model.middle_dropout_keep_prob: 1 - middle_dropout, model.input_dropout_keep_prob: 1 - input_dropout, model.l2_penalty: l2, model.drop_penalty: regularize_drop_penalty } lstm_feed.update(char_embedding_feed) run_list = [train_op, model.loss] _, loss = sess.run(run_list, feed_dict=lstm_feed) return loss epochs = 6000 train_batches_weak = dp.get_batches('cdr_train_weak', batch_size, random=False) train_batches_cdr = dp.get_batches('cdr_train', batch_size, random=False) train_batches_bc = dp.get_batches('bc_train', batch_size, random=False) dev_batches_cdr = dp.get_batches('cdr_dev', batch_size, random=False) dev_batches_bc = dp.get_batches('bc_dev', batch_size, random=False) test_batches_cdr = dp.get_batches('cdr_test', batch_size, random=False) test_batches_bc = dp.get_batches('bc_test', batch_size, random=False) max_f1 = 0 epoch_last_saved = 0 last_saved = 'N/A' for i in range(epochs): batches_weak = dp.get_batches('cdr_train_weak', batch_size) batches_cdr = dp.get_batches('cdr_train', batch_size)
model.middle_dropout_keep_prob: 1 - middle_dropout, model.input_dropout_keep_prob: 1 - input_dropout, model.l2_penalty: l2, model.drop_penalty: regularize_drop_penalty } lstm_feed.update(char_embedding_feed) run_list = [train_op, model.loss] _, loss = sess.run(run_list, feed_dict=lstm_feed) return loss epochs = 6000 train_batches_A = dp.get_batches('A_train', batch_size, random=False) train_batches_B = dp.get_batches('B_train', batch_size, random=False) dev_batches = dp.get_batches('dev', batch_size, random=False) test_batches = dp.get_batches('test', batch_size, random=False) max_f1 = 0 epoch_last_saved = 0 last_saved = 'N/A' for i in range(epochs): batches_A = dp.get_batches('A_train', batch_size) batches_B = dp.get_batches('B_train', batch_size) l = min(len(batches_A), len(batches_B)) for j in range(l):