- exposed eig in linalg

theano/sandbox/linalg/__init__.py

 
 from ops import (cholesky, matrix_inverse, solve,
         diag, extract_diag, alloc_diag,
-        det, psd,
+        det, psd, eig,
         trace, spectral_radius_bound)

theano/sandbox/linalg/ops.py

@@ -900,7 +900,9 @@ class Eig(Op):
 
     def make_node(self, x):
         x = as_tensor_variable(x)
-        return Apply(self, [x], [x.type(), x.type()])
+        w = theano.tensor.vector(x.dtype)
+        v = theano.tensor.matrix(x.dtype)
+        return Apply(self, [x], [w, v])
 
     def perform(self, node, (x,), (w, v)):
         try:
@@ -909,6 +911,10 @@ class Eig(Op):
             logger.debug('Failed to find eig of %s' % str(node.inputs[0]))
             raise
 
+    def infer_shape(self, node, shapes):
+        n = shapes[0][0]
+        return [(n,), (n,n)]
+
     def __str__(self):
         return "Eig"
 

theano/sandbox/linalg/tests/test_linalg.py

@@ -26,6 +26,7 @@ from theano.sandbox.linalg.ops import (cholesky,
                                        matrix_dot,
                                        spectral_radius_bound,
                                        imported_scipy,
+                                       Eig,
                                        )
 
 from nose.plugins.skip import SkipTest
@@ -467,3 +468,20 @@ class test_Solve(utt.InferShapeTester):
                                  numpy.asarray(rng.rand(5),
                                                dtype=config.floatX)],
                                 self.op_class)
+
+class test_Eig(utt.InferShapeTester):
+    def setUp(self):
+        super(test_Eig, self).setUp()
+        self.op_class = Eig
+        self.op = Eig()
+
+    def test_infer_shape(self):
+        rng = numpy.random.RandomState(utt.fetch_seed())
+        A = theano.tensor.matrix()
+        X = numpy.asarray(rng.rand(5, 5),
+                          dtype=config.floatX)
+        self._compile_and_check([A],  # theano.function inputs
+                                self.op(A),  # theano.function outputs
+                                # A must be square
+                                [X.dot(X.T)],
+                                self.op_class)