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| author | Étienne Simon <esimon@esimon.eu> | 2015-05-05 23:03:13 -0400 |
|---|---|---|
| committer | Étienne Simon <esimon@esimon.eu> | 2015-05-05 23:03:13 -0400 |
| commit | 60aa0d3fdd42d7489cc69acbb54c59d7c249ea34 (patch) | |
| tree | 3ef37dab66250972cb226bff2ffb49f716a85915 | |
| parent | c29a0d3f22134a8d1f5d557b325f6779c5961546 (diff) | |
| download | taxi-60aa0d3fdd42d7489cc69acbb54c59d7c249ea34.tar.gz taxi-60aa0d3fdd42d7489cc69acbb54c59d7c249ea34.zip | |
Adapt Alexandre's model to the new interface
| -rw-r--r-- | config/dest_simple_mlp_tgtcls_1_cswdtx_alexandre.py | 8 | ||||
| -rw-r--r-- | model/dest_simple_mlp_tgtcls_alexandre.py | 8 |
2 files changed, 9 insertions, 7 deletions
diff --git a/config/dest_simple_mlp_tgtcls_1_cswdtx_alexandre.py b/config/dest_simple_mlp_tgtcls_1_cswdtx_alexandre.py index 91ad71c..5642f27 100644 --- a/config/dest_simple_mlp_tgtcls_1_cswdtx_alexandre.py +++ b/config/dest_simple_mlp_tgtcls_1_cswdtx_alexandre.py @@ -9,11 +9,11 @@ n_end_pts = 5 n_valid = 1000 -with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f) +with open("%s/arrival-clusters.pkl" % data.path) as f: tgtcls = cPickle.load(f) dim_embeddings = [ - ('origin_call', data.n_train_clients+1, 10), - ('origin_stand', data.n_stands+1, 10), + ('origin_call', data.origin_call_train_size, 10), + ('origin_stand', data.stands_size, 10), ('week_of_year', 52, 10), ('day_of_week', 7, 10), ('qhour_of_day', 24 * 4, 10), @@ -28,3 +28,5 @@ dim_output = tgtcls.shape[0] learning_rate = 0.01 momentum = 0.9 batch_size = 200 + +valid_set = 'cuts/test_times_0' diff --git a/model/dest_simple_mlp_tgtcls_alexandre.py b/model/dest_simple_mlp_tgtcls_alexandre.py index 87e20a3..825bf80 100644 --- a/model/dest_simple_mlp_tgtcls_alexandre.py +++ b/model/dest_simple_mlp_tgtcls_alexandre.py @@ -14,11 +14,11 @@ 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 = [] |