def __call__(self):
for index, epoch in make_prod(self.config):
base_dir = make_base_dir(index, self.dataset, 'valid', epoch)
base_dir.mkdir(parents=True, exist_ok=True)
checkpoint_path = get_checkpoint_path(index, epoch)
self.write(base_dir, checkpoint_path, self.buffer_size,
self.source)
def __call__(self):
for result in self.make_result_table().maximum_list():
base_dir = make_base_dir(result.index, self.dataset, 'test',
result.epoch)
base_dir.mkdir(parents=True, exist_ok=True)
checkpoint_path = get_checkpoint_path(result.index, result.epoch)
self.write(base_dir, checkpoint_path, self.buffer_size,
self.source)
def test_single_errant_result(dataset):
valid_tab = ErrantCat2ResultTable(dataset, 'valid')
test_lst = []
for valid_result in valid_tab.maximum_list():
result_path = make_base_dir(valid_result.index, dataset, 'test', valid_result.epoch) / 'result.cat2'
if result_path.exists():
test_lst.append(ErrantCat2Result(valid_result.index, valid_result.epoch, result_path))
lst = [result.cat_score() for result in test_lst]
lst = [np.mean(tup) for tup in zip(*lst)]
return lst
def show_test_single_results(dataset, valid_result_table_class,
test_result_class):
valid_result_table = valid_result_table_class(dataset, 'valid')
test_result_list = []
for valid_result in valid_result_table.maximum_list():
base_dir = make_base_dir(valid_result.index, dataset, 'test',
valid_result.epoch)
result_path = base_dir / 'result.res'
if result_path.exists():
test_result = test_result_class(valid_result.index,
valid_result.epoch, result_path)
test_result_list.append(test_result)
print('index {}: {} ({})'.format(test_result.index,
test_result.gleu,
test_result.epoch))
if len(test_result_list) > 0:
ave = np.mean([result.gleu for result in test_result_list])
print('average: {}'.format(ave))
def show_test_single_results(dataset, valid_result_table_class,
test_result_class):
valid_result_table = valid_result_table_class(dataset, 'valid')
test_result_list = []
for valid_result in valid_result_table.maximum_list():
base_dir = make_base_dir(valid_result.index, dataset, 'test',
valid_result.epoch)
result_path = base_dir / 'result.res'
if result_path.exists():
try:
test_result = test_result_class(valid_result.index,
valid_result.epoch,
result_path)
test_result_list.append(test_result)
print('index {}: {} ({}, {}, {})'.format(
test_result.index, test_result.f, test_result.p,
test_result.r, test_result.epoch))
except IndexError:
pass
if len(test_result_list) > 0:
ave_p, ave_r, ave_f = list_average_score(test_result_list)
print('average: {} ({}, {})'.format(ave_f, ave_p, ave_r))
def __call__(self):
for result in self.make_result_table().maximum_list():
self.write(
make_base_dir(result.index, self.dataset, 'test',
result.epoch))
def __call__(self):
for index, epoch in make_prod(self.config):
self.write(make_base_dir(index, self.dataset, 'valid', epoch))
def make(self):
for result in self.make_result_table().maximum_list():
self.append_command(make_base_dir(result.index, self.dataset, self.stage, result.epoch))
def make(self):
for index, epoch in make_prod(self.config):
self.append_command(make_base_dir(index, self.dataset, self.stage, epoch))
def make(self):
for epoch in make_epoch_list(self.config):
base_dir = make_base_dir(self.index, self.dataset, self.stage, epoch)
self.add(epoch, base_dir / 'result.cat2')
