Have create_param() set the broadcast pattern of created shared varia…

…bles

lasagne/tests/test_utils.py

@@ -274,6 +274,15 @@ def test_create_param_retain_ndarray_dtype():
     assert (result.dtype == param.dtype)
 
 
+def test_create_param_broadcast_pattern():
+    from lasagne.utils import create_param
+    for shape in (10, 1, 20), (1, 2), (3, 1), (2, 3):
+        bcast = tuple(s == 1 for s in shape)
+        assert create_param(np.zeros, shape).broadcastable == bcast
+        assert create_param(np.zeros(shape, np.float32),
+                            shape).broadcastable == bcast
+
+
 def test_unroll_scan():
     from lasagne.utils import unroll_scan
     k = 2

lasagne/utils.py

@@ -348,7 +348,11 @@ def create_param(spec, shape, name=None):
         if spec.shape != shape:
             raise ValueError("%s has shape %s, should be %s" %
                              (err_prefix % "numpy array", spec.shape, shape))
-        spec = theano.shared(spec)
+        # We assume parameter variables do not change shape after creation.
+        # We can thus fix their broadcast pattern, to allow Theano to infer
+        # broadcastable dimensions of expressions involving these parameters.
+        bcast = tuple(s == 1 for s in shape)
+        spec = theano.shared(spec, broadcastable=bcast)
 
     if isinstance(spec, theano.Variable):
         # We cannot check the shape here, Theano expressions (even shared