Release notes#

Upgrading#

To upgrade Material to the latest version, use pip:

pip install --upgrade kashgari-tf

To inspect the currently installed version, use the following command:

pip show kashgari-tf

Current Release#

1.0.0 - 2019.10.18#

Unfortunately, we have to change the package name for clarity and consistency. Here is the new naming sytle.

Backend pypi version desc
TensorFlow 2.x kashgari 2.x.x coming soon
TensorFlow 1.14+ kashgari 1.x.x
Keras kashgari 0.x.x legacy version

Here is how the existing versions changes

Supported Backend Kashgari Versions Kahgsari-tf Version
TensorFlow 2.x kashgari 2.x.x -
TensorFlow 1.14+ kashgari 1.0.1 -
TensorFlow 1.14+ kashgari 1.0.0 0.5.5
TensorFlow 1.14+ - 0.5.4
TensorFlow 1.14+ - 0.5.3
TensorFlow 1.14+ - 0.5.2
TensorFlow 1.14+ - 0.5.1
Keras (legacy) kashgari 0.2.6 -
Keras (legacy) kashgari 0.2.5 -
Keras (legacy) kashgari 0.x.x -

0.5.4 - 2019.09.30#

  • ✨ Add shuffle parameter to fit function (#249)
  • ✨ Improved type hinting for loaded model (#248)
  • 🐛 Fix loading models with CRF layers (#244, #228)
  • 🐛 Fix the configuration changes during embedding save/load (#224)
  • 🐛 Fix stacked embedding save/load (#224)
  • 🐛 Fix evaluate function where the list has int instead of str ([#222])
  • 💥 Renaming model.pre_processor to model.processor
  • 🚨 Removing TensorFlow and numpy warnings
  • 📝 Add docs how to specify which CPU or GPU
  • 📝 Add docs how to compile model with custom optimizer

0.5.3 - 2019.08.11#

  • 🐛 Fixing CuDNN Error (#198)

0.5.2 - 2019.08.10#

  • 💥 Add CuDNN Cell config, disable auto CuDNN cell. (#182, #198)

0.5.1 - 2019.07.15#

  • 📝 Rewrite documents with mkdocs
  • 📝 Add Chinese documents
  • ✨ Add predict_top_k_class for classification model to get predict probabilities (#146)
  • 🚸 Add label2idx, token2idx properties to Embeddings and Models
  • 🚸 Add tokenizer property for BERT Embedding. (#136)
  • 🚸 Add predict_kwargs for models predict() function
  • ⚡️ Change multi-label classification's default loss function to binary_crossentropy (#151)

0.5.0 - 2019.07.11#

🎉🎉 tf.keras version 🎉🎉

  • 🎉 Rewrite Kashgari using tf.keras (#77)
  • 🎉 Rewrite Documents
  • ✨ Add TPU support
  • ✨ Add TF-Serving support.
  • ✨ Add advance customization support, like multi-input model
  • 🐎 Performance optimization

Legacy Version Changelog#

0.2.6 - 2019.07.12#

  • 📝 Add tf.keras version info
  • 🐛 Fixing lstm issue in labeling model (#125)

0.2.4 - 2019.06.06#

  • Add BERT output feature layer fine-tune support. Discussion: (#103)
  • Add BERT output feature layer number selection, default 4 according to BERT paper
  • Fix BERT embedding token index offset issue (#104

0.2.1 - 2019.03.05#

  • fix missing sequence_labeling_tokenize_add_bos_eos config

0.2.0#

  • multi-label classification for all classification models
  • support cuDNN cell for sequence labeling
  • add option for output BOS and EOS in sequence labeling result, fix #31

0.1.9#

  • add AVCNNModel, KMaxCNNModel, RCNNModel, AVRNNModel, DropoutBGRUModel, DropoutAVRNNModel model to classification task.
  • fix several small bugs

0.1.8#

  • fix BERT Embedding model's to_json function, issue #19

0.1.7#

  • remove class candidates filter to fix #16
  • overwrite init function in CustomEmbedding
  • add parameter check to custom_embedding layer
  • add keras-bert version to setup.py file

0.1.6#

  • add output_dict, debug_info params to text_classification model
  • add output_dict, debug_info and chunk_joinerparams to text_classification model
  • fix possible crash at data_generator

0.1.5#

  • fix sequence labeling evaluate result output
  • refactor model save and load function

0.1.4#

  • fix classification model evaluate result output
  • change test settings