Allow permutation to return just one permutation.

theano/tensor/raw_random.py

@@ -183,7 +183,11 @@ class RandomFunction(gof.Op):
         draw.
 
         """
-        shape = tensor.as_tensor_variable(shape, ndim=1)
+        shape_ = tensor.as_tensor_variable(shape, ndim=1)
+        if shape == ():
+            shape = shape_.astype('int32')
+        else:
+            shape = shape_
         assert shape.type.ndim == 1
         assert (shape.type.dtype == 'int64') or (shape.type.dtype == 'int32')
         if not isinstance(r.type, RandomStateType):
@@ -700,6 +704,14 @@ def permutation(random_state, size=None, n=1, ndim=None, dtype='int64'):
     :note:
         Note that the output will then be of dimension ndim+1.
     """
+    if size is None or size == ():
+        if not(ndim is None or ndim == 1):
+            raise TypeError(
+                "You asked for just one permutation but asked for more then 1 dimensions.")
+        ndim = 1
+        size = ()
+        bcast = ()
+    else:
         ndim, size, bcast = _infer_ndim_bcast(ndim, size)
     #print "NDIM", ndim, size
     op = RandomFunction(permutation_helper,

theano/tensor/tests/test_raw_random.py

@@ -230,7 +230,7 @@ class T_random_function(utt.InferShapeTester):
         rng_R = random_state_type()
 
         # No shape, no args -> TypeError
-        self.assertRaises(TypeError, permutation, rng_R, size=None, ndim=2)
+        self.assertRaises(TypeError, poisson, rng_R, size=None, ndim=2)
 
     def test_random_function_ndim_added(self):
         """Test that random_function helper function accepts ndim_added as
@@ -561,6 +561,19 @@ class T_random_function(utt.InferShapeTester):
         self.assertTrue(numpy.all(val0 == numpy_val0))
         self.assertTrue(numpy.all(val1 == numpy_val1))
 
+        # Test that we can generate a list: have size=None or ().
+        for ndim in [1, None]:
+            post_r, out = permutation(rng_R, n=10, size=None, ndim=ndim)
+            inp = compile.In(rng_R,
+                             value=numpy.random.RandomState(utt.fetch_seed()),
+                             update=post_r, mutable=True)
+            f = theano.function([inp], out)
+            o = f()
+            assert o.shape == (10,)
+            assert (numpy.sort(o) == numpy.arange(10)).all()
+        # Wrong number of dimensions asked
+        self.assertRaises(TypeError, permutation, rng_R, size=None, ndim=2)
+
     def test_multinomial(self):
         """Test that raw_random.multinomial generates the same
         results as numpy."""