mlflow_save_model: Save Model for MLflow

Description Usage Arguments

View source: R/model.R

Description

Saves model in MLflow format that can later be used for prediction and serving. This method is generic to allow package authors to save custom model types.

Usage

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## S3 method for class 'crate'
mlflow_save_model(model, path, model_spec = list(), ...)

mlflow_save_model(model, path, model_spec = list(), ...)

## S3 method for class 'H2OModel'
mlflow_save_model(model, path, model_spec = list(), conda_env = NULL, ...)

## S3 method for class 'keras.engine.training.Model'
mlflow_save_model(model, path, model_spec = list(), conda_env = NULL, ...)

## S3 method for class 'ml_pipeline_model'
mlflow_save_model(
  model,
  path,
  model_spec = list(),
  conda_env = NULL,
  sample_input = NULL,
  ...
)

## S3 method for class 'xgb.Booster'
mlflow_save_model(model, path, model_spec = list(), conda_env = NULL, ...)

Arguments

model

The model that will perform a prediction.

path

Destination path where this MLflow compatible model will be saved.

model_spec

MLflow model config this model flavor is being added to.

...

Optional additional arguments.

conda_env

Path to Conda dependencies file.

sample_input

Sample Spark DataFrame input that the model can evaluate. This is required by MLeap for data schema inference.


mlflow documentation built on Sept. 6, 2021, 9:06 a.m.