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author | Alex Auvolat <alex.auvolat@ens.fr> | 2015-07-27 12:59:39 -0400 |
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committer | Alex Auvolat <alex.auvolat@ens.fr> | 2015-07-27 12:59:39 -0400 |
commit | 0021c3fb99d1cd3f8792a8cf5c35548815536428 (patch) | |
tree | 9edb909def7652579a1b6a40ecb311a61b40455b /config | |
parent | 2a20bc827a8c1c9b6e74ef4e1234788207be45b8 (diff) | |
download | taxi-0021c3fb99d1cd3f8792a8cf5c35548815536428.tar.gz taxi-0021c3fb99d1cd3f8792a8cf5c35548815536428.zip |
Config files
Diffstat (limited to 'config')
-rw-r--r-- | config/bidirectional_tgtcls_1_momentum.py | 4 | ||||
-rw-r--r-- | config/bidirectional_tgtcls_1_momentum_maxlen.py | 39 | ||||
l--------- | config/bidirectional_tgtcls_1_notvt.py | 1 | ||||
-rw-r--r-- | config/memory_network_bidir_momentum.py | 8 |
4 files changed, 46 insertions, 6 deletions
diff --git a/config/bidirectional_tgtcls_1_momentum.py b/config/bidirectional_tgtcls_1_momentum.py index 65ad021..99b50d0 100644 --- a/config/bidirectional_tgtcls_1_momentum.py +++ b/config/bidirectional_tgtcls_1_momentum.py @@ -27,12 +27,12 @@ embed_weights_init = IsotropicGaussian(0.01) weights_init = IsotropicGaussian(0.1) biases_init = Constant(0.01) -batch_size = 300 +batch_size = 200 batch_sort_size = 20 max_splits = 100 # monitor_freq = 10000 # temporary, for finding good learning rate -step_rule= Momentum(learning_rate=0.01, momentum=0.9) +step_rule= Momentum(learning_rate=0.001, momentum=0.9) diff --git a/config/bidirectional_tgtcls_1_momentum_maxlen.py b/config/bidirectional_tgtcls_1_momentum_maxlen.py new file mode 100644 index 0000000..25e09a1 --- /dev/null +++ b/config/bidirectional_tgtcls_1_momentum_maxlen.py @@ -0,0 +1,39 @@ +import os +import cPickle + +from blocks.algorithms import Momentum +from blocks.initialization import IsotropicGaussian, Constant + +import data +from model.bidirectional_tgtcls import Model, Stream + + +with open(os.path.join(data.path, 'arrival-clusters.pkl')) as f: tgtcls = cPickle.load(f) + +dim_embeddings = [ + ('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), + ('taxi_id', data.taxi_id_size, 10), +] + +hidden_state_dim = 100 + +dim_hidden = [500, 500] + +embed_weights_init = IsotropicGaussian(0.01) +weights_init = IsotropicGaussian(0.1) +biases_init = Constant(0.01) + +batch_size = 400 +batch_sort_size = 20 + +max_splits = 100 +train_max_len = 500 + +# monitor_freq = 10000 # temporary, for finding good learning rate + +step_rule= Momentum(learning_rate=0.001, momentum=0.9) + diff --git a/config/bidirectional_tgtcls_1_notvt.py b/config/bidirectional_tgtcls_1_notvt.py new file mode 120000 index 0000000..546c8e9 --- /dev/null +++ b/config/bidirectional_tgtcls_1_notvt.py @@ -0,0 +1 @@ +bidirectional_tgtcls_1.py
\ No newline at end of file diff --git a/config/memory_network_bidir_momentum.py b/config/memory_network_bidir_momentum.py index 3d90494..504fdee 100644 --- a/config/memory_network_bidir_momentum.py +++ b/config/memory_network_bidir_momentum.py @@ -45,14 +45,14 @@ representation_activation = Tanh normalize_representation = True -batch_size = 32 +batch_size = 64 batch_sort_size = 20 max_splits = 100 num_cuts = 1000 -train_candidate_size = 300 -valid_candidate_size = 300 -test_candidate_size = 300 +train_candidate_size = 100 +valid_candidate_size = 100 +test_candidate_size = 100 step_rule = Momentum(learning_rate=0.01, momentum=0.9) |