def test_random_crop_dict_mismatch_raises():
with pytest.raises(IteratorValidationError):
_ = RandomCrop(inner, shape_dict={'images': (1, 1)})
with pytest.raises(IteratorValidationError):
_ = RandomCrop(inner, shape_dict={'default': 10})
with pytest.raises(IteratorValidationError):
_ = RandomCrop(inner, shape_dict={'default': (1, 1, 1)})
with pytest.raises(IteratorValidationError):
_ = RandomCrop(inner, shape_dict={'default': (10, 10)})
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_random_crop():
a = np.random.randn(1, 3, 5, 5, 4)
b = np.random.randn(1, 3, 4, 4, 1)
c = np.random.randn(1, 3, 1)
iterator = Undivided(default=a, secondary=b, targets=c)
crop = RandomCrop(iterator, shape_dict={'default': (3, 3),
'secondary': (2, 2)
})(default_handler)
x = next(crop)
assert set(x.keys()) == set(iterator.data.keys())
assert x['default'].shape == (1, 3, 3, 3, 4)
assert x['secondary'].shape == (1, 3, 2, 2, 1)
assert x['targets'].shape == (1, 3, 1)
assert np.allclose(x['targets'], c)