Fix CSV import (partially)

1 files changed, 21 insertions, 15 deletions

diff --git a/model.py b/model.py
index 6a8be9d..065db7e 100644
--- a/model.py
+++ b/model.py
@@ -29,7 +29,7 @@ from fuel.schemes import ConstantScheme, SequentialExampleScheme
 from blocks.algorithms import GradientDescent, Scale, AdaDelta, Momentum
 from blocks.graph import ComputationGraph
 from blocks.main_loop import MainLoop
-from blocks.extensions import Printing
+from blocks.extensions import Printing, FinishAfter
 from blocks.extensions.saveload import Dump, LoadFromDump, Checkpoint
 from blocks.extensions.monitoring import DataStreamMonitoring
 
@@ -48,9 +48,9 @@ def setup_stream():
     # Load the training and test data
     train = H5PYDataset('/data/lisatmp3/simonet/taxi/data.hdf5',
                         which_set='train',
-                        subset=slice(0, config.train_size - config.n_valid),
+                        subset=slice(0, data.dataset_size - config.n_valid),
                         load_in_memory=True)
-    train = DataStream(train, iteration_scheme=SequentialExampleScheme(config.train_size - config.n_valid))
+    train = DataStream(train, iteration_scheme=SequentialExampleScheme(data.dataset_size - config.n_valid))
     train = transformers.add_first_k(config.n_begin_end_pts, train)
     train = transformers.add_random_k(config.n_begin_end_pts, train)
     train = transformers.add_destination(train)
@@ -61,7 +61,7 @@ def setup_stream():
 
     valid = H5PYDataset('/data/lisatmp3/simonet/taxi/data.hdf5',
                         which_set='train',
-                        subset=slice(config.train_size - config.n_valid, config.train_size),
+                        subset=slice(data.dataset_size - config.n_valid, data.dataset_size),
                         load_in_memory=True)
     valid = DataStream(valid, iteration_scheme=SequentialExampleScheme(config.n_valid))
     valid = transformers.add_first_k(config.n_begin_end_pts, valid)
@@ -74,6 +74,18 @@ def setup_stream():
     
     return (train_stream, valid_stream)
 
+def setup_test_stream():
+    test = data.test_data
+    
+    test = DataStream(test)
+    test = transformers.add_first_k(config.n_begin_end_pts, test)
+    test = transformers.add_last_k(config.n_begin_end_pts, test)
+    test = transformers.Select(test, ('trip_id', 'origin_stand', 'origin_call', 'first_k_latitude',
+                                      'last_k_latitude', 'first_k_longitude', 'last_k_longitude'))
+    test_stream = Batch(test, iteration_scheme=ConstantScheme(1000))
+
+    return test_stream
+
 def main():
     # The input and the targets
     x_firstk_latitude = (tensor.matrix('first_k_latitude') - data.porto_center[0]) / data.data_std[0]
@@ -94,8 +106,8 @@ def main():
     # x_lastk_longitude = theano.printing.Print("x_lastk_longitude")(x_lastk_longitude)
 
     # Define the model
-    client_embed_table = LookupTable(length=config.n_clients+1, dim=config.dim_embed, name='client_lookup')
-    stand_embed_table = LookupTable(length=config.n_stands+1, dim=config.dim_embed, name='stand_lookup')
+    client_embed_table = LookupTable(length=data.n_clients+1, dim=config.dim_embed, name='client_lookup')
+    stand_embed_table = LookupTable(length=data.n_stands+1, dim=config.dim_embed, name='stand_lookup')
     mlp = MLP(activations=[Rectifier() for _ in config.dim_hidden] + [Identity()],
                        dims=[config.dim_input] + config.dim_hidden + [config.dim_output])
 
@@ -152,6 +164,7 @@ def main():
                 # Checkpoint('model.pkl', every_n_batches=100),
                 Dump('taxi_model', every_n_batches=1000),
                 LoadFromDump('taxi_model'),
+                FinishAfter(after_epoch=1)
                 ]
 
     main_loop = MainLoop(
@@ -163,13 +176,7 @@ def main():
     main_loop.profile.report()
 
     # Produce an output on the test data
-    '''
-    test = data.test_data
-    test = DataStream(test)
-    test = transformers.add_first_k(conifg.n_begin_end_pts, test)
-    test = transformers.add_last_k(config.n_begin_end_pts, test)
-    test = transformers.Select(test, ('trip_id', 'origin_stand', 'origin_call', 'first_k', 'last_k'))
-    test_stream = Batch(test, iteration_scheme=ConstantScheme(1000))
+    test_stream = setup_test_stream()
 
     outfile = open("test-output.csv", "w")
     outcsv = csv.writer(outfile)
@@ -177,9 +184,8 @@ def main():
     for out in apply_model.Apply(outputs=outputs, stream=test_stream, return_vars=['trip_id', 'outputs']):
         dest = out['outputs']
         for i, trip in enumerate(out['trip_id']):
-            outcsv.writerow([trip, repr(dest[i, 1]), repr(dest[i, 0])])
+            outcsv.writerow([trip, repr(dest[i, 0]), repr(dest[i, 1])])
     outfile.close()
-    '''
 
 
 if __name__ == "__main__":