Features

• Add support for distributed training and distributed hyper-parameter tuning in the OSS build. See https://www.tensorflow.org/decision_forests/distributed_training
• Setting "subsample" is enough enable random subsampling (to need to also set "sampling_method=RANDOM").
• Add "min_vocab_frequency" argument in "FeatureUsage" to control the minimum frequency of categorical items.
• Add "override_global_imputation_value" argument in "FeatureUsage" to override the value used for global imputation of missing value by the global-imputation algorithm.
• The Tuner argument "use_predefined_hps" automatically configures the set of hyper-parameters to explore during automatic hyper-parameter tuning.
• Replaces the MEAN_MIN_DEPTH variable importance with INV_MEAN_MIN_DEPTH.
• Add option to forbid model inference with the slow inference engine.

Fix

• Automatic documentation generation for RandomForestModel and other classes.