from blocks.initialization import IsotropicGaussian, Constant
import data
from model.rnn 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),
]
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'
