blob: 293a0abbb9851fd829264cfd912e0c5f235ddb5c (
plain) (
tree)
|
|
import cPickle
import data
import model.simple_mlp_tgtcls as model
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
with open(data.DATA_PATH + "/arrival-clusters.pkl") as f: tgtcls = cPickle.load(f)
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]
learning_rate = 0.0001
momentum = 0.99
batch_size = 32
|