def test_sparse(self):
sp = pytest.importorskip("scipy")
mySymbolicSparseList = TypedListType(
sparse.SparseType("csr", aesara.config.floatX))()
mySymbolicSparse = sparse.csr_matrix()
z = Count()(mySymbolicSparseList, mySymbolicSparse)
f = aesara.function([mySymbolicSparseList, mySymbolicSparse], z)
x = sp.sparse.csr_matrix(random_lil((10, 40), aesara.config.floatX, 3))
y = sp.sparse.csr_matrix(random_lil((10, 40), aesara.config.floatX, 3))
assert f([x, y, y], y) == 2
def test_sanity_check(self):
mySymbolicMatricesList = TypedListType(
TensorType(aesara.config.floatX, (False, False)))()
myMatrix = matrix()
z = Count()(mySymbolicMatricesList, myMatrix)
f = aesara.function([mySymbolicMatricesList, myMatrix], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
assert f([y, y, x, y], y) == 3
def test_non_tensor_type(self):
mySymbolicNestedMatricesList = TypedListType(
TensorType(aesara.config.floatX, (False, False)), 1)()
mySymbolicMatricesList = TypedListType(
TensorType(aesara.config.floatX, (False, False)))()
z = Count()(mySymbolicNestedMatricesList, mySymbolicMatricesList)
f = aesara.function(
[mySymbolicNestedMatricesList, mySymbolicMatricesList], z)
x = rand_ranged_matrix(-1000, 1000, [100, 101])
y = rand_ranged_matrix(-1000, 1000, [100, 101])
assert f([[x, y], [x, y, y]], [x, y]) == 1