Move weights init to config files ; fix s/time/travel_time

1 files changed, 10 insertions, 12 deletions

diff --git a/model/time_simple_mlp.py b/model/time_simple_mlp.py
index 1568ed3..9e1b10a 100644
--- a/model/time_simple_mlp.py
+++ b/model/time_simple_mlp.py
@@ -1,8 +1,6 @@
 from blocks.bricks import MLP, Rectifier, Linear, Sigmoid, Identity
 from blocks.bricks.lookup import LookupTable
 
-from blocks.initialization import IsotropicGaussian, Constant
-
 from theano import tensor
 
 import data
@@ -11,11 +9,11 @@ import error
 class Model(object):
     def __init__(self, config):
         # The input and the targets
-        x_firstk_latitude = (tensor.matrix('first_k_latitude') - data.porto_center[0]) / data.data_std[0]
-        x_firstk_longitude = (tensor.matrix('first_k_longitude') - data.porto_center[1]) / data.data_std[1]
+        x_firstk_latitude = (tensor.matrix('first_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0]
+        x_firstk_longitude = (tensor.matrix('first_k_longitude') - data.train_gps_mean[1]) / data.train_gps_std[1]
 
-        x_lastk_latitude = (tensor.matrix('last_k_latitude') - data.porto_center[0]) / data.data_std[0]
-        x_lastk_longitude = (tensor.matrix('last_k_longitude') - data.porto_center[1]) / data.data_std[1]
+        x_lastk_latitude = (tensor.matrix('last_k_latitude') - data.train_gps_mean[0]) / data.train_gps_std[0]
+        x_lastk_longitude = (tensor.matrix('last_k_longitude') - data.train_gps_mean[1]) / data.train_gps_std[1]
 
         input_list = [x_firstk_latitude, x_firstk_longitude, x_lastk_latitude, x_lastk_longitude]
         embed_tables = []
@@ -29,7 +27,7 @@ class Model(object):
             embed_tables.append(tbl)
             input_list.append(tbl.apply(vardata))
 
-        y = tensor.lvector('time')
+        y = tensor.lvector('travel_time')
 
         # Define the model
         mlp = MLP(activations=[Rectifier() for _ in config.dim_hidden] + [Identity()],
@@ -38,7 +36,7 @@ class Model(object):
         # Create the Theano variables
         inputs = tensor.concatenate(input_list, axis=1)
         # inputs = theano.printing.Print("inputs")(inputs)
-        outputs = tensor.exp(mlp.apply(inputs) + 2)
+        outputs = config.exp_base ** mlp.apply(inputs)
 
         # outputs = theano.printing.Print("outputs")(outputs)
         # y = theano.printing.Print("y")(y)
@@ -51,9 +49,9 @@ class Model(object):
 
         # Initialization
         for tbl in embed_tables:
-            tbl.weights_init = IsotropicGaussian(0.001)
-        mlp.weights_init = IsotropicGaussian(0.01)
-        mlp.biases_init = Constant(0.001)
+            tbl.weights_init = config.embed_weights_init
+        mlp.weights_init = config.mlp_weights_init
+        mlp.biases_init = config.mlp_biases_init
 
         for tbl in embed_tables:
             tbl.initialize()
@@ -62,4 +60,4 @@ class Model(object):
         self.cost = cost
         self.monitor = [cost]
         self.outputs = outputs
-        self.pred_vars = ['time']
+        self.pred_vars = ['travel_time']