Remove the Multinomial Op to MultinomialFromUniform, that's what it does.

theano/sandbox/multinomial.py

@@ -9,7 +9,8 @@ if cuda_available:
     from theano.sandbox.cuda import CudaNdarrayType
     from theano.sandbox.cuda.basic_ops import host_from_gpu, gpu_from_host
 
-class Multinomial(Op):
+class MultinomialFromUniform(Op):
+    '''Converts samples from a uniform into sample from a multinomial.'''
     def __init__(self, odtype):
         self.odtype=odtype
     def __eq__(self, other):
@@ -91,7 +92,7 @@ class Multinomial(Op):
         const int nb_outcomes = %(pvals)s->dimensions[1];
 
         //
-        // For each multinomials, loop over each possible outcome
+        // For each multinomial, loop over each possible outcome
         //
         for (int n = 0; n < nb_multi; ++n)
         {
@@ -117,10 +118,9 @@ class Multinomial(Op):
         }
         } // END NESTED SCOPE
         """ % locals()
-#multinomial = Multinomial()
 
 
-class GpuMultinomial(Multinomial):
+class GpuMultinomialFromUniform(MultinomialFromUniform):
 
     def make_node(self, pvals, unis):
         assert pvals.dtype == 'float32'
@@ -134,7 +134,9 @@ class GpuMultinomial(Multinomial):
         else:
             odtype = self.odtype
         if odtype != pvals.dtype:
-            raise NotImplementedError('GpuMultinomial works only if self.odtype == pvals.dtype', odtype, pvals.dtype)
+            raise NotImplementedError(
+                    'GpuMultinomialFromUniform works only if '
+                    'self.odtype == pvals.dtype', odtype, pvals.dtype)
         return Apply(self, [pvals, unis], [pvals.type()])
 
     def c_code_cache_version(self):
@@ -281,11 +283,11 @@ class GpuMultinomial(Multinomial):
 
 @local_optimizer()
 def use_gpu_multinomial(node):
-    if node.op == multinomial:
+    if isinstance(node.op, MultinomialFromUniform):
         p, u = node.inputs
         m, = node.outputs
         if p.dtype == u.dtype == m.dtype == 'float32':
-            gpu_op = GpuMultinomial(op.odtype)
+            gpu_op = GpuMultinomialFromUniform(op.odtype)
             return [host_from_gpu(gpu_op(*[gpu_from_host(i) for i in node.inputs]))]
 if cuda_enabled:#theano.config.device.startswith('gpu'):
     register_specialize(use_gpu_multinomial)

theano/sandbox/rng_mrg.py

@@ -759,7 +759,7 @@ class MRG_RandomStreams(object):
             assert ndim==1
             bcast = bcast+(pvals.type.broadcastable[-1],)
             unis = self.uniform(size=size, ndim=1)
-            op = multinomial.Multinomial(dtype)
+            op = multinomial.MultinomialFromUniform(dtype)
             return op(pvals, unis)
         else:
             raise NotImplementedError(("MRG_RandomStreams.multinomial only"