SGrad, improvements to formula

formula.py

@@ -11,6 +11,23 @@ def _zip(*lists):
     else:
         return zip(*lists)
 
+
+
+# x = ivector()
+# y = ivector()
+# e = x + y
+
+# f = Formula(x = x, y = y, e = e)
+
+# y = x + x
+# g = Formula(x=x,y=y)
+
+# x2 = x + x
+# g = Formula(x=x, x2=x2)
+
+
+
+
 class Formula(utils.object2):
     
     def __init__(self, symtable_d = {}, **symtable_kwargs):
@@ -257,11 +274,23 @@ class Formulas(utils.object2):
 
 
 
+
+
 # class Test(Formulas):
 #     x = T.ivector()
 #     y = T.ivector()
 #     e = x + y + 21
 
+# x = T.ivector()
+# y = T.ivector()
+# e = x + y + 21
+
+# f1 = Formula(x = x, y = y, e = e)
+
+# Test() -> f1.clone()
+
+
+
 # f = Test()
 # print f
 # print f.reassign(x = T.ivector())
@@ -317,6 +346,8 @@ print unicode(g)
 
 
 
+
+
 # lr = 0.01
 # def autoassociator_f(x, w, b, c):
 #     reconstruction = sigmoid(T.dot(sigmoid(T.dot(x, w) + b), w.T) + c)

tensor.py

@@ -253,6 +253,11 @@ def tensor(*args, **kwargs):
 
 def _multi(*fns):
     def f2(f, names):
+        if isinstance(names, int):
+            if names == 1:
+                return f()
+            else:
+                return [f() for i in xrange(names)]
         if len(names) == 1:
             return f(names)
         else:
@@ -639,6 +644,7 @@ def transpose(x, **kwargs):
 
 
 
+
 class Subtensor(Op):
     """Return a subtensor view
 
@@ -908,7 +914,7 @@ class Dot(Op):
     def grad(self, (x, y), (gz,)):
         return dot(gz, y.T), dot(x.T, gz)
     def __str__(self):
-        return "Dot"
+        return "dot"
 dot = Dot()
 
 class Gemm(Op):
@@ -1136,6 +1142,14 @@ gemm = Gemm()
 # Gradient
 #########################
 
+class SGrad(gof.Op):
+    def make_node(self, cost, wrt):
+        return Apply(self, [cost, wrt], [wrt.type()])
+    def expand(self, r):
+        cost, wrt = r.owner.inputs
+        return grad(cost, wrt)
+sgrad = SGrad()
+
 def grad(cost, wrt, g_cost=None):
     """
     @type cost: L{Result}