def test_jax_specify_shape():
x_np = np.zeros((20, 3))
x = SpecifyShape()(aet.as_tensor_variable(x_np), (20, 3))
x_fg = FunctionGraph([], [x])
compare_jax_and_py(x_fg, [])
with config.change_flags(compute_test_value="off"):
x = SpecifyShape()(aet.as_tensor_variable(x_np), (2, 3))
x_fg = FunctionGraph([], [x])
with pytest.raises(AssertionError):
compare_jax_and_py(x_fg, [])
def test_bad_shape(self):
# Test that at run time we raise an exception when the shape
# is not the one specified
specify_shape = SpecifyShape()
x = vector()
xval = np.random.rand(2).astype(config.floatX)
f = aesara.function([x], specify_shape(x, [2]), mode=self.mode)
f(xval)
xval = np.random.rand(3).astype(config.floatX)
with pytest.raises(AssertionError):
f(xval)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
x = matrix()
xval = np.random.rand(2, 3).astype(config.floatX)
f = aesara.function([x], specify_shape(x, [2, 3]), mode=self.mode)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
f(xval)
for shape_ in [(1, 3), (2, 2), (5, 5)]:
xval = np.random.rand(*shape_).astype(config.floatX)
with pytest.raises(AssertionError):
f(xval)
def test_infer_shape(self):
rng = np.random.RandomState(3453)
adtens4 = dtensor4()
aivec = ivector()
aivec_val = [3, 4, 2, 5]
adtens4_val = rng.rand(*aivec_val)
self._compile_and_check(
[adtens4, aivec],
[SpecifyShape()(adtens4, aivec)],
[adtens4_val, aivec_val],
SpecifyShape,
)
def test_bad_number_of_shape(self):
# Test that the number of dimensions provided is good
specify_shape = SpecifyShape()
x = vector()
shape_vec = ivector()
xval = np.random.random((2)).astype(config.floatX)
with pytest.raises(AssertionError, match="will never match"):
specify_shape(x, [])
with pytest.raises(AssertionError, match="will never match"):
specify_shape(x, [2, 2])
f = aesara.function([x, shape_vec], specify_shape(x, shape_vec), mode=self.mode)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
expected = r"(Got 1 dimensions \(shape \(2,\)\), expected 0 dimensions with shape \(\).)"
expected += r"|(Got 1 dimensions, expected 0 dimensions.)"
with pytest.raises(AssertionError, match=expected):
f(xval, [])
expected = r"(Got 1 dimensions \(shape \(2,\)\), expected 2 dimensions with shape \(2, 2\).)"
expected += r"|(SpecifyShape: Got 1 dimensions, expected 2 dimensions.)"
with pytest.raises(AssertionError, match=expected):
f(xval, [2, 2])
x = matrix()
xval = np.random.random((2, 3)).astype(config.floatX)
for shape_ in [(), (1,), (2, 3, 4)]:
with pytest.raises(AssertionError, match="will never match"):
specify_shape(x, shape_)
f = aesara.function(
[x, shape_vec], specify_shape(x, shape_vec), mode=self.mode
)
assert isinstance(
[
n
for n in f.maker.fgraph.toposort()
if isinstance(n.op, SpecifyShape)
][0]
.inputs[0]
.type,
self.input_type,
)
s_exp = str(shape_).replace("(", r"\(").replace(")", r"\)")
expected = rf"(Got 2 dimensions \(shape \(2, 3\)\), expected {len(shape_)} dimensions with shape {s_exp}.)"
expected += rf"|(SpecifyShape: Got 2 dimensions, expected {len(shape_)} dimensions.)"
with pytest.raises(AssertionError, match=expected):
f(xval, shape_)
def test_bad_shape(self):
"""Test that at run-time we raise an exception when the shape is not the one specified."""
