From e1673538607a7c8d784013b21b753f0c05c4cc34 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=89tienne=20Simon?= <esimon@esimon.eu>
Date: Tue, 21 Jul 2015 18:26:43 -0400
Subject: Genericize RNNs

---
 config/rnn_1.py            |  2 +-
 config/rnn_lag_tgtcls_1.py | 49 ++++++++++++++++++++++++++++++++++++++++++++++
 config/rnn_tgtcls_1.py     | 37 ++++++++++++++++++++++++++++++++++
 3 files changed, 87 insertions(+), 1 deletion(-)
 create mode 100644 config/rnn_lag_tgtcls_1.py
 create mode 100644 config/rnn_tgtcls_1.py

(limited to 'config')

diff --git a/config/rnn_1.py b/config/rnn_1.py
index 5bc62d8..6e148c4 100644
--- a/config/rnn_1.py
+++ b/config/rnn_1.py
@@ -1,7 +1,7 @@
 from blocks.initialization import IsotropicGaussian, Constant
 
 import data
-from model.rnn import Model, Stream
+from model.rnn_direct import Model, Stream
 
 class EmbedderConfig(object):
     __slots__ = ('dim_embeddings', 'embed_weights_init')
diff --git a/config/rnn_lag_tgtcls_1.py b/config/rnn_lag_tgtcls_1.py
new file mode 100644
index 0000000..7a41b70
--- /dev/null
+++ b/config/rnn_lag_tgtcls_1.py
@@ -0,0 +1,49 @@
+import os
+import cPickle
+
+from blocks import roles
+from blocks.bricks import Rectifier
+from blocks.filter import VariableFilter
+from blocks.initialization import IsotropicGaussian, Constant
+
+import data
+from model.rnn_lag_tgtcls import Model, Stream
+
+class EmbedderConfig(object):
+    __slots__ = ('dim_embeddings', 'embed_weights_init')
+
+pre_embedder = EmbedderConfig()
+pre_embedder.embed_weights_init = IsotropicGaussian(0.001)
+pre_embedder.dim_embeddings = [ 
+    ('week_of_year', 52, 10),
+    ('day_of_week', 7, 10),
+    ('qhour_of_day', 24 * 4, 10),
+    ('day_type', 3, 10),
+    ('taxi_id', 448, 10),
+]
+
+post_embedder = EmbedderConfig()
+post_embedder.embed_weights_init = IsotropicGaussian(0.001)
+post_embedder.dim_embeddings = [ 
+    ('origin_call', data.origin_call_train_size, 10), 
+    ('origin_stand', data.stands_size, 10),
+]
+
+with open(os.path.join(data.path, 'arrival-clusters.pkl')) as f: tgtcls = cPickle.load(f)
+
+hidden_state_dim = 100 
+weights_init = IsotropicGaussian(0.01)
+biases_init = Constant(0.001)
+
+rec_to_out_dims = [200, 1000]
+in_to_rec_dims = [200]
+
+dropout = 0.5
+dropout_inputs = VariableFilter(bricks=[Rectifier], name='output')
+
+noise = 0.01
+noise_inputs = VariableFilter(roles=[roles.PARAMETER])
+
+batch_size = 10
+batch_sort_size = 10
+valid_set = 'cuts/test_times_0'
diff --git a/config/rnn_tgtcls_1.py b/config/rnn_tgtcls_1.py
new file mode 100644
index 0000000..3204559
--- /dev/null
+++ b/config/rnn_tgtcls_1.py
@@ -0,0 +1,37 @@
+import os
+import cPickle
+
+from blocks.initialization import IsotropicGaussian, Constant
+
+import data
+from model.rnn_tgtcls import Model, Stream
+
+class EmbedderConfig(object):
+    __slots__ = ('dim_embeddings', 'embed_weights_init')
+
+pre_embedder = EmbedderConfig()
+pre_embedder.embed_weights_init = IsotropicGaussian(0.001)
+pre_embedder.dim_embeddings = [ 
+    ('week_of_year', 52, 10),
+    ('day_of_week', 7, 10),
+    ('qhour_of_day', 24 * 4, 10),
+    ('day_type', 3, 10),
+    ('taxi_id', 448, 10),
+]
+
+post_embedder = EmbedderConfig()
+post_embedder.embed_weights_init = IsotropicGaussian(0.001)
+post_embedder.dim_embeddings = [ 
+    ('origin_call', data.origin_call_train_size, 10), 
+    ('origin_stand', data.stands_size, 10),
+]
+
+with open(os.path.join(data.path, 'arrival-clusters.pkl')) as f: tgtcls = cPickle.load(f)
+
+hidden_state_dim = 100 
+weights_init = IsotropicGaussian(0.01)
+biases_init = Constant(0.001)
+
+batch_size = 10
+batch_sort_size = 10
+valid_set = 'cuts/test_times_0'
-- 
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