Add optimization tests.

theano/sparse/tests/test_sp2.py

@@ -541,5 +541,72 @@ class SamplingDotTester(utt.InferShapeTester):
             return S2.sampling_dot(x, y, self.a[2])
         verify_grad_sparse(_helper, self.a[:2])
 
+
+# ##################
+# Optimization tests
+# ##################
+
+
+def test_local_mul_s_d():
+    mode = theano.compile.mode.get_default_mode()
+    mode = mode.including("specialize", "local_mul_s_d")
+
+    for sp_format in sparse.sparse_formats:
+        inputs = [getattr(theano.sparse, sp_format + '_matrix')(),
+                  tensor.matrix()]
+
+        f = theano.function(inputs,
+                            sparse.mul_s_d(*inputs),
+                            mode=mode)
+
+        assert not any(isinstance(node.op, sparse.MulSD) for node
+                       in f.maker.env.toposort())
+
+def test_local_mul_s_v():
+    mode = theano.compile.mode.get_default_mode()
+    mode = mode.including("specialize", "local_mul_s_v")
+
+    for sp_format in ['csr']:  # Not implemented for other format
+        inputs = [getattr(theano.sparse, sp_format + '_matrix')(),
+                  tensor.vector()]
+
+        f = theano.function(inputs,
+                            S2.mul_s_v(*inputs),
+                            mode=mode)
+
+        assert not any(isinstance(node.op, S2.MulSV) for node
+                       in f.maker.env.toposort())
+
+def test_local_structured_add_s_v():
+    mode = theano.compile.mode.get_default_mode()
+    mode = mode.including("specialize", "local_structured_add_s_v")
+
+    for sp_format in ['csr']:  # Not implemented for other format
+        inputs = [getattr(theano.sparse, sp_format + '_matrix')(),
+                  tensor.vector()]
+
+        f = theano.function(inputs,
+                            S2.structured_add_s_v(*inputs),
+                            mode=mode)
+
+        assert not any(isinstance(node.op, S2.StructuredAddSV) for node
+                       in f.maker.env.toposort())
+
+def test_local_sampling_dot_csr():
+    mode = theano.compile.mode.get_default_mode()
+    mode = mode.including("specialize", "local_sampling_dot_csr")
+
+    for sp_format in ['csr']:  # Not implemented for other format
+        inputs = [tensor.matrix(),
+                  tensor.matrix(),
+                  getattr(theano.sparse, sp_format + '_matrix')()]
+
+        f = theano.function(inputs,
+                            S2.sampling_dot(*inputs),
+                            mode=mode)
+
+        assert not any(isinstance(node.op, S2.SamplingDot) for node
+                       in f.maker.env.toposort())
+
 if __name__ == '__main__':
     unittest.main()