Predict using a SavedModel

Runs a prediction over a saved model file, local service or cloudml model.

predict_savedmodel(instances, model, ...)

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, CloudML name or graph object. A local path can be exported using export_savedmodel(), a REST URL can be created using serve_savedmodel(), a CloudML model can be deployed usin cloudml::cloudml_deploy() and a graph object loaded using load_savedmodel(). Notice that predicting over a CloudML model requires a version parameter to identify the model. A type parameter can be specified to explicitly choose the type model performing the prediction. Valid values are cloudml, export, webapi and graph.
...	See predict_savedmodel.export_prediction(), predict_savedmodel.graph_prediction(), predict_savedmodel.webapi_prediction() and predict_savedmodel.cloudml_prediction() for additional options. #' @section Implementations: predict_savedmodel.export_prediction() predict_savedmodel.graph_prediction() predict_savedmodel.webapi_prediction()] predict_savedmodel.cloudml_prediction()

See also

export_savedmodel(), serve_savedmodel(), load_savedmodel()

Examples

# NOT RUN {
# perform prediction based on an existing model
tfdeploy::predict_savedmodel(
  list(rep(9, 784)),
  system.file("models/tensorflow-mnist", package = "tfdeploy")
)
# }