Add multinomial to raw_random and RandomStream

theano/tensor/randomstreams.py

@@ -182,3 +182,10 @@ class RandomStreams(Component):
         """
         return self.gen(raw_random.permutation, *args, **kwargs)
 
+    def multinomial(self, *args, **kwargs):
+        """Return a symbolic multinomial sample
+
+        This is a shortcut for a call to `self.gen`
+        """
+        return self.gen(raw_random.multinomial, *args, **kwargs)
+

theano/tensor/raw_random.py

@@ -171,7 +171,7 @@ class RandomFunction(gof.Op):
         if not self.inplace:
             r = copy(r)
         rout[0] = r
-        rval = self.fn(r, *(args + [shape]))
+        rval = self.fn(r, *(args + [tuple(shape)]))
         if not isinstance(rval, numpy.ndarray) \
                or str(rval.dtype) != node.outputs[1].type.dtype:
             out[0] = numpy.asarray(rval, dtype = node.outputs[1].type.dtype)
@@ -301,6 +301,12 @@ Usage: permutation(random_state, size, n)
 Returns a permutation of the integers between 0 and n-1.
 """
 
+multinomial = random_function('multinomial', 'float64', 1, [0.5, 0.5])
+multinomial.__doc__ = """
+Usage: multinomial(random_state, size, n, pvals)
+Sample from a multinomial distribution defined by probabilities pvals.
+"""
+
 
 @gof.local_optimizer([None])
 def random_make_inplace(node):