def update_sent_attr_stats(sent_attrs, history, prediction):
"""
Update the sent_attrs dict with the attributes of a prediction with given history.
Inputs:
sent_attrs: dictionary mapping each attr (a string) to a list of floats
(the scores).
history: a ConvAI2History
prediction: string. the response text for which we measure sent attributes
"""
for attr in sent_attrs.keys():
attr_score = eval_attr(prediction, history, attr)
sent_attrs[attr].append(attr_score)
return sent_attrs
def make_dataset(opt):
# Initialize control information so we can compute sentence attributes.
# Here we set build_task=False so we don't download data/controllable_dialogue
# (because we're trying to create it instead).
initialize_control_information(opt, build_task=False)
# Create repeat label agent and assign it to the specified task
agent = RepeatLabelAgent(opt)
world = create_task(opt, agent)
ignorefields = opt.get('ignore_fields', '')
outfile = opt['outfile']
# Number of examples to process
if opt['num_examples'] == -1:
num_examples = world.num_examples()
else:
num_examples = opt['num_examples']
# List of controls to include:
controls = opt['controls'].split(',') if opt['controls'] != '' else []
print('[ starting to convert.. ]')
print('[ saving output to {} ]'.format(outfile))
fw = open(outfile, 'w')
log_timer = TimeLogger()
for _ in range(num_examples):
world.parley()
world.acts[0]['labels'] = world.acts[0].get(
'labels', world.acts[0].pop('eval_labels', None))
# Need to get history in order to compute control values
hist = ConvAI2History(world.acts[0]['text'], assume_persontokens=False)
response = world.acts[0]['labels'][0]
# Compute control values
for ctrl in controls:
ctrl_val = eval_attr(response, hist, ctrl)
if ctrl == 'avg_nidf':
assert ctrl_val >= 0
assert ctrl_val <= 1
elif ctrl == 'question':
assert ctrl_val in [0, 1]
elif ctrl == 'lastuttsim':
if ctrl_val is not None:
assert ctrl_val >= -1
assert ctrl_val <= 1
else:
raise Exception('unexpected ctrl name: %s' % ctrl)
world.acts[0][ctrl] = ctrl_val # add control value to act
# Write to file
txt = msg_to_str(world.acts[0], ignore_fields=ignorefields)
fw.write(txt + '\n')
if world.acts[0].get('episode_done', False):
fw.write('\n')
if log_timer.time() > opt['log_every_n_secs']:
text, _log = log_timer.log(world.total_parleys,
world.num_examples())
print(text)
if world.epoch_done():
print('EPOCH DONE')
break
fw.close()