Added __eq__ and __hash__ to Op Class and deleted them in function with props attribute.

theano/gof/op.py

@@ -575,6 +575,18 @@ class Op(utils.object2, PureOp, CLinkerOp):
     def __init__(self, use_c_code=theano.config.cxx):
         self._op_use_c_code = use_c_code
 
+    def __hash__(self):
+        if hasattr(self, 'props'):
+            return hash((type(self), self.props()))
+        else:
+            raise utils.MethodNotDefined("c_headers", type(self), self.__class__.__name__)
+
+    def __eq__(self, other):
+        if hasattr(self, 'props'):
+            return (type(self) == type(other) and self.props() == other.props())
+        else:
+            raise utils.MethodNotDefined("c_headers", type(self), self.__class__.__name__)
+
     def make_thunk(self, node, storage_map, compute_map, no_recycling):
         """
         :param node: something previously returned by self.make_node

theano/tensor/nlinalg.py

@@ -42,12 +42,6 @@ class MatrixPinv(Op):
         """
         return ()
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, x):
         x = as_tensor_variable(x)
         assert x.ndim == 2
@@ -84,12 +78,6 @@ class MatrixInverse(Op):
         """
         return ()
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, x):
         x = as_tensor_variable(x)
         assert x.ndim == 2
@@ -324,12 +312,6 @@ class Eig(Op):
         """
         return ()
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, x):
         x = as_tensor_variable(x)
         assert x.ndim == 2
@@ -440,12 +422,6 @@ class EighGrad(Op):
     def props(self):
         return (self.UPLO,)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def __str__(self):
         return 'EighGrad{%s}' % self.UPLO
 
@@ -511,12 +487,6 @@ class QRFull(Op):
     def __init__(self, mode):
         self.mode = mode
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, x):
         x = as_tensor_variable(x)
         assert x.ndim == 2, "The input of qr function should be a matrix."
@@ -548,12 +518,6 @@ class QRIncomplete(Op):
     def __init__(self, mode):
         self.mode = mode
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def props(self):
         return self.mode
 
@@ -644,12 +608,6 @@ class SVD(Op):
         self.full_matrices = full_matrices
         self.compute_uv = compute_uv
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def props(self):
         return self.full_matrices, self.compute_uv,
 

theano/tensor/slinalg.py

@@ -50,12 +50,6 @@ class Cholesky(Op):
         return (self.lower,
                 self.destructive)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def infer_shape(self, node, shapes):
         return [shapes[0]]
 
@@ -100,12 +94,6 @@ class CholeskyGrad(Op):
         return (self.lower,
                 self.destructive)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def __str__(self):
         if self.lower:
             lu = 'lower'
@@ -193,12 +181,6 @@ class Solve(Op):
                 self.overwrite_A,
                 self.overwrite_b)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return type(self) == type(other) and self.props() == other.props()
-
     def __repr__(self):
         return 'Solve{%s}' % str(self.props())
 
@@ -248,12 +230,6 @@ class Eigvalsh(Op):
     def props(self):
         return (self.lower,)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, a, b):
         assert imported_scipy, (
             "Scipy not  available. Scipy is needed for the Eigvalsh op")
@@ -317,12 +293,6 @@ class EigvalshGrad(Op):
     def props(self):
         return (self.lower,)
 
-    def __hash__(self):
-        return hash((type(self), self.props()))
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and self.props() == other.props())
-
     def make_node(self, a, b, gw):
         assert imported_scipy, (
             "Scipy not available. Scipy is needed for the GEigvalsh op")