API Documentation

Ensemble Graph Constructors

Ensemble(ops, schema[, label_columns])

Class that represents an entire ensemble consisting of multiple models that run sequentially in tritonserver initiated by an inference request.

Ensemble Operator Constructors

workflow.TransformWorkflow([workflow, ...])	This operator takes a workflow and turns it into a ensemble operator so that we can execute feature engineering during ensemble on tritonserver.
tensorflow.PredictTensorflow(model_or_path)	TensorFlow Model Prediction Operator.
fil.PredictForest(model, input_schema, *[, ...])	Operator for running inference on Forest models.
implicit.PredictImplicit(model[, ...])	Operator for running inference on Implicit models..
softmax_sampling.SoftmaxSampling(relevance_col)	Given inputs of ID and prediction, this operator will sort all inputs in descending order.
session_filter.FilterCandidates(filter_out)	This operator takes the input column and filters out elements of that column based on the supplied criteria.
unroll_features.UnrollFeatures(item_id_col, ...)	This operator takes a target column and joins the "unroll" columns to the target.

Conversion Functions for Triton Inference Server

convert_df_to_triton_input(schema, batch[, ...])	Convert a dataframe to a set of Triton inputs
convert_triton_output_to_df(columns, response)	Convert a Triton response to a dataframe