taxi

commit 5096e0cdae167122d07b09cd207a04f28ea5c3f5
parent 98139f573eb179c8f5a06ba6c8d8883376814ccf
Author: Alex Auvolat <alex.auvolat@ens.fr>
Date:   Thu,  2 Jul 2015 13:23:28 -0400

Add random seed for TaxiGenerateSplits and for fuel

Diffstat:
M
data/transformers.py
 | 
8
++++++--
M
train.py
 | 
18
+++++++++++-------

2 files changed, 17 insertions(+), 9 deletions(-)
diff --git a/data/transformers.py b/data/transformers.py
@@ -1,8 +1,10 @@
 import datetime
-import random
 
 import numpy
 import theano
+
+import fuel
+
 from fuel.schemes import ConstantScheme
 from fuel.transformers import Batch, Mapping, SortMapping, Transformer, Unpack
 
@@ -66,13 +68,15 @@ class TaxiGenerateSplits(Transformer):
         self.id_latitude = data_stream.sources.index('latitude')
         self.id_longitude = data_stream.sources.index('longitude')
 
+        self.rng = numpy.random.RandomState(fuel.config.default_seed)
+
     def get_data(self, request=None):
         if request is not None:
             raise ValueError
         while self.isplit >= len(self.splits):
             self.data = next(self.child_epoch_iterator)
             self.splits = range(len(self.data[self.id_longitude]))
-            random.shuffle(self.splits)
+            self.rng.shuffle(self.splits)
             if self.max_splits != -1 and len(self.splits) > self.max_splits:
                 self.splits = self.splits[:self.max_splits]
             self.isplit = 0
diff --git a/train.py b/train.py
@@ -9,12 +9,16 @@ from functools import reduce
 
 from theano import tensor
 
+import blocks
+import fuel
+
 from blocks import roles
 from blocks.algorithms import AdaDelta, CompositeRule, GradientDescent, RemoveNotFinite, StepRule, Momentum
 from blocks.extensions import Printing, FinishAfter
 from blocks.extensions.monitoring import DataStreamMonitoring, TrainingDataMonitoring
-import blocks
+
 blocks.config.default_seed = 123
+fuel.config.default_seed = 123
 
 try:
     from blocks.extras.extensions.plotting import Plot
@@ -104,12 +108,12 @@ if __name__ == "__main__":
                                      every_n_batches=1000),
                 Printing(every_n_batches=1000),
 
-                SaveLoadParams(dump_path, cg,
-                               before_training=True,        # before training -> load params
-                               every_n_batches=1000,        # every N batches -> save params
-                               after_epoch=True,            # after epoch -> save params
-                               after_training=True,         # after training -> save params
-                               ),
+                # SaveLoadParams(dump_path, cg,
+                #                before_training=True,        # before training -> load params
+                #                every_n_batches=1000,        # every N batches -> save params
+                #                after_epoch=True,            # after epoch -> save params
+                #                after_training=True,         # after training -> save params
+                #                ),
 
                 RunOnTest(model_name,
                           model,