Use MRG_RandomStreams instead for shared_randomstreams for GPU compat.

Author: abergeron

code/SdA.py

@@ -40,7 +40,7 @@
 
 import theano
 import theano.tensor as T
-from theano.tensor.shared_randomstreams import RandomStreams
+from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
 
 from logistic_sgd import LogisticRegression, load_data
 from mlp import HiddenLayer

code/dA.py

@@ -40,7 +40,7 @@
 
 import theano
 import theano.tensor as T
-from theano.tensor.shared_randomstreams import RandomStreams
+from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
 
 from logistic_sgd import load_data
 from utils import tile_raster_images

code/hmc/hmc.py

@@ -358,7 +358,7 @@ def new_from_shared_positions(
         stepsize = sharedX(initial_stepsize, 'hmc_stepsize')
         avg_acceptance_rate = sharedX(target_acceptance_rate,
                                       'avg_acceptance_rate')
-        s_rng = TT.shared_randomstreams.RandomStreams(seed)
+        s_rng = theano.sandbox.rng_mrg.MRG_RandomStreams(seed)
 
         # define graph for an `n_steps` HMC simulation
         accept, final_pos = hmc_move(

code/rbm.py

@@ -20,7 +20,7 @@
 import theano.tensor as T
 import os
 
-from theano.tensor.shared_randomstreams import RandomStreams
+from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
 
 from utils import tile_raster_images
 from logistic_sgd import load_data

code/rnnrbm.py

@@ -19,7 +19,7 @@
 from midi.utils import midiread, midiwrite
 import theano
 import theano.tensor as T
-from theano.tensor.shared_randomstreams import RandomStreams
+from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
 
 #Don't use a python long as this don't work on 32 bits computers.
 numpy.random.seed(0xbeef)