Automated rollback of change 153039058

Change: 153045639

tensorflow/core/common_runtime/gpu/gpu_device.h

@@ -108,7 +108,6 @@ class BaseGPUDevice : public LocalDevice {
   mutex trace_mu_;
   int gpu_id_ = -1;
   const bool sync_every_op_ = false;
-  bool force_gpu_compatible_ = false;
   const int32 max_streams_;
   std::unique_ptr<EventMgr> em_;
 

tensorflow/core/common_runtime/gpu/gpu_device_factory.cc

@@ -31,16 +31,12 @@ class GPUDevice : public BaseGPUDevice {
             Allocator* cpu_allocator)
       : BaseGPUDevice(options, name, memory_limit, locality, gpu_id,
                       physical_device_desc, gpu_allocator, cpu_allocator,
-                      false /* sync every op */, 1 /* max_streams */) {
-    if (options.config.has_gpu_options()) {
-      force_gpu_compatible_ = options.config.gpu_options.force_gpu_compatible;
-    }
-  }
+                      false /* sync every op */, 1 /* max_streams */) {}
 
   Allocator* GetAllocator(AllocatorAttributes attr) override {
     if (attr.on_host()) {
       ProcessState* ps = ProcessState::singleton();
-      if (attr.gpu_compatible() || force_gpu_compatible_) {
+      if (attr.gpu_compatible()) {
         return ps->GetCUDAHostAllocator(0);
       } else {
         return cpu_allocator_;
@@ -75,16 +71,12 @@ class GPUCompatibleCPUDevice : public ThreadPoolDevice {
   GPUCompatibleCPUDevice(const SessionOptions& options, const string& name,
                          Bytes memory_limit, const