Do not try to pickle `method_descriptor` objects

theano/tensor/raw_random.py

@@ -866,8 +866,11 @@ def multinomial(random_state, size=None, n=1, pvals=[0.5, 0.5],
 def random_make_inplace(node):
     op = node.op
     if isinstance(op, RandomFunction) and not op.inplace:
-        new_op = RandomFunction(op.fn, op.outtype, inplace=True,
-                                ndim_added=op.ndim_added)
+        # Read op_fn from op.state, not from op.fn, since op.fn
+        # may not be picklable.
+        op_fn, op_outtype, op_inplace, op_ndim_added = op.__getstate__()
+        new_op = RandomFunction(op_fn, op_outtype, inplace=True,
+                                ndim_added=op_ndim_added)
         return new_op.make_node(*node.inputs).outputs
     return False
 

theano/tensor/tests/test_raw_random.py

 from __future__ import print_function
-__docformat__ = "restructuredtext en"
 import numpy
+import pickle
+
 from theano.tests import unittest_tools as utt
 
 from theano.tensor.raw_random import *
@@ -10,6 +11,8 @@ from theano import tensor
 
 from theano import compile, config, gof
 
+__docformat__ = "restructuredtext en"
+
 
 class T_random_function(utt.InferShapeTester):
     def setUp(self):
@@ -1181,6 +1184,19 @@ class T_random_function(utt.InferShapeTester):
                                 pvals_val], RandomFunction)
         """
 
+    def test_pkl(self):
+        # Test pickling of RandomFunction.
+        # binomial was created by calling RandomFunction on a string,
+        # random_integers by calling it on a function.
+        rng_r = random_state_type()
+        post_bin_r, bin_sample = binomial(rng_r, (3, 5), 1, .3)
+        f = theano.function([rng_r], [post_bin_r, bin_sample])
+        pkl_f = pickle.dumps(f)
+
+        post_int_r, int_sample = random_integers(rng_r, (3, 5), -1, 8)
+        g = theano.function([rng_r], [post_int_r, int_sample])
+        pkl_g = pickle.dumps(g)
+
 
 if __name__ == '__main__':
     from theano.tests import main