def tune_args(args):
"""
tune the dataset specific args so train_file or test_file need not be changed
"""
try:
files = dataset_files_pairs.get(args.dataset)
args.data_root, args.train_file, args.valid_file, args.test_file = files
return args
except AssertionError:
err("Error. Cannot find the specific key -> {} in dataset_files_pairs.".format(args.dataset))
def make_sure_model_is_valid(self):
"""
check if the model has necessary attributes
"""
try:
_ = self.loss
_ = self.correct_prediction
except AttributeError as e:
err("Your model {} doesn't have enough attributes.\nError Message:\n\t{}"
.format(self.model_name, e))
self.sess.close()
exit(1)
def confirm_model_dataset_fitness(self):
# make sure the models_in_datasets var is correct
try:
assert (models_in_datasets.get(self.args.dataset, None)
is not None)
except AssertionError:
err("Models_in_datasets doesn't have the specified dataset key: {}."
.format(self.args.dataset))
self.sess.close()
exit(1)
# make sure the model fit the dataset
try:
assert (self.model_name
in models_in_datasets.get(self.args.dataset, None))
except AssertionError:
err("The model -> {} doesn't support the dataset -> {}".format(
self.model_name, self.args.dataset))
self.sess.close()
exit(1)