Merge pull request #3181 from harlouci/props_sandbox

theano/sandbox/fourier.py

@@ -11,6 +11,9 @@ from theano.gof import Op, Apply, generic
 
 
 class GradTodo(Op):
+
+    __props__ = ()
+
     def make_node(self, x):
         return Apply(self, [x], [x.type()])
 
@@ -40,22 +43,12 @@ class FFT(Op):
 
     half = False
     """Only return the first half (positive-valued) of the frequency components"""
+    __props__ = ("half", "inverse")
 
     def __init__(self, half=False, inverse=False):
         self.half = half
         self.inverse = inverse
 
-    def __eq__(self, other):
-        return (type(self) == type(other) and
-                self.half == other.half and
-                self.inverse == other.inverse)
-
-    def __hash__(self):
-        return hash(type(self)) ^ hash(self.half) ^ 9828743 ^ (self.inverse)
-
-    def __ne__(self, other):
-        return not(self == other)
-
     def make_node(self, frames, n, axis):
         """ compute an n-point fft of frames along given axis """
         _frames = tensor.as_tensor(frames, ndim=2)

theano/sandbox/multinomial.py

@@ -14,15 +14,11 @@ if cuda_available:
 
 class MultinomialFromUniform(Op):
     '''Converts samples from a uniform into sample from a multinomial.'''
+    __props__ = ("odtype",)
+
     def __init__(self, odtype):
         self.odtype = odtype
 
-    def __eq__(self, other):
-        return type(self) == type(other) and self.odtype == other.odtype
-
-    def __hash__(self):
-        return hash((type(self), self.odtype))
-
     def __str__(self):
         return '%s{%s}' % (self.__class__.__name__, self.odtype)
 

theano/sandbox/neighbourhoods.py

@@ -16,6 +16,10 @@ from theano import gof, Op
 
 
 class NeighbourhoodsFromImages(Op):
+
+    __props__ = ("n_dims_before", "dims_neighbourhoods", "strides",
+                 "ignore_border", "inverse")
+
     def __init__(self, n_dims_before, dims_neighbourhoods,
                  strides=None, ignore_border=False, inverse=False):
         """
@@ -84,20 +88,6 @@ class NeighbourhoodsFromImages(Op):
 
         self.code_string, self.code = self.make_py_code()
 
-    def __eq__(self, other):
-        return type(self) == type(other) and \
-            self.n_dims_before == other.n_dims_before and \
-            self.dims_neighbourhoods == other.dims_neighbourhoods and \
-            self.strides == other.strides and \
-            self.ignore_border == other.ignore_border
-
-    def __hash__(self):
-        return hash(type(self)) ^ \
-            hash(self.n_dims_before) ^ \
-            hash(self.dims_neighbourhoods) ^ \
-            hash(self.strides) ^ \
-            hash(self.ignore_border)
-
     def __str__(self):
         return '%s{%s,%s,%s,%s}' % (self.__class__.__name__,
                                     self.n_dims_before,

theano/sandbox/rng_mrg.py

@@ -78,11 +78,7 @@ class DotModulo(Op):
 
     We do this 2 times on 2 triple inputs and concatenating the output
     """
-    def __eq__(self, other):
-        return type(self) == type(other)
-
-    def __hash__(self):
-        return hash(type(self))
+    __props__ = ()
 
     def make_node(self, A, s, m, A2, s2, m2):
         return Apply(self, [A, s, m, A2, s2, m2], [s.type()])
@@ -286,6 +282,9 @@ def mrg_next_value(rstate, new_rstate):
 
 
 class mrg_uniform_base(Op):
+
+    __props__ = ("output_type", "inplace")
+
     def __init__(self, output_type, inplace=False):
         Op.__init__(self)
         self.output_type = output_type
@@ -294,14 +293,6 @@ class mrg_uniform_base(Op):
             self.destroy_map = {0: [0]}
         self.warned_numpy_version = False
 
-    def __eq__(self, other):
-        return (type(self) == type(other) and
-                self.output_type == other.output_type and
-                self.inplace == other.inplace)
-
-    def __hash__(self):
-        return hash(type(self)) ^ hash(self.output_type) ^ hash(self.inplace)
-
     def __str__(self):
         if self.inplace:
             s = "inplace"