def load_network():
"""
Loads the network from the default file and returns it.
"""
file = open(senna_dump)
words, type_features = load_features(file)
word_dict = WordDictionary(None, wordlist=words, variant='senna')
tables = [type_features]
# PADDING, allcaps, hascap, initcap, nocaps
caps, caps_features = load_features(file)
tables.append(caps_features)
suff, suffix_features = load_features(file)
tables.append(suffix_features)
hidden_weights = load_weights(file) # (hidden_size, input_size)
hidden_bias = load_bias(file)
output_weights = load_weights(file) # (output_size, hidden_size)
output_bias = load_bias(file)
transition0 = load_bias(file)
transitions = load_weights(file).T
transitions = np.vstack((transitions, transition0))
word_window_size = 5
input_size = hidden_weights.shape[1]
hidden_size = hidden_weights.shape[0]
output_size = output_bias.shape[0]
nn = Network(word_window_size, input_size, hidden_size, output_size,
hidden_weights, hidden_bias, output_weights, output_bias)
nn.feature_tables = tables
nn.transitions = transitions
return nn, word_dict, suff
