f84b3616c71d52b4f3cefebe629ba4808b59b8d8,baseline/tf/tagger/training/datasets.py,,fit_datasets,#Any#Any#Any#Any#,23

Before Change

    test_dataset = test_dataset.repeat(epochs + 1)
    test_dataset = test_dataset.prefetch(NUM_PREFETCH)

    iter = tf.data.Iterator.from_structure(train_dataset.output_types,
                                           train_dataset.output_shapes)

    features, y = iter.get_next()
    // Add features to the model params
    model_params.update(features)

After Change

    train_dataset = train_dataset.shuffle(buffer_size=SHUF_BUF_SZ)
    train_dataset = train_dataset.batch(batchsz, drop_remainder=False)
    train_dataset = train_dataset.repeat(epochs + 1)
    train_dataset = train_dataset.prefetch(NUM_PREFETCH)

    valid_dataset = tf.data.Dataset.from_tensor_slices(to_tensors(vs, lengths_key))
    valid_dataset = valid_dataset.batch(batchsz, drop_remainder=False)
    valid_dataset = valid_dataset.repeat(epochs + 1)
    valid_dataset = valid_dataset.prefetch(NUM_PREFETCH)

    test_dataset = tf.data.Dataset.from_tensor_slices(to_tensors(es, lengths_key))
    test_dataset = test_dataset.batch(test_batchsz, drop_remainder=False)
    test_dataset = test_dataset.repeat(epochs + 1)
    test_dataset = test_dataset.prefetch(NUM_PREFETCH)

    iter = tf.compat.v1.data.Iterator.from_structure(tf.compat.v1.data.get_output_types(train_dataset),
                                                     tf.compat.v1.data.get_output_shapes(train_dataset))

    features, y = iter.get_next()
    // Add features to the model params
    model_params.update(features)

Instances