diff options
Diffstat (limited to 'config')
-rw-r--r-- | config/simple_mlp_2_cs.py | 25 | ||||
-rw-r--r-- | config/simple_mlp_2_noembed.py (renamed from config/simple_mlp_0.py) | 7 | ||||
-rw-r--r-- | config/simple_mlp_tgtcls_0_cs.py (renamed from config/simple_mlp_tgtcls_0.py) | 8 | ||||
-rw-r--r-- | config/simple_mlp_tgtcls_1_cs.py (renamed from config/simple_mlp_tgtcls_1.py) | 8 |
4 files changed, 42 insertions, 6 deletions
diff --git a/config/simple_mlp_2_cs.py b/config/simple_mlp_2_cs.py new file mode 100644 index 0000000..692d325 --- /dev/null +++ b/config/simple_mlp_2_cs.py @@ -0,0 +1,25 @@ +import model.simple_mlp as model + +import data + +n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday +n_dom = 31 +n_hour = 24 + +n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory +n_end_pts = 5 + +n_valid = 1000 + +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10) +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) +dim_hidden = [200, 100] +dim_output = 2 + +learning_rate = 0.0001 +momentum = 0.99 +batch_size = 32 diff --git a/config/simple_mlp_0.py b/config/simple_mlp_2_noembed.py index 61ddbfd..bc300e7 100644 --- a/config/simple_mlp_0.py +++ b/config/simple_mlp_2_noembed.py @@ -1,5 +1,7 @@ import model.simple_mlp as model +import data + n_dow = 7 # number of division for dayofweek/dayofmonth/hourofday n_dom = 31 n_hour = 24 @@ -9,8 +11,9 @@ n_end_pts = 5 n_valid = 1000 -dim_embed = 10 -dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed +dim_embeddings = [] # do not use embeddings + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) dim_hidden = [200, 100] dim_output = 2 diff --git a/config/simple_mlp_tgtcls_0.py b/config/simple_mlp_tgtcls_0_cs.py index 91770c2..b174517 100644 --- a/config/simple_mlp_tgtcls_0.py +++ b/config/simple_mlp_tgtcls_0_cs.py @@ -15,8 +15,12 @@ n_valid = 1000 with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f) -dim_embed = 10 -dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10) +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) dim_hidden = [] dim_output = tgtcls.shape[0] diff --git a/config/simple_mlp_tgtcls_1.py b/config/simple_mlp_tgtcls_1_cs.py index 8d6c37b..6bf82e1 100644 --- a/config/simple_mlp_tgtcls_1.py +++ b/config/simple_mlp_tgtcls_1_cs.py @@ -15,8 +15,12 @@ n_valid = 1000 with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f) -dim_embed = 10 -dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed +dim_embeddings = [ + ('origin_call', data.n_train_clients+1, 10), + ('origin_stand', data.n_stands+1, 10) +] + +dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) dim_hidden = [500] dim_output = tgtcls.shape[0] |