Merge pull request #148 from nouiz/fix_extract_diag

theano/sandbox/linalg/ops.py

@@ -463,6 +463,7 @@ solve = Solve() # general solve
 #TODO: Optimizations to replace multiplication by matrix inverse with solve() Op (still unwritten)
 
 class ExtractDiag(Op):
+    """ Return the diagonal of matrix """
     def __init__(self, view=False):
         self.view = view
         if self.view:
@@ -485,8 +486,12 @@ class ExtractDiag(Op):
         z, = outs
         #for some reason numpy.diag(x) is really slow
         N,M = x.shape
-        assert N==M
+
+        if x.shape[0] < x.shape [1]:
+            rval = x[:,0]
+        else:
             rval = x[0]
+
         rval.strides = (x.strides[0]+x.strides[1],)
         if self.view:
             z[0] = rval
@@ -501,7 +506,8 @@ class ExtractDiag(Op):
 
     def infer_shape(self, node, shapes):
         x_s, = shapes
-        return [(x_s[0],)]
+        shp = tensor.min(node.inputs[0].shape)
+        return [(shp,)]
 
 extract_diag = ExtractDiag()
 #TODO: optimization to insert ExtractDiag with view=True

theano/sandbox/linalg/tests/test_linalg.py

@@ -182,20 +182,14 @@ def test_extract_diag():
     g = extract_diag(x)
     f = theano.function([x], g)
 
-    m = rng.rand(3,3).astype(config.floatX)
+    for shp in [(2, 3), (3, 2), (3, 3)]:
+        m = rng.rand(*shp).astype(config.floatX)
         v = numpy.diag(m)
         r = f(m)
         # The right diagonal is extracted
         assert (r == v).all()
 
-    m = rng.rand(2, 3).astype(config.floatX)
-    ok = False
-    try:
-        r = f(m)
-    except Exception:
-        ok = True
-    assert ok
-
+    # Test we accept only matrix
     xx = theano.tensor.vector()
     ok = False
     try:
@@ -204,11 +198,14 @@ def test_extract_diag():
         ok = True
     assert ok
 
+    # Test infer_shape
     f = theano.function([x], g.shape)
     topo = f.maker.env.toposort()
+    if config.mode != 'FAST_COMPILE':
         assert sum([node.op.__class__ == ExtractDiag for node in topo]) == 0
-    m = rng.rand(3,3).astype(config.floatX)
-    assert f(m) == 3
+    for shp in [(2, 3), (3, 2), (3, 3)]:
+        m = rng.rand(*shp).astype(config.floatX)
+        assert f(m) == min(shp)
 
 # not testing the view=True case since it is not used anywhere.
 
@@ -219,7 +216,8 @@ def test_trace():
     g = trace(x)
     f = theano.function([x], g)
 
-    m = rng.rand(4, 4).astype(config.floatX)
+    for shp in [(2, 3), (3, 2), (3, 3)]:
+        m = rng.rand(*shp).astype(config.floatX)
         v = numpy.trace(m)
         assert v == f(m)