add functions for serializing keras models to R 'raw' objects

anuj2054 · Jul 31, 2017 · dec2cb5 · dec2cb5
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Showing 19 changed files with 363 additions and 18 deletions.
diff --git a/NAMESPACE b/NAMESPACE
@@ -218,6 +218,7 @@ export(reset_states)
 export(save_model_hdf5)
 export(save_model_weights_hdf5)
 export(sequences_to_matrix)
+export(serialize_model)
 export(set_weights)
 export(skipgrams)
 export(tensorboard)
@@ -233,6 +234,7 @@ export(tf_config)
 export(time_distributed)
 export(to_categorical)
 export(train_on_batch)
+export(unserialize_model)
 export(use_condaenv)
 export(use_python)
 export(use_virtualenv)

diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,9 @@
 
 # keras 2.0.6 (unreleased)
 
+- Added `serialize_model()` and `unserialize_model()` functions for saving 
+  Keras models as 'raw' R objects.
+
 
 # keras 2.0.5
 

diff --git a/R/model-persistence.R b/R/model-persistence.R
@@ -18,9 +18,12 @@
 #' This allows you to save the entirety of the state of a model
 #' in a single file.
 #' 
-#' Saved models can be reinstantiated via `load_model()`. The model returned by
-#' `load_model()` is a compiled model ready to be used (unless the saved model
+#' Saved models can be reinstantiated via `load_model_hdf5()`. The model returned by
+#' `load_model_hdf5()` is a compiled model ready to be used (unless the saved model
 #' was never compiled in the first place or `compile = FALSE` is specified.
+#'
+#' @note The [serialize_model()] function enables saving Keras models to
+#' R objects that can be persisted across R sessions.
 #' 
 #' @family model persistence
 #' 
@@ -170,5 +173,53 @@ model_from_yaml <- function(yaml, custom_objects = NULL) {
   keras$models$model_from_yaml(yaml, custom_objects)
 }
 
+#' Serialize a model to an R object
+#'
+#' Model objects are external references to Keras objects which cannot be saved
+#' and restored across R sessions. The `serialize_model()` and
+#' `unserialize_model()` functions provide facilities to convert Keras models to
+#' R objects for persistence within R data files.
+#'
+#' @note The [save_model_hdf5()] function enables saving Keras models to
+#' external hdf5 files.
+#'
+#' @inheritParams save_model_hdf5
+#' @param model Keras model or R "raw" object containing serialized Keras model.
+#'
+#' @return `serialize_model()` returns an R "raw" object containing an hdf5
+#'   version of the Keras model. `unserialize_model()` returns a Keras model.
+#'
+#' @family model persistence
+#'
+#' @export
+serialize_model <- function(model, include_optimizer = TRUE) {
+
+  if (!inherits(model, "keras.engine.training.Model"))
+    stop("You must pass a Keras model object to serialize_model")
+
+  # write hdf5 file to temp file
+  tmp <- tempfile(pattern = "keras_model", fileext = ".h5")  
+  on.exit(unlink(tmp), add = TRUE)
+  save_model_hdf5(model, tmp, include_optimizer = include_optimizer)
+
+  # read it back intoa  raw vector
+  readBin(tmp, what = "raw", n = file.size(tmp))
+}
+
+#' @rdname serialize_model
+#' @export
+unserialize_model <- function(model, custom_objects = NULL, compile = TRUE) {
+
+  # write raw hdf5 bytes to temp file 
+  tmp <- tempfile(pattern = "keras_model", fileext = ".h5")  
+  on.exit(unlink(tmp), add = TRUE)
+  writeBin(model, tmp)
+
+  # read in from hdf5
+  load_model_hdf5(tmp, custom_objects = custom_objects, compile = compile)
+}
+
+
+
 
 
diff --git a/docs/articles/index.html b/docs/articles/index.html
diff --git a/docs/reference/get_weights.html b/docs/reference/get_weights.html
diff --git a/docs/reference/index.html b/docs/reference/index.html
diff --git a/docs/reference/model_to_json.html b/docs/reference/model_to_json.html
diff --git a/docs/reference/model_to_yaml.html b/docs/reference/model_to_yaml.html
diff --git a/docs/reference/save_model_hdf5.html b/docs/reference/save_model_hdf5.html
diff --git a/docs/reference/save_model_weights_hdf5.html b/docs/reference/save_model_weights_hdf5.html