def run(self):
make_dirs('output/summary/')
call([
'python3', 'qanta/reporting/performance.py', 'generate',
c.PRED_TARGET.format(self.fold),
c.META_TARGET.format(self.fold),
'output/summary/{0}.json'.format(self.fold)
])
def run(self):
make_dirs('output/models/')
call([
'vw',
'-d', c.VW_INPUT.format('dev'),
'-b', '30',
'--loss_function', 'logistic',
'-f', c.VW_MODEL
])
def run(self):
make_dirs('output/summary/')
call([
'python3',
'qanta/reporting/performance.py',
'generate',
c.PRED_TARGET.format(self.fold),
c.META_TARGET.format(self.fold),
'output/summary/{0}.json'.format(self.fold)
])
def run(self):
make_dirs("output/summary/")
call([
"python3",
"qanta/reporting/performance.py",
"generate",
c.PRED_TARGET.format(self.fold),
c.META_TARGET.format(self.fold),
"output/summary/{0}.json".format(self.fold),
])
def run(self):
make_dirs('output/predictions/')
shell(
('vw -t '
'-d output/vw_input/{fold}.vw.txt '
'--loss_function logistic '
'-i {vw_model} --audit '
'| python cli.py format_vw_audit '
'> output/predictions/{fold}.audit').format(fold='test', vw_model=c.VW_MODEL)
)
def run(self):
make_dirs('output/predictions/')
call([
'vw',
'-t',
'--loss_function', 'logistic',
'-d', c.VW_INPUT.format(self.fold),
'-i', c.VW_MODEL,
'-p', c.VW_PREDICTIONS.format(self.fold)
])
def run(self):
make_dirs('output/tagme/')
db = QuestionDatabase()
questions = list(db.all_questions().values())
batch = 0
batch_lookup = {}
while batch * BATCH_SIZE < len(questions):
batch_questions = questions[batch * BATCH_SIZE:(batch + 1) *
BATCH_SIZE]
batch_lookup[batch] = batch_questions
batch += 1
with open('output/tagme/batches.pickle', 'wb') as f:
pickle.dump(batch_lookup, f)
with open('output/tagme/meta.pickle', 'wb') as f:
pickle.dump(batch, f)
def run(self):
make_dirs(safe_path("output/predictions/"))
make_dirs(safe_path("output/expo/"))
make_dirs(safe_path("output/vw_input/"))
config = conf["buzzer"]["config"]
buzzer_test.generate(config, [self.fold])
def run(self):
make_dirs(safe_path("output/buzzers/"))
train_cost_sensitive(conf["buzzer"]["config"],
c.BUZZER_GENERATION_FOLDS)
def run(self):
make_dirs(safe_path('output/predictions/'))
make_dirs(safe_path('output/expo/'))
make_dirs(safe_path('output/vw_input/'))
config=conf['buzzer']['config']
buzzer_test.generate(config, [self.fold])
def run(self):
make_dirs(safe_path('output/buzzers/'))
train_cost_sensitive(conf['buzzer']['config'], c.BUZZER_GENERATION_FOLDS)
def run(self):
make_dirs(safe_path('output/predictions/'))
make_dirs(safe_path('output/expo/'))
make_dirs(safe_path('output/vw_input/'))
args = Namespace(fold=self.fold, config=conf['buzzer']['config'])
buzzer_test.generate(args)
def run(self):
make_dirs(safe_path('output/buzzers/'))
args = Namespace(config=conf['buzzer']['config'], epochs=6, load=False)
train_cost_sensitive(args)
def output(self):
make_dirs('output/predictions/')
return LocalTarget(
c.VW_PREDICTIONS.format(self.fold))