added test for output dtype (solve)

theano/tensor/tests/test_slinalg.py

@@ -229,6 +229,45 @@ class test_Solve(utt.InferShapeTester):
         assert numpy.allclose(scipy.linalg.solve_triangular(U_val, b_val, lower=False),
                               upper_solve_func(U_val, b_val))
 
+    def test_solve_dtype(self):
+        if not imported_scipy:
+            raise SkipTest("Scipy needed for the Solve op.")
+        A_32 = tensor.fmatrix()
+        b_32 = tensor.fmatrix()
+        A_64 = tensor.dmatrix()
+        b_64 = tensor.dmatrix()
+        A_val = numpy.eye(2)
+        b_val = numpy.ones((2, 1))
+
+        # A 64, b 64
+        x_6464_out = solve(A_64, b_64)
+        fn_6464 = function([A_64, b_64], x_6464_out)
+        x_6464_result = fn_6464(A_val.astype('float64'), b_val.astype('float64'))
+        assert x_6464_out.dtype == 'float64'
+        assert x_6464_result.dtype == 'float64'
+
+        # A 32, b 32
+        x_3232_out = solve(A_32, b_32)
+        fn_3232 = function([A_32, b_32], x_3232_out)
+        x_3232_result = fn_3232(A_val.astype('float32'), b_val.astype('float32'))
+        assert x_3232_out.dtype == 'float32'
+        assert x_3232_result.dtype == 'float32'
+
+        # A 64, b 32
+        x_6432_out = solve(A_64, b_32)
+        fn_6432 = function([A_64, b_32], x_6432_out)
+        x_6432_result = fn_6432(A_val.astype('float64'), b_val.astype('float32'))
+        assert x_6432_out.dtype == 'float64'
+        assert x_6432_result.dtype == 'float64'
+
+        # A 32, b 64
+        x_3264_out = solve(A_32, b_64)
+        fn_3264 = function([A_32, b_64], x_3264_out)
+        x_3264_result = fn_3264(A_val.astype('float32'), b_val.astype('float64'))
+        assert x_3264_out.dtype == 'float64'
+        assert x_3264_result.dtype == 'float64'
+
+
     def verify_solve_grad(self, m, n, A_structure, lower, rng):
         # ensure diagonal elements of A relatively large to avoid numerical
         # precision issues