@rbharath rbharath released this Mar 3, 2018 · 552 commits to master since this release

Assets 2

This major version release finishes consolidating the DeepChem codebase around our TensorGraph API for constructing complex models in DeepChem. We've made a variety of improvements to TensorGraph's saving/loading features and added a number of new tutorials improving our documentation of TensorGraph. We've also removed a number of older deprecated submodules and models in favor of the new, standardized TensorGraph implementations.

In addition, we've implemented a number of new deep models and algorithms, including DRAGONNs, Molecular Autoencoders, MIX+GANs, continuous space A3C, MCTS for RL, Mol2Vec and more. We've also continued improving our core graph convolutional implementations.

We've also made a variety of documentation, build, and website improvements and fixes.

Our thanks to our contributors for all the hard work!

  • TensorGraph Conversion and Upgrades
    • #925 Sequential API for Model Construction
    • #949 Cleanup of Examples plus bugfixes
    • #952 Using Queues for prediction
    • #954 GraphConvTensorGraph Classification with Multiple Tasks
    • #965 Can restore from any checkpoint
    • #966 Simplified names of TensorGraph graph conv models
    • #970 Added TensorGraph LSTM Layer
    • #972 Add Model Configuration params to GraphConvTensorGraph
    • #975 Swap examples to use new TensorGraph models
    • #976 Remove deprecated TensorFlow classes
    • #989 Remove tf_new_models old submodule
    • #992 Remove the deprecated old fully connected models
    • #1007 Add ability to change loss functions after reload
    • #1023 Add TensorGraph Cast layer
    • #1024 Can move saved TensorGraph models on disk
    • #1054 Implement IRV TensorGraph Model
    • #1082 Move tensorflow_models and autoencoder_models into contrib
    • #1083 Add one-shot code back into contrib
    • #1085 Saving and loading Weave models
    • #1086 Implementation of robust models in TensorGraph
    • #1090 Move dc.nn to contrib
  • Reinforcement Learning Upgrades
    • #931 Monte Carlo Tree Search for RL
    • #1022 A3C supporting continuous action spaces.
  • Graph Convolution Improvements:
    • #1033 Adding master atoms to graph convolutions
    • #1080 Adding chirality to Atom and Bond features
    • #1081 Pinning Graph Gather to CPU for TF Bug
    • #1105 Graph Normalization
  • MoleculeNet Improvements
    • #933 Run MoleculeNet on Jenkins
    • #958 Building multi-assay datasets from PubChem based on genes
    • #996 PCBA dataset generation based on a single gene
    • #1032 Simplify Tox21 loading
    • #1042 Update MoleculeNet to latest models
    • #1049 Fixes for MoleculeNet update
  • New models added to DeepChem
    • #939 Mol2Vec implementation added to contrib
    • Add DRAGONN models
      • #979 Adding DRAGONN example to contrib
      • #1003 Removing some commented out DRAGONN code
      • #1008 Adding DNA Simulation code
      • #1020 Implementing FASTALoader
    • #981 MIX+GAN implemented
    • #1026 Molecular Autoencoder Implementation in TensorGraph
  • dc.data improvements
    • #930 Complete Shuffle Disk Dataset
    • #1031 Bugfix for merging DiskDatasets
    • #1034 Enabling merging of NumpyDataset
    • #1091 Adding dataset.make_iterator to create tf.data.Iterator instances from Dataset objects
  • Improvements to featurization and data splits
    • #1005 Enable choice of featurizer to be searched as a hyperparameter
    • #1009 Add Maxmin splitter
  • DeepChem tutorial additions and improvements
    • #940 Update datasets for protein-ligand complex tutorial
    • #961 Fix BACE tutorial
    • #998 Fix GraphConv tutorial
    • #1051 New TensorBoard usage tutorial
    • #1104 New splitter tutorial
  • #1072 DeepChem Organizational Structure and Governance
  • Documentation improvements
    • #957 Bump to 1.3.1
    • #997 Docstring for dc.utils.load_from_disk
    • #1018 Add README link
    • #1050 Improve README
    • #1053 README fixes
    • #1067 Docs fix to keep numpy docstrings rendering
    • #1068 Update SAMPL example docstrings to read correctly
    • #1077 Fix README links
    • #1107 Better installation from source examples
    • #1117 Fixes to prevent test modules from being generated in docs
    • #1123 Convert some leftover GPL license tags to MIT
    • #1124 Version bump for 2.0.0
  • Build Improvements
    • #928 Bump conda, docker to 1.3.1 version
    • #1013 Add manifest to include data files
    • #1028 Install simdna from conda-forge
    • #1056 Turn off PyPi uploading to deal with bugs
    • #1059 TensorFlow 1.5 Upgrade
  • Website improvements
    • #932 Bump Website version
    • #1057 Number of website fixes
  • Bugfixes, Tests, and Miscellaneous Improvements
    • #934 Upgrade yapf version to 0.19
    • #945 Fix import bug
    • #948 Write values not tensors to TensorBoard
    • #964 Fix infinite loop caused by shards of size 0
    • #973 Fix featurizer name error
    • #982 Fix import errors from ICU package
    • #987 Speed up tests
    • #1001 Upgrade yapf version to 0.20
    • #1061 Fix gaussian process optimization bug
    • #1063 Install pbr package properly
    • #1088 Fix import bugs
    • #1113 Using logger instead of print