def test_dataset_onehot(self):
Xs, Ys = dsu.cifar10_load()
ds = dsu.Dataset(
Xs=Xs, ys=Ys, split=[0.8, 0.1, 0.1], one_hot=True, n_classes=10)
X_i, Y_i = next(ds.train.next_batch())
assert (X_i.shape == (100, 32, 32, 3))
assert (Y_i.shape == (100, 10))
def CIFAR10(flatten=True, split=[1.0, 0.0, 0.0]):
"""Returns the CIFAR10 dataset.
Parameters
----------
flatten : bool, optional
Convert the 3 x 32 x 32 pixels to a single vector
split : list, optional
Description
Returns
-------
cifar : Dataset
Description
"""
# plt.imshow(np.transpose(np.reshape(
# cifar.train.images[10], (3, 32, 32)), [1, 2, 0]))
Xs, ys = cifar10_load()
if flatten:
Xs = Xs.reshape((Xs.shape[0], -1))
return Dataset(Xs, ys, split=split)
def CIFAR10(flatten=True, split=[1.0, 0.0, 0.0]):
"""Returns the CIFAR10 dataset.
Parameters
----------
flatten : bool, optional
Convert the 3 x 32 x 32 pixels to a single vector
split : list, optional
Description
Returns
-------
cifar : Dataset
Description
"""
# plt.imshow(np.transpose(np.reshape(
# cifar.train.images[10], (3, 32, 32)), [1, 2, 0]))
Xs, ys = cifar10_load()
if flatten:
Xs = Xs.reshape((Xs.shape[0], -1))
return Dataset(Xs, ys, split=split)
def test_draw_train_dataset(self):
Xs, ys = dsu.cifar10_load()
Xs = Xs[:100, ...].reshape((100, 3072))
ys = ys[:100]
ds = dsu.Dataset(Xs, ys, split=(0.5, 0.25, 0.25))
draw.train_dataset(n_epochs=1, batch_size=25, ds=ds, A=32, B=32, C=3)
def test_dataset_split_batch_generator(self):
Xs, Ys = dsu.cifar10_load()
ds = dsu.Dataset(Xs=Xs, ys=Ys, split=[0.8, 0.1, 0.1], one_hot=False)
X_i, Y_i = next(ds.train.next_batch())
assert (X_i.shape == (100, 32, 32, 3))
assert (Y_i.shape == (100,))
def test_dataset_split(self):
Xs, Ys = dsu.cifar10_load()
ds = dsu.Dataset(Xs=Xs, ys=Ys, split=[0.8, 0.1, 0.1], one_hot=False)
assert (ds.train.images.shape == (40000, 32, 32, 3))
assert (ds.valid.images.shape == (5000, 32, 32, 3))
assert (ds.test.images.shape == (5000, 32, 32, 3))
def test_dataset(self):
Xs, Ys = dsu.cifar10_load()
ds = dsu.Dataset(Xs=Xs, ys=Ys, split=[0.8, 0.1, 0.1], one_hot=False)
assert (ds.X.shape == (50000, 32, 32, 3))
assert (ds.Y.shape == (50000,))
def test_cifar_loads(self):
Xs, Ys = dsu.cifar10_load()
assert (Xs.shape == (50000, 32, 32, 3))
assert (Ys.shape == (50000,))
assert (np.mean(Ys) == 4.5)
assert (np.mean(Xs) == 120.70756512369792)
def test_draw_train_dataset(self):
Xs, ys = dsu.cifar10_load()
Xs = Xs[:100, ...].reshape((100, 3072))
ys = ys[:100]
ds = dsu.Dataset(Xs, ys, split=(0.5, 0.25, 0.25))
draw.train_dataset(n_epochs=1, batch_size=25, ds=ds, A=32, B=32, C=3)