diff options
| -rw-r--r-- | config/model_0.py | 2 | ||||
| -rw-r--r-- | data.py | 5 | ||||
| -rw-r--r-- | model.py | 6 |
3 files changed, 7 insertions, 6 deletions
diff --git a/config/model_0.py b/config/model_0.py index 736ef30..f26a99c 100644 --- a/config/model_0.py +++ b/config/model_0.py @@ -9,7 +9,7 @@ n_valid = 1000 dim_embed = 10 dim_input = n_begin_end_pts * 2 * 2 + dim_embed + dim_embed -dim_hidden = [200] +dim_hidden = [100] dim_output = 2 learning_rate = 0.002 @@ -2,6 +2,7 @@ import ast, csv import socket import fuel import numpy +import h5py from enum import Enum from fuel.datasets import Dataset from fuel.streams import DataStream @@ -28,7 +29,7 @@ dataset_size = 1710670 def make_client_ids(): f = h5py.File(H5DATA_PATH, "r") - l = f['uniq_origin_call'] + l = f['unique_origin_call'] r = {} for i in range(l.shape[0]): r[l[i]] = i @@ -37,7 +38,7 @@ def make_client_ids(): client_ids = make_client_ids() def get_client_id(n): - if n in client_ids: + if n in client_ids and client_ids[n] <= n_train_clients: return client_ids[n] else: return 0 @@ -46,7 +46,7 @@ if __name__ == "__main__": def setup_stream(): # Load the training and test data - train = H5PYDataset(H5DATA_PATH, + train = H5PYDataset(data.H5DATA_PATH, which_set='train', subset=slice(0, data.dataset_size - config.n_valid), load_in_memory=True) @@ -59,7 +59,7 @@ def setup_stream(): 'destination_latitude', 'destination_longitude')) train_stream = Batch(train, iteration_scheme=ConstantScheme(config.batch_size)) - valid = H5PYDataset(H5DATA_PATH, + valid = H5PYDataset(data.H5DATA_PATH, which_set='train', subset=slice(data.dataset_size - config.n_valid, data.dataset_size), load_in_memory=True) @@ -164,7 +164,7 @@ def main(): # Checkpoint('model.pkl', every_n_batches=100), Dump('taxi_model', every_n_batches=1000), LoadFromDump('taxi_model'), - FinishAfter(after_epoch=1) + FinishAfter(after_epoch=5) ] main_loop = MainLoop( |