Merge pull request #659 from rstudio/feature/tf-keras-default

switch to tf.keras as default implementation

Author: javierluraschi

NEWS.md

@@ -1,4 +1,9 @@
 
+## Development version
+
+- Use `tf.keras` as default implementation module.
+
+
 ## Keras 2.2.4 (CRAN)
 
 - Improve handling of `timeseries_generator()` in calls to `fit_generator()`

R/package.R

@@ -77,6 +77,7 @@ use_backend <- function(backend = c("tensorflow", "cntk", "theano", "plaidml"))
   } else {
     Sys.setenv(KERAS_BACKEND = match.arg(backend))
   }
+  if (backend != "tensorflow") use_implementation("keras")
 }
 
 
@@ -87,7 +88,7 @@ keras <- NULL
 
   # resolve the implementaiton module (might be keras proper or might be tensorflow)
   implementation_module <- resolve_implementation_module()
-  
+
   # if KERAS_PYTHON is defined then forward it to RETICULATE_PYTHON
   keras_python <- get_keras_python()
   if (!is.null(keras_python))
@@ -160,7 +161,7 @@ resolve_implementation_module <- function() {
   implementation_module
 }
 
-get_keras_implementation <- function(default = "keras") {
+get_keras_implementation <- function(default = "tensorflow") {
   get_keras_option("KERAS_IMPLEMENTATION", default = default)
 }
 

inst/python/kerastools/layer.py

@@ -1,17 +1,18 @@
 
 import os
 
-if (os.getenv('KERAS_IMPLEMENTATION', 'keras') == 'tensorflow'):
+if (os.getenv('KERAS_IMPLEMENTATION', 'tensorflow') == 'keras'):
+  from keras.engine.topology import Layer
+  def shape_filter(shape):
+    return shape
+else:
   from tensorflow.python.keras.engine import Layer
   def shape_filter(shape):
     if not isinstance(shape, list):
       return shape.as_list()
     else:
       return shape
-else:
-  from keras.engine.topology import Layer
-  def shape_filter(shape):
-    return shape
+  
 
 class RLayer(Layer):
 

inst/python/kerastools/model.py

@@ -2,15 +2,14 @@
 
 import os
 
-if (os.getenv('KERAS_IMPLEMENTATION', 'keras') == 'tensorflow'):
+if (os.getenv('KERAS_IMPLEMENTATION', 'tensorflow') == 'keras'):
+  from keras.engine import Model
+else:
   try:
     from tensorflow.python.keras.engine import Model
   except:
     from tensorflow.python.keras.engine.training import Model
-else:
-  from keras.engine import Model
- 
- 
+
 class RModel(Model):
 
   def __init__(self, name = None):

inst/python/kerastools/wrapper.py

@@ -1,17 +1,17 @@
 import os
 
-if (os.getenv('KERAS_IMPLEMENTATION', 'keras') == 'tensorflow'):
+if (os.getenv('KERAS_IMPLEMENTATION', 'tensorflow') == 'keras'):
+  from keras.layers import Wrapper
+  def shape_filter(shape): 
+    return shape
+else:
   from tensorflow.python.keras.layers import Wrapper
   def shape_filter(shape):
     if not isinstance(shape, list):
       return shape.as_list()
     else:
       return shape
-else:
-  from keras.layers import Wrapper
-  def shape_filter(shape):
-    return shape
-
+ 
 class RWrapper(Wrapper):
 
   def __init__(self, r_build, r_call, r_compute_output_shape, **kwargs):

tests/testthat/test-model-persistence.R

@@ -115,7 +115,7 @@ test_succeeds("model can be exported to TensorFlow", {
 
   export <- function() tensorflow::export_savedmodel(model, model_dir)
 
-  if (grepl("^tensorflow", Sys.getenv("KERAS_IMPLEMENTATION"))) {
+  if (!grepl("^keras", Sys.getenv("KERAS_IMPLEMENTATION"))) {
     expect_error(export())
   }
   else {