Keras Transformer-XL

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Unofficial implementation of Transformer-XL.

Install

pip install keras-transformer-xl

Usage

Load Pretrained Weights

Several configuration files can be found at the info directory.

import os
from keras_transformer_xl import load_trained_model_from_checkpoint

checkpoint_path = 'foo/bar/sota/enwiki8'
model = load_trained_model_from_checkpoint(
    config_path=os.path.join(checkpoint_path, 'config.json'),
    checkpoint_path=os.path.join(checkpoint_path, 'model.ckpt')
)
model.summary()

About IO

The generated model has two inputs, and the second input is the lengths of memories.

You can use MemorySequence wrapper for training and prediction:

import keras
import numpy as np
from keras_transformer_xl import MemorySequence, build_transformer_xl


class DummySequence(keras.utils.Sequence):

    def __init__(self):
        pass

    def __len__(self):
        return 10

    def __getitem__(self, index):
        return np.ones((3, 5 * (index + 1))), np.ones((3, 5 * (index + 1), 3))


model = build_transformer_xl(
    units=4,
    embed_dim=4,
    hidden_dim=4,
    num_token=3,
    num_block=3,
    num_head=2,
    batch_size=3,
    memory_len=20,
    target_len=10,
)
seq = MemorySequence(
    model=model,
    sequence=DummySequence(),
    target_len=10,
)

model.predict(model, seq, verbose=True)

Use tf.keras

Add TF_KERAS=1 to environment variables to use tensorflow.python.keras.