Features

• Add advanced option predict_single_probability_for_binary_classification to generate prediction tensors of shape [batch_size, 2] for binary classification model.
• Add support for weighted training.
• Add support for permutation variable importance in the GBT learner with the compute_permutation_variable_importance parameter.
• Support for tf.int8 and tf.int16 values.
• Support for distributed gradient boosted trees learning. Currently, the TF ParameterServerStrategy distribution strategy is only available in monolithic TF-DF builds. The Yggdrasil Decision Forest GRPC distribute strategy can be used instead.
• Support for training from dataset stored on disk in CSV and RecordIO format (instead of creating a tensorflow dataset). This option is currently more efficient for distributed training (until the ParameterServerStrategy support per-worker datasets).
• Add max_vocab_count argument to the model constructor. The existing max_vocab_count argument in FeatureUsage objects take precedence.

Fixes

• Missing filtering of unique values in the categorical-set training feature accumulator. Was responsible for a small (e.g. ~0.5% on SST2 dataset) drop of accuracy compared to the C++ API.
• Fix broken support for max_vocab_count in a FeatureUsage with type CATEGORICAL_SET.