specify_shape = SpecifyShape()
x = vector()
xval = np.random.random((2)).astype(config.floatX)
f = aesara.function([x], specify_shape(x, 2), mode=self.mode)
assert np.array_equal(f(xval), xval)
xval = np.random.random((3)).astype(config.floatX)
with pytest.raises(AssertionError, match="SpecifyShape:.*"):
f(xval)
assert isinstance(
[
n for n in f.maker.fgraph.toposort()
if isinstance(n.op, SpecifyShape)
][0].inputs[0].type,
self.input_type,
)
x = matrix()
xval = np.random.random((2, 3)).astype(config.floatX)
f = aesara.function([x], specify_shape(x, 2, 3), mode=self.mode)
assert isinstance(
[
n for n in f.maker.fgraph.toposort()
if isinstance(n.op, SpecifyShape)
][0].inputs[0].type,
self.input_type,
)
assert np.array_equal(f(xval), xval)
for shape_ in [(4, 3), (2, 8)]:
xval = np.random.random(shape_).astype(config.floatX)
with pytest.raises(AssertionError, match="SpecifyShape:.*"):
f(xval)
s = iscalar("s")
f = aesara.function([x, s], specify_shape(x, None, s), mode=self.mode)
x_val = np.zeros((3, 2), dtype=config.floatX)
assert f(x_val, 2).shape == (3, 2)
with pytest.raises(AssertionError, match="SpecifyShape:.*"):
f(xval, 3)
def test_bad_number_of_shape(self):
# Test that the number of dimensions provided is good
specify_shape = SpecifyShape()
x = vector()
shape_vec = ivector()
xval = np.random.rand(2).astype(config.floatX)
with pytest.raises(AssertionError):
specify_shape(x, [])
with pytest.raises(AssertionError):
specify_shape(x, [2, 2])
f = aesara.function([x, shape_vec], specify_shape(x, shape_vec), mode=self.mode)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
with pytest.raises(AssertionError):
f(xval, [])
with pytest.raises(AssertionError):
f(xval, [2, 2])
x = matrix()
xval = np.random.rand(2, 3).astype(config.floatX)
for shape_ in [(), (1,), (2, 3, 4)]:
with pytest.raises(AssertionError):
specify_shape(x, shape_)
f = aesara.function(
[x, shape_vec], specify_shape(x, shape_vec), mode=self.mode
)
assert isinstance(
[
n
for n in f.maker.fgraph.toposort()
if isinstance(n.op, SpecifyShape)
][0]
.inputs[0]
.type,
self.input_type,
)
with pytest.raises(AssertionError):
f(xval, shape_)
def test_bad_shape(self):
# Test that at run time we raise an exception when the shape
# is not the one specified
specify_shape = SpecifyShape()
x = vector()
xval = np.random.random((2)).astype(config.floatX)
f = aesara.function([x], specify_shape(x, [2]), mode=self.mode)
f(xval)
xval = np.random.random((3)).astype(config.floatX)
expected = r"(Got shape \(3,\), expected \(2,\))"
expected += r"|(dim 0 of input has shape 3, expected 2.)"
with pytest.raises(AssertionError, match=expected):
f(xval)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
x = matrix()
xval = np.random.random((2, 3)).astype(config.floatX)
f = aesara.function([x], specify_shape(x, [2, 3]), mode=self.mode)
assert isinstance(
[n for n in f.maker.fgraph.toposort() if isinstance(n.op, SpecifyShape)][0]
.inputs[0]
.type,
self.input_type,
)
f(xval)
for shape_ in [(4, 3), (2, 8)]:
xval = np.random.random(shape_).astype(config.floatX)
s_exp = str(shape_).replace("(", r"\(").replace(")", r"\)")
expected = rf"(Got shape {s_exp}, expected \(2, 3\).)"
expected += r"|(dim 0 of input has shape 4, expected 2)"
expected += r"|(dim 1 of input has shape 8, expected 3)"
with pytest.raises(AssertionError, match=expected):
f(xval)