commit c51da68e1dbe80029b0ef93b86cf6fde4447aaa4
author Xiao Yu <fishx@google.com> Fri Jul 10 18:42:31 2020 -0700
committer TensorFlower Gardener <gardener@tensorflow.org> Fri Jul 10 18:45:49 2020 -0700
tree b2c751fb32a11338f5390a2a73f2afcac3baa736
parent 484fc676b33d38fd8b3eb8d93c16b21b7eecf256

Pluggable device/op_handler support in c_api_tfrt. And it starts to reuse device name (e.g. /device:CPU:0) borrowed from TensorFlow. It also allows creating different op handler for different GPU devices.

PiperOrigin-RevId: 320713554
Change-Id: Id554249713fe7571e29e8f2f36fc0986ee44e9ec

tensorflow/c/eager/c_api.cc

diff --git a/tensorflow/c/eager/c_api.cc b/tensorflow/c/eager/c_api.cc
index 70acd71..6804247 100644
--- a/tensorflow/c/eager/c_api.cc
+++ b/tensorflow/c/eager/c_api.cc
@@ -725,13 +725,7 @@
 TFE_Context* TFE_NewContext(const TFE_ContextOptions* opts, TF_Status* status) {
   if (opts->use_tfrt) {
 #ifdef PLATFORM_GOOGLE
-    tfrt::SmallVector<std::string, 4> op_handler_chains;
-    tfrt::SmallVector<tensorflow::DeviceAttributes, 4> device_attributes;
-    status->status = tfrt::ListOpHandlerChains(
-        opts->session_options.options, &op_handler_chains, &device_attributes);
-    if (!status->status.ok()) return nullptr;
-    return tensorflow::wrap(new tfrt::ContextInterface(
-        op_handler_chains, device_attributes, opts->async));
+    return tensorflow::wrap(new tfrt::ContextInterface(opts->async));
 #else
     status->status = tensorflow::errors::Unimplemented("TFRT is not supported");
     return nullptr;