def test_non5d_data_raises():
with pytest.raises(IteratorValidationError):
_ = Flip(Undivided(default=np.random.randn(2, 3, 1, 2)),
prob_dict={'default': 1})
with pytest.raises(IteratorValidationError):
_ = Pad(Undivided(default=np.random.randn(2, 3, 1, 2)),
size_dict={'default': 1})
with pytest.raises(IteratorValidationError):
_ = RandomCrop(Undivided(default=np.random.randn(2, 3, 1, 2)),
shape_dict={'default': (1, 1)})
def test_pad():
a = np.random.randn(2, 3, 5, 5, 4)
b = np.random.randn(2, 3, 4, 4, 1)
c = np.random.randn(2, 3, 1)
iterator = Undivided(default=a, secondary=b, targets=c)
pad = Pad(iterator, size_dict={'default': 1})(default_handler)
x = next(pad)
assert set(x.keys()) == set(iterator.data.keys())
assert x['default'].shape == (2, 3, 7, 7, 4)
assert x['secondary'].shape == (2, 3, 4, 4, 1)
assert x['targets'].shape == (2, 3, 1)
assert np.allclose(x['default'][:, :, 1:-1, 1:-1, :], a)
assert np.allclose(x['secondary'], b)
assert np.allclose(x['targets'], c)
def test_pad_dict_mismatch_raises():
with pytest.raises(IteratorValidationError):
_ = Pad(inner, size_dict={'images': 1})
with pytest.raises(IteratorValidationError):
_ = Pad(inner, size_dict={'default': 1}, value_dict={'images': 0})