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