Keras XLNet
Unofficial implementation of XLNet.
Install
pip install keras-xlnet
Usage
Load Pretrained Checkpoints
import os
from keras_xlnet import load_trained_model_from_checkpoint
checkpoint_path = '.../xlnet_cased_L-24_H-1024_A-16'
model = load_trained_model_from_checkpoint(
config_path=os.path.join(checkpoint_path, 'xlnet_config.json'),
checkpoint_path=os.path.join(checkpoint_path, 'xlnet_model.ckpt'),
batch_size=16,
memory_len=512,
target_len=128,
in_train_phase=False,
)
model.summary()
Arguments batch_size, memory_len and target_len are maximum sizes used for initialization of memories. The model used for training a language model is returned if in_train_phase is True, otherwise a model used for fine-tuning will be returned.
About I/O
in_train_phase is False
3 inputs:
- IDs of tokens, with shape
(batch_size, target_len). - IDs of segments, with shape
(batch_size, target_len). - Length of memories, with shape
(batch_size, 1).
1 output:
- The feature for each token, with shape
(batch_size, target_len, units).
in_train_phase is True
4 inputs:
- IDs of tokens, with shape
(batch_size, target_len). - IDs of segments, with shape
(batch_size, target_len). - Length of memories, with shape
(batch_size, 1). - Masks of tokens, with shape
(batch_size, target_len).
1 output:
- The probability of each token in each position, with shape
(batch_size, target_len, num_token).
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