Add a few tiny tests and update a docstring

blocks/utils.py

@@ -45,8 +45,9 @@ def unpack(arg, singleton=False):
         will be cast to a list before returning. Any other variable
         will be returned as is.
     singleton : bool
-        If ``True``, `arg` is expected to be a singleton and an exception
-        is raised if this is not the case. ``False`` by default.
+        If ``True``, `arg` is expected to be a singleton (a list or tuple
+        with exactly one element) and an exception is raised if this is not
+        the case. ``False`` by default.
 
     Returns
     -------

tests/test_utils.py

@@ -0,0 +1,32 @@
+from numpy.testing import assert_raises
+from theano import tensor
+
+from blocks.utils import (check_theano_variable, graph_inputs, shared_floatx,
+                          unpack)
+
+
+def test_unpack():
+    assert unpack((1, 2)) == [1, 2]
+    assert unpack([1, 2]) == [1, 2]
+    assert unpack([1]) == 1
+    test = object()
+    assert unpack(test) is test
+    assert_raises(ValueError, unpack, [1, 2], True)
+
+
+def test_check_theano_variable():
+    check_theano_variable(None, 3, 'float')
+    check_theano_variable([[1, 2]], 2, 'int')
+    assert_raises(ValueError, check_theano_variable,
+                  tensor.vector(), 2, 'float')
+    assert_raises(ValueError, check_theano_variable,
+                  tensor.vector(), 1, 'int')
+
+
+def test_graph_inputs():
+    a = tensor.matrix('a')
+    b = shared_floatx(0, 'b')
+    c = 3
+
+    d = a + b + c
+    assert graph_inputs([d]) == [a]