Small refactoring to speed up get_scalar_constant_value.

theano/tensor/basic.py

@@ -508,6 +508,12 @@ class EmptyConstantError(NotScalarConstantError):
     """
 
 
+get_scalar_constant_value_elemwises = (
+    scal.Cast, scal.Switch,
+    scal.NEQ, scal.EQ,
+    scal.LT, scal.GT, scal.LE, scal.GE,
+    scal.Sub, scal.Add, scal.Mod, scal.Mul,
+    scal.IntDiv, scal.TrueDiv)
 def get_scalar_constant_value(v):
     """return the constant scalar(0-D) value underlying variable `v`
 
@@ -562,7 +568,7 @@ def get_scalar_constant_value(v):
                                    compile.ops.OutputGuard,
                                    compile.DeepCopyOp)):
             return get_scalar_constant_value(v.owner.inputs[0])
-        if (isinstance(v.owner.op, theano.compile.ops.Shape_i) and
+        elif (isinstance(v.owner.op, theano.compile.ops.Shape_i) and
             isinstance(v.owner.inputs[0], Constant)):
             return v.owner.inputs[0].data.shape[v.owner.op.i]
         # Don't act as the constant_folding optimization here as this
@@ -570,26 +576,29 @@ def get_scalar_constant_value(v):
         # mess with the stabilization optimization and be too slow.
         # We put all the scalar Ops used by get_canonical_form_slice()
         # to allow it to determine the broadcast pattern correctly.
-        if ((isinstance(v.owner.op, Elemwise) and
-             isinstance(v.owner.op.scalar_op, scal.Second)) or
-            isinstance(v.owner.op, scal.Second)):
-            # We don't need both input to be constant for second
-            shape, val = v.owner.inputs
-            return get_scalar_constant_value(val)
-        elemwises = (scal.Cast, scal.Switch,
-                     scal.NEQ, scal.EQ,
-                     scal.LT, scal.GT, scal.LE, scal.GE,
-                     scal.Sub, scal.Add, scal.Mod, scal.Mul,
-                     scal.IntDiv, scal.TrueDiv)
-        if (isinstance(v.owner.op, Elemwise) and
-            len(v.owner.outputs) == 1 and
-            (isinstance(v.owner.op.scalar_op, elemwises) or
-            isinstance(v.owner.op, elemwises))):
-            const = [get_scalar_constant_value(i) for i in v.owner.inputs]
-            ret = [[None]]
-            v.owner.op.perform(v.owner, const, ret)
-            return ret[0][0]
-        if isinstance(v.owner.op, theano.tensor.subtensor.Subtensor) and v.ndim == 0:
+        elif isinstance(v.owner.op, scal.ScalarOp):
+            if isinstance(v.owner.op, scal.Second):
+                # We don't need both input to be constant for second
+                shape, val = v.owner.inputs
+                return get_scalar_constant_value(val)
+            if isinstance(v.owner.op, get_scalar_constant_value_elemwises):
+                const = [get_scalar_constant_value(i)
+                         for i in v.owner.inputs]
+                ret = [[None]]
+                v.owner.op.perform(v.owner, const, ret)
+                return ret[0][0]
+        elif isinstance(v.owner.op, Elemwise):
+            if isinstance(v.owner.op.scalar_op, scal.Second):
+                # We don't need both input to be constant for second
+                shape, val = v.owner.inputs
+                return get_scalar_constant_value(val)
+            elif isinstance(v.owner.op.scalar_op,
+                            get_scalar_constant_value_elemwises):
+                const = [get_scalar_constant_value(i) for i in v.owner.inputs]
+                ret = [[None]]
+                v.owner.op.perform(v.owner, const, ret)
+                return ret[0][0]
+        elif isinstance(v.owner.op, theano.tensor.subtensor.Subtensor) and v.ndim == 0:
             if isinstance(v.owner.inputs[0], TensorConstant):
                 cdata = tuple(v.owner.op.get_constant_idx(v.owner.inputs))
                 try:
@@ -626,7 +635,7 @@ def get_scalar_constant_value(v):
                 # join can cast implicitly its input in some case.
                 return theano._asarray(ret, dtype=v.type.dtype)
 
-            if (v.owner.inputs[0].owner and
+            elif (v.owner.inputs[0].owner and
                 isinstance(v.owner.inputs[0].owner.op,
                            theano.tensor.opt.MakeVector) and
                 # MakeVector normally accept only scalar as input.