def _init_data(self):
hparams = self.hparams
batch_size = hparams.batch_size
if hparams.dataset == 'mnist':
# Get MNIST test data
X_train, Y_train, X_test, Y_test = data_mnist(
train_start=hparams.train_start,
train_end=hparams.train_end,
test_start=hparams.test_start,
test_end=hparams.test_end)
input_shape = (batch_size, 28, 28, 1)
preproc_func = None
elif hparams.dataset == 'cifar10':
X_train, Y_train, X_test, Y_test = cifar_input.read_CIFAR10(
os.path.join(hparams.data_path, hparams.dataset))
input_shape = (batch_size, 32, 32, 3)
preproc_func = cifar_input.cifar_tf_preprocess
elif hparams.dataset == 'svhn':
X_train, Y_train, X_test, Y_test = svhn_input.read_SVHN(
os.path.join(hparams.data_path, hparams.dataset))
input_shape = (batch_size, 32, 32, 3)
preproc_func = svhn_input.svhn_tf_preprocess
# Use label smoothing
assert Y_train.shape[1] == 10.
label_smooth = .1
Y_train = Y_train.clip(label_smooth / 9., 1. - label_smooth)
self.X_train = X_train
self.Y_train = Y_train
self.X_test = X_test
self.Y_test = Y_test
self.data = (X_train, Y_train, X_test, Y_test)
self.input_shape = input_shape
self.preproc_func = preproc_func
def _init_data(self):
hparams = self.hparams
batch_size = hparams.batch_size
if hparams.dataset == 'mnist':
# Get MNIST test data
X_train, Y_train, X_test, Y_test = data_mnist(
train_start=hparams.train_start,
train_end=hparams.train_end,
test_start=hparams.test_start,
test_end=hparams.test_end)
input_shape = (batch_size, 28, 28, 1)
preproc_func = None
elif hparams.dataset == 'cifar10':
X_train, Y_train, X_test, Y_test = cifar_input.read_CIFAR10(
os.path.join(hparams.data_path, hparams.dataset))
input_shape = (batch_size, 32, 32, 3)
preproc_func = cifar_input.cifar_tf_preprocess
elif hparams.dataset == 'svhn':
X_train, Y_train, X_test, Y_test = svhn_input.read_SVHN(
os.path.join(hparams.data_path, hparams.dataset))
input_shape = (batch_size, 32, 32, 3)
preproc_func = svhn_input.svhn_tf_preprocess
# Use label smoothing
assert Y_train.shape[1] == 10.
label_smooth = .1
Y_train = Y_train.clip(label_smooth / 9., 1. - label_smooth)
self.X_train = X_train
self.Y_train = Y_train
self.X_test = X_test
self.Y_test = Y_test
self.data = (X_train, Y_train, X_test, Y_test)
self.input_shape = input_shape
self.preproc_func = preproc_func