Python utils.TextLoader方法代碼示例

本文整理匯總了Python中utils.TextLoader方法的典型用法代碼示例。如果您正苦於以下問題：Python utils.TextLoader方法的具體用法？Python utils.TextLoader怎麽用？Python utils.TextLoader使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類utils的用法示例。

在下文中一共展示了utils.TextLoader方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: setUp

# 需要導入模塊: import utils [as 別名]
# 或者: from utils import TextLoader [as 別名]
def setUp(self):
        self.data_loader = TextLoader("tests/test_data", batch_size=2, seq_length=5)

開發者ID:hunkim，項目名稱:word-rnn-tensorflow，代碼行數:4，代碼來源:test_train.py

示例2: train

# 需要導入模塊: import utils [as 別名]
# 或者: from utils import TextLoader [as 別名]
def train(args):
    data_loader = TextLoader(args.data_dir, args.batch_size, args.seq_length)
    args.vocab_size = data_loader.vocab_size

    with open(os.path.join(args.save_dir, 'config.pkl'), 'wb') as f:
        cPickle.dump(args, f)
    with open(os.path.join(args.save_dir, 'chars_vocab.pkl'), 'wb') as f:
        cPickle.dump((data_loader.chars, data_loader.vocab), f)

    model = Model(args)

    with tf.Session() as sess:
        tf.initialize_all_variables().run()
        saver = tf.train.Saver(tf.all_variables())
        for e in range(args.num_epochs):
            sess.run(tf.assign(model.lr, args.learning_rate * (args.decay_rate ** e)))
            data_loader.reset_batch_pointer()
            state = model.initial_state.eval()
            for b in range(data_loader.num_batches):
                start = time.time()
                x, y = data_loader.next_batch()
                feed = {model.input_data: x, model.targets: y, model.initial_state: state}
                train_loss, state, _ = sess.run([model.cost, model.final_state, model.train_op], feed)
                end = time.time()
                print("{}/{} (epoch {}), train_loss = {:.3f}, time/batch = {:.3f}" \
                    .format(e * data_loader.num_batches + b,
                            args.num_epochs * data_loader.num_batches,
                            e, train_loss, end - start))
                if (e * data_loader.num_batches + b) % args.save_every == 0:
                    checkpoint_path = os.path.join(args.save_dir, 'model.ckpt')
                    saver.save(sess, checkpoint_path, global_step = e * data_loader.num_batches + b)
                    print("model saved to {}".format(checkpoint_path))

開發者ID:DeepLearningProjects，項目名稱:poem-bot，代碼行數:34，代碼來源:train.py

示例3: train

# 需要導入模塊: import utils [as 別名]
# 或者: from utils import TextLoader [as 別名]
def train(args):
    data_loader = TextLoader(args.data_dir, args.batch_size, args.seq_length)
    args.vocab_size = data_loader.vocab_size

    with open(os.path.join(args.save_dir, 'config.pkl'), 'wb') as f:
        pickle.dump(args, f)
    with open(os.path.join(args.save_dir, 'chars_vocab.pkl'), 'wb') as f:
        pickle.dump((data_loader.chars, data_loader.vocab), f)

    model = Model(args)

    with tf.Session() as sess:
        tf.global_variables_initializer().run()
        saver = tf.train.Saver(tf.global_variables())
        train_loss_iterations = {'iteration': [], 'epoch': [], 'train_loss': [], 'val_loss': []}

        for e in range(args.num_epochs):
            sess.run(tf.assign(model.lr, args.learning_rate * (args.decay_rate ** e)))
            data_loader.reset_batch_pointer()
            state = sess.run(model.initial_state)
            for b in range(data_loader.num_batches):
                start = time.time()
                x, y = data_loader.next_batch()
                feed = {model.input_data: x, model.targets: y, model.initial_state: state}
                train_loss, state, _ = sess.run([model.cost, model.final_state, model.train_op], feed)
                end = time.time()
                batch_idx = e * data_loader.num_batches + b
                print("{}/{} (epoch {}), train_loss = {:.3f}, time/batch = {:.3f}" \
                      .format(batch_idx,
                              args.num_epochs * data_loader.num_batches,
                              e, train_loss, end - start))
                train_loss_iterations['iteration'].append(batch_idx)
                train_loss_iterations['epoch'].append(e)
                train_loss_iterations['train_loss'].append(train_loss)

                if batch_idx % args.save_every == 0:

                    # evaluate
                    state_val = sess.run(model.initial_state)
                    avg_val_loss = 0
                    for x_val, y_val in data_loader.val_batches:
                        feed_val = {model.input_data: x_val, model.targets: y_val, model.initial_state: state_val}
                        val_loss, state_val, _ = sess.run([model.cost, model.final_state, model.train_op], feed_val)
                        avg_val_loss += val_loss / len(list(data_loader.val_batches))
                    print('val_loss: {:.3f}'.format(avg_val_loss))
                    train_loss_iterations['val_loss'].append(avg_val_loss)

                    checkpoint_path = os.path.join(args.save_dir, 'model.ckpt')
                    saver.save(sess, checkpoint_path, global_step=e * data_loader.num_batches + b)
                    print("model saved to {}".format(checkpoint_path))
                else:
                    train_loss_iterations['val_loss'].append(None)

            pd.DataFrame(data=train_loss_iterations,
                         columns=train_loss_iterations.keys()).to_csv(os.path.join(args.save_dir, 'log.csv'))

開發者ID:philipperemy，項目名稱:tensorflow-grid-lstm，代碼行數:57，代碼來源:train.py

注：本文中的utils.TextLoader方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。