New config (added a hidden layer), small changes to train.py

2 files changed, 27 insertions, 2 deletions

diff --git a/config/simple_mlp_tgtcls_1.py b/config/simple_mlp_tgtcls_1.py
new file mode 100644
index 0000000..8d6c37b
--- /dev/null
+++ b/config/simple_mlp_tgtcls_1.py
@@ -0,0 +1,25 @@
+import cPickle
+
+import data
+
+import model.simple_mlp_tgtcls as model
+
+n_dow = 7       # number of division for dayofweek/dayofmonth/hourofday
+n_dom = 31
+n_hour = 24
+
+n_begin_end_pts = 5     # how many points we consider at the beginning and end of the known trajectory
+n_end_pts = 5
+
+n_valid = 1000
+
+with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f)
+
+dim_embed = 10
+dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed
+dim_hidden = [500]
+dim_output = tgtcls.shape[0]
+
+learning_rate = 0.0001
+momentum = 0.99
+batch_size = 32
diff --git a/train.py b/train.py
index dcf3fcd..5135544 100644
--- a/train.py
+++ b/train.py
@@ -110,7 +110,7 @@ def main():
                 # Checkpoint('model.pkl', every_n_batches=100),
                 Dump('model_data/' + model_name, every_n_batches=1000),
                 LoadFromDump('model_data/' + model_name),
-                FinishAfter(after_epoch=5)
+                FinishAfter(after_epoch=10),
                 ]
 
     main_loop = MainLoop(
@@ -124,7 +124,7 @@ def main():
     # Produce an output on the test data
     test_stream = setup_test_stream()
 
-    outfile = open("test-output.csv", "w")
+    outfile = open("test-output-%s.csv" % model_name, "w")
     outcsv = csv.writer(outfile)
     outcsv.writerow(["TRIP_ID", "LATITUDE", "LONGITUDE"])
     for out in apply_model.Apply(outputs=outputs, stream=test_stream, return_vars=['trip_id', 'outputs']):