Revert previous change to replace dot22 with gemm instead of dot22scalar

theano/tensor/blas.py

@@ -2043,12 +2043,8 @@ def local_dot22_to_dot22scalar(node):
         a = T.cast(_as_scalar(m.owner.inputs[scalar_idx],
                               dtype=d.dtype), d.type.dtype)
         assert not a.type.ndim
+        dot = _dot22scalar(d.owner.inputs[0], d.owner.inputs[1], a)
 
-        z = T.AllocEmpty(d.owner.inputs[0].dtype)(d.owner.inputs[0].shape[0],
-                                                  d.owner.inputs[1].shape[1])
-        zero = T.as_tensor_variable(numpy.asarray(0, dtype=a.dtype))
-        dot = gemm(z, a, d.owner.inputs[0], d.owner.inputs[1], zero)
-        
         # The other inputs to the original node that were
         # neither part of the dot22 or this mul should be
         # factors in the returned "mul" node.
@@ -2083,16 +2079,12 @@ def local_dot22_to_dot22scalar(node):
     a = T.cast(i_scalar[scalar_idx], d.type.dtype)
     assert not a.type.ndim
     if len(o) == 0:
-        z = T.AllocEmpty(d.owner.inputs[0].dtype)(d.owner.inputs[0].shape[0],
-                                                  d.owner.inputs[1].shape[1])
-        zero = T.as_tensor_variable(numpy.asarray(0, dtype=a.dtype))
-        return [gemm(z, a, d.owner.inputs[0], d.owner.inputs[1], zero)]
+        return [_dot22scalar(d.owner.inputs[0], d.owner.inputs[1], a)]
     else:
-        z = T.AllocEmpty(d.owner.inputs[0].dtype)(d.owner.inputs[0].shape[0],
-                                                  d.owner.inputs[1].shape[1])
-        zero = T.as_tensor_variable(numpy.asarray(0, dtype=a.dtype))
-        return [T.mul(gemm(z, a, d.owner.inputs[0], d.owner.inputs[1],
-                      zero), *o)]
+        return [T.mul(_dot22scalar(d.owner.inputs[0],
+                                   d.owner.inputs[1], a), *o)]
+
+
 # must happen after gemm as the gemm optimizer don't understant
 # dot22scalar and gemm give more speed up then dot22scalar
 blas_optdb.register('local_dot22_to_dot22scalar',