import model.dest_simple_mlp as model

import data

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 = []   # 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

learning_rate = 0.0001
momentum = 0.99
batch_size = 32

valid_set = 'cuts/test_times_0'