Split op and test classes, improve description of out_var in make_node.

theano/sandbox/linalg/kron.py

 import numpy
+import theano
 from theano.gof import Op, Apply
-from theano import tensor, function
-from theano.tests import unittest_tools as utt
+from theano import tensor
 
 try:
     import scipy.linalg
@@ -24,6 +24,7 @@ class Kron(Op):
     A: array, shape (M*P, N*Q)
 
     The result is the block matrix:
+    (notice that a[i,j]*b is itself a matrix of the same shape as b)
 
     a[0,0]*b    a[0,1]*b  ... a[0,-1]*b
     a[1,0]*b    a[1,1]*b  ... a[1,-1]*b
@@ -42,7 +43,7 @@ class Kron(Op):
 
     def make_node(self, a, b):
         assert imported_scipy, (
-            "Scipy not available. Scipy is needed for the Solve op")
+            "Scipy not available. Scipy is needed for the Kron op")
         a = tensor.as_tensor_variable(a)
         b = tensor.as_tensor_variable(b)
 
@@ -50,9 +51,9 @@ class Kron(Op):
             raise TypeError('%s: inputs must have two dimensions' %
                             self.__class__.__name__)
 
-        out_type = tensor.TensorType(dtype=(a[0, 0] * b[0, 0]).dtype,
+        out_var = tensor.TensorType(dtype=theano.scalar.upcast(a, b),
                                      broadcastable=(False, False))()
-        return Apply(self, [a, b], [out_type])
+        return Apply(self, [a, b], [out_var])
 
     def infer_shape(self, node, in_shapes):
         shape_a, shape_b = in_shapes
@@ -67,43 +68,3 @@ class Kron(Op):
                 ' implemented' % self.__class__.__name__)
 
 kron = Kron()
-
-
-class TestKron(utt.InferShapeTester):
-
-    rng = numpy.random.RandomState(43)
-
-    def setUp(self):
-        super(TestKron, self).setUp()
-        self.op_class = Kron
-        self.op = kron
-
-    def test_perform(self):
-        x = tensor.dmatrix()
-        y = tensor.dmatrix()
-        f = function([x, y], kron(x, y))
-
-        for shp0 in [(8, 6), (5, 8)]:
-            for shp1 in [(5, 7), (3, 3)]:
-                a = numpy.random.rand(*shp0)
-                b = numpy.random.rand(*shp1)
-                out = f(a, b)
-                assert numpy.allclose(out, scipy.linalg.kron(a, b))
-
-    def test_infer_shape(self):
-        x = tensor.dmatrix()
-        y = tensor.dmatrix()
-        self._compile_and_check([x, y], [self.op(x, y)],
-                                [numpy.random.rand(8, 5),
-                                 numpy.random.rand(3, 7)],
-                                self.op_class)
-        self._compile_and_check([x, y], [self.op(x, y)],
-                                [numpy.random.rand(2, 5),
-                                 numpy.random.rand(6, 3)],
-                                self.op_class)
-
-if __name__ == "__main__":
-    t = TestKron('setUp')
-    t.setUp()
-    t.test_perform()
-    t.test_infer_shape()

theano/sandbox/linalg/tests/test_kron.py

+import numpy
+from theano import tensor, function
+from theano.tests import unittest_tools as utt
+from theano.sandbox.linalg.kron import Kron, kron
+
+try:
+    import scipy.linalg
+    imported_scipy = True
+except ImportError:
+    imported_scipy = False
+
+
+class TestKron(utt.InferShapeTester):
+
+    rng = numpy.random.RandomState(43)
+
+    def setUp(self):
+        super(TestKron, self).setUp()
+        self.op_class = Kron
+        self.op = kron
+
+    def test_perform(self):
+        assert imported_scipy, (
+            "Scipy not available. Scipy is needed for TestKron")
+        x = tensor.dmatrix()
+        y = tensor.dmatrix()
+        f = function([x, y], kron(x, y))
+
+        for shp0 in [(8, 6), (5, 8)]:
+            for shp1 in [(5, 7), (3, 3)]:
+                a = numpy.random.rand(*shp0)
+                b = numpy.random.rand(*shp1)
+                out = f(a, b)
+                assert numpy.allclose(out, scipy.linalg.kron(a, b))
+
+    def test_infer_shape(self):
+        x = tensor.dmatrix()
+        y = tensor.dmatrix()
+        self._compile_and_check([x, y], [self.op(x, y)],
+                                [numpy.random.rand(8, 5),
+                                 numpy.random.rand(3, 7)],
+                                self.op_class)
+        self._compile_and_check([x, y], [self.op(x, y)],
+                                [numpy.random.rand(2, 5),
+                                 numpy.random.rand(6, 3)],
+                                self.op_class)
+
+if __name__ == "__main__":
+    t = TestKron('setUp')
+    t.setUp()
+    t.test_perform()
+    t.test_infer_shape()