for w in workers:
w.id = mturk_agent_ids[0]
def run_conversation(mturk_manager, opt, workers):
agents = workers[:]
conv_idx = mturk_manager.conversation_index
world = MTurkPersonalityCaptionsWorld(
opt,
agents=agents,
world_tag='conversation t_{}'.format(conv_idx),
)
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
world.review_work()
mturk_manager.start_task(eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()
def main():
"""
Image Chat data collection task.
A worker is shown an image and part of a conversation, and is given a personality
with which the worker should continue the conversation.
"""
argparser = ParlaiParser(False, False)
argparser.add_parlai_data_path()
argparser.add_mturk_args()
argparser.add_argument('-min_t',
'--min_turns',
default=3,
type=int,
help='minimum number of turns')
argparser.add_argument('-mt',
'--max_turns',
default=5,
type=int,
help='maximal number of chat turns')
argparser.add_argument(
'-mx_rsp_time',
'--max_resp_time',
default=1800,
type=int,
help='time limit for entering a dialog message',
)
argparser.add_argument(
'-mx_onb_time',
'--max_onboard_time',
type=int,
default=300,
help='time limit for turker'
'in onboarding',
)
argparser.add_argument(
'-ni',
'--num_images',
type=int,
default=10,
help='number of images to show \
to turker',
)
argparser.add_argument(
'--auto-approve-delay',
type=int,
default=3600 * 24 * 5,
help='how long to wait for \
auto approval',
)
argparser.add_argument(
'--second-response',
type='bool',
default=False,
help='Specify if getting responses \
to responses to original comment',
)
ImageChatTeacher.add_cmdline_args(argparser)
opt = argparser.parse_args()
directory_path = os.path.dirname(os.path.abspath(__file__))
opt['task'] = os.path.basename(directory_path)
if 'data_path' not in opt:
opt['data_path'] = os.getcwd() + '/data/' + opt['task']
opt.update(config_second if opt['second_response'] else config_first)
mturk_agent_ids = [RESPONDER]
mturk_manager = MTurkManager(opt=opt, mturk_agent_ids=mturk_agent_ids)
personality_generator = PersonalityGenerator(opt)
example_generator = ExampleGenerator(opt)
mturk_manager.setup_server(task_directory_path=directory_path)
try:
mturk_manager.start_new_run()
mturk_manager.ready_to_accept_workers()
def run_onboard(worker):
worker.personality_generator = personality_generator
worker.example_generator = example_generator
world = RoleOnboardWorld(opt, worker)
world.parley()
world.shutdown()
mturk_manager.set_onboard_function(onboard_function=run_onboard)
mturk_manager.create_hits()
def check_worker_eligibility(worker):
return True
def assign_worker_roles(workers):
for w in workers:
w.id = mturk_agent_ids[0]
def run_conversation(mturk_manager, opt, workers):
agents = workers[:]
conv_idx = mturk_manager.conversation_index
world = MTurkImageChatWorld(
opt,
agents=agents,
world_tag='conversation t_{}'.format(conv_idx))
while not world.episode_done():
world.parley()
world.save_data()
world.shutdown()
world.review_work()
mturk_manager.start_task(
eligibility_function=check_worker_eligibility,
assign_role_function=assign_worker_roles,
task_function=run_conversation,
)
except BaseException:
raise
finally:
mturk_manager.expire_all_unassigned_hits()
mturk_manager.shutdown()