tfdeploy (version 0.6.1)

predict_savedmodel.graph_prediction: Predict using a Loaded SavedModel

Description

Performs a prediction using a SavedModel model already loaded using load_savedmodel().

Usage

# S3 method for graph_prediction
predict_savedmodel(instances, model, sess,
  signature_name = "serving_default", ...)

Arguments

instances

A list of prediction instances to be passed as input tensors to the service. Even for single predictions, a list with one entry is expected.

model

The model as a local path, a REST url or graph object.

A local path can be exported using export_savedmodel(), a REST URL can be created using serve_savedmodel() and a graph object loaded using load_savedmodel().

A type parameter can be specified to explicitly choose the type model performing the prediction. Valid values are export, webapi and graph.

sess

The active TensorFlow session.

signature_name

The named entry point to use in the model for prediction.

...

See predict_savedmodel.export_prediction(), predict_savedmodel.graph_prediction(), predict_savedmodel.webapi_prediction() for additional options.

#' @section Implementations:

• predict_savedmodel.export_prediction()

• predict_savedmodel.graph_prediction()

• predict_savedmodel.webapi_prediction()]