Implement HDist, transformer that selects k at a random position.

1 files changed, 11 insertions, 7 deletions

diff --git a/model.py b/model.py
index 95b002f..a5c820e 100644
--- a/model.py
+++ b/model.py
@@ -24,6 +24,7 @@ from blocks.extensions.monitoring import DataStreamMonitoring
 
 import data
 import transformers
+import hdist
 
 n_dow = 7       # number of division for dayofweek/dayofmonth/hourofday
 n_dom = 31
@@ -38,8 +39,8 @@ n_end_pts = 5
 dim_embed = 50
 dim_hidden = 200
 
-learning_rate = 0.1
-batch_size = 32
+learning_rate = 0.01
+batch_size = 64
 
 def main():
     # The input and the targets
@@ -67,7 +68,8 @@ def main():
     outputs = output_layer.apply(hidden)
 
     # Calculate the cost
-    cost = (outputs - y).norm(2, axis=1).mean()
+    # cost = (outputs - y).norm(2, axis=1).mean()
+    cost = hdist.hdist(outputs, y).mean()
     cost.name = 'cost'
 
     # Initialization
@@ -84,14 +86,16 @@ def main():
     # Load the training and test data
     train = data.train_data
     train = DataStream(train)
-    train = transformers.add_extremities(train, n_begin_end_pts)
+    train = transformers.add_first_k(n_begin_end_pts, train)
+    train = transformers.add_random_k(n_begin_end_pts, train)
     train = transformers.add_destination(train)
     train = transformers.Select(train, ('origin_stand', 'origin_call', 'first_k', 'last_k', 'destination'))
     train_stream = Batch(train, iteration_scheme=ConstantScheme(batch_size))
 
     valid = data.valid_data
     valid = DataStream(valid)
-    valid = transformers.add_extremities(valid, n_begin_end_pts)
+    valid = transformers.add_first_k(n_begin_end_pts, valid)
+    valid = transformers.add_random_k(n_begin_end_pts, valid)
     valid = transformers.add_destination(valid)
     valid = transformers.Select(valid, ('origin_stand', 'origin_call', 'first_k', 'last_k', 'destination'))
     valid_stream = Batch(valid, iteration_scheme=ConstantScheme(batch_size))
@@ -107,8 +111,8 @@ def main():
 
     extensions=[DataStreamMonitoring([cost], valid_stream,
                                      prefix='valid',
-                                     every_n_batches=100),
-                Printing(every_n_batches=100),
+                                     every_n_batches=1000),
+                Printing(every_n_batches=1000),
                 # Dump('taxi_model', every_n_batches=100),
                 # LoadFromDump('taxi_model'),
                 ]