def generate_test(self,
batch_size,
encode,
soft_ordinal_conf,
ensemble=False,
ensemble_type='regression'):
# Load dataset if not loaded
self.load(self._name)
if self._big_dataset:
return BigGenerator(self._df_test,
self._base_path,
self._num_classes,
self._x_col,
self._y_col,
mean=self.mean_train,
std=self.std_train,
encode=encode,
batch_size=batch_size,
labels=self._labels,
soft_ordinal_config=soft_ordinal_conf,
ensemble=ensemble,
ensemble_type=ensemble_type)
else:
return SmallGenerator(self._x_test,
self._y_test,
self._num_classes,
mean=self.mean_train,
std=self.std_train,
batch_size=batch_size,
encode=encode,
labels=self._labels,
soft_ordinal_config=soft_ordinal_conf,
ensemble=ensemble,
ensemble_type=ensemble_type)
def generate_test(self, batch_size): # Load dataset if not loaded self.load(self._name) if self._big_dataset: return BigGenerator(self._df_test, self._base_path, self._num_classes, self._x_col, self._y_col, mean=self.mean_train, std=self.std_train, batch_size=batch_size) else: return SmallGenerator(self._x_test, self._y_test, self._num_classes, mean=self.mean_train, std=self.std_train, batch_size=batch_size)
def generate_test(self, batch_size, labels_transform=lambda labels, n: to_categorical(labels, num_classes=n)): # Load dataset if not loaded self.load(self._name) if self._big_dataset: return BigGenerator(self._df_test, self._base_path, self._num_classes, self._x_col, self._y_col, mean=self.mean_train, std=self.std_train, batch_size=batch_size, labels_transform=labels_transform) else: return SmallGenerator(self._x_test, self._y_test, self._num_classes, mean=self.mean_train, std=self.std_train, batch_size=batch_size, labels_transform=labels_transform)
def generate_train(self, batch_size, augmentation):
# Load dataset if not loaded
self.load(self._name)
if self._big_dataset:
return BigGenerator(self._df_train,
self._base_path,
self._num_classes,
self._x_col,
self._y_col,
mean=self.mean_train,
std=self.std_train,
batch_size=batch_size,
augmentation=augmentation,
workers=self._workers)
else:
return SmallGenerator(self._x_train,
self._y_train,
self._num_classes,
mean=self.mean_train,
std=self.std_train,
batch_size=batch_size,
augmentation=augmentation,
workers=self._workers)