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Release v1.7.0
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@mgqa34 mgqa34 released this 24 Nov 09:37
· 4160 commits to master since this release
v1.7.0
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Major Features and Improvements

FATE-ARCH

  • Support EggRoll 2.4.0
  • Support Spark-Local Computing Engine
  • Support Hive Storage
  • Support LocalFS Storage for Spark-Local Computing Engine
  • Optimizing the API interface for Storage session and table
  • Simplified the API interface for Session, remove backend and workmode parameters
  • Heterogeneous Engine Support: Federation between Spark-Local and Spark-Cluster
  • Computing Engine, Storage Engine, Federation Engine are set in conf/service_conf.yaml when FATE is deployed

FederatedML

  • Optimized Hetero-SecureBoost: with gradient packing、cipher compressing, and sparse point statistics optimization, 4x+ faster
  • Homo-SecureBoost supports memory-based histogram computation for more efficient tree building, 5x+ faster
  • Optimized RSA Intersect with CRT optimization, 3x+ faster
  • New two-party Hetero Logistic Regression Algorithm: mixed protocol of HE and MPC, without a trusted third party
  • Support data with match-id, separating match id and sample id
  • New DH Intersect based on PH Key-exchange protocol
  • Intersect support cardinality estimation
  • Intersect adds optionally preprocessing step
  • RSA and DH Intersect support cache
  • New Feature Imputation module: can apply arbitrary imputation method to each column
  • New Label Transform module: transform categorical label values
  • Homo-LR, Homo-SecureBoost, Homo-NN now can convert models into sklearn、lightgbm、torch & tf-keras framework
  • Hetero Feature Binning supports multi-class task, higher efficiency with label packing
  • Hetero Feature Selection support multi-class iv filter
  • Secure Information Retrieval supports multi-column retrieval
  • Major training algorithms support warm-start and checkpoint : Homo & Hetero LR, Homo & Hetero-SecureBoost, Homo & Hetero NN
  • Optimized Pailler addition operation, several times faster, Hetero-SecureBoost with Paillier speed up 2x+

Fate-Client

  • Pipeline supports uploading match id functionality
  • Pipeline supports homo model conversion
  • Pipeline supports model push to FATE-Serving
  • Pipeline supports running jobs with specified FATE version

FATE-Test

  • Integrate FederatedML unittest
  • Support for uploading image data
  • Big data generation using storage interface, optimized generation logic
  • Support for historical data comparison
  • cache_deps and model_loader_deps support
  • Run DSL Testsuite with specified FATE version
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