blob: 6cfe510c6a539d3982668eaa70f988f2f2c19a31 (
plain) (
tree)
|
|
from blocks.initialization import IsotropicGaussian, Constant
import data
from model.time_simple_mlp import Model, Stream
n_begin_end_pts = 5 # how many points we consider at the beginning and end of the known trajectory
n_valid = 1000
dim_embeddings = [
]
dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings)
dim_hidden = [200]
dim_output = 1
embed_weights_init = IsotropicGaussian(0.001)
mlp_weights_init = IsotropicGaussian(0.01)
mlp_biases_init = Constant(0.001)
exp_base = 1.5
learning_rate = 0.00001
momentum = 0.99
batch_size = 32
valid_set = 'cuts/test_times_0'
max_splits = 100
|
