handler_startup.train {vetiver}

Model handler functions for API endpoint

Description

These are developer-facing functions, useful for supporting new model types. Each model supported by vetiver_model() uses two handler functions in vetiver_api():

• The handler_startup function executes when the API starts. Use this function for tasks like loading packages. A model can use the default method here, which is NULL (to do nothing at startup).

• The handler_predict function executes at each API call. Use this function for calling predict() and any other tasks that must be executed at each API call.

Usage

## S3 method for class 'train'
handler_startup(vetiver_model)

## S3 method for class 'train'
handler_predict(vetiver_model, ...)

## S3 method for class 'gam'
handler_startup(vetiver_model)

## S3 method for class 'gam'
handler_predict(vetiver_model, ...)

## S3 method for class 'glm'
handler_predict(vetiver_model, ...)

handler_startup(vetiver_model)

## Default S3 method:
handler_startup(vetiver_model)

handler_predict(vetiver_model, ...)

## Default S3 method:
handler_predict(vetiver_model, ...)

## S3 method for class 'keras.engine.training.Model'
handler_startup(vetiver_model)

## S3 method for class 'keras.engine.training.Model'
handler_predict(vetiver_model, ...)

## S3 method for class 'kproto'
handler_predict(vetiver_model, ...)

## S3 method for class 'lm'
handler_predict(vetiver_model, ...)

## S3 method for class 'luz_module_fitted'
handler_startup(vetiver_model)

## S3 method for class 'luz_module_fitted'
handler_predict(vetiver_model, ...)

## S3 method for class 'Learner'
handler_startup(vetiver_model)

## S3 method for class 'Learner'
handler_predict(vetiver_model, ...)

## S3 method for class 'ranger'
handler_startup(vetiver_model)

## S3 method for class 'ranger'
handler_predict(vetiver_model, ...)

## S3 method for class 'recipe'
handler_startup(vetiver_model)

## S3 method for class 'recipe'
handler_predict(vetiver_model, ...)

## S3 method for class 'model_stack'
handler_startup(vetiver_model)

## S3 method for class 'model_stack'
handler_predict(vetiver_model, ...)

## S3 method for class 'workflow'
handler_startup(vetiver_model)

## S3 method for class 'workflow'
handler_predict(vetiver_model, ...)

## S3 method for class 'xgb.Booster'
handler_startup(vetiver_model)

## S3 method for class 'xgb.Booster'
handler_predict(vetiver_model, ...)

Arguments

vetiver_model

A deployable vetiver_model() object

...

Other arguments passed to predict(), such as prediction type

Details

These are two generics that use the class of vetiver_model$model for dispatch.

Value

A handler_startup function should return invisibly, while a handler_predict function should return a function with the signature ⁠function(req)⁠. The request body (req$body) consists of the new data at prediction time; this function should return predictions either as a tibble or as a list coercable to a tibble via tibble::as_tibble().

Examples

cars_lm <- lm(mpg ~ ., data = mtcars)
v <- vetiver_model(cars_lm, "cars_linear")
handler_startup(v)
handler_predict(v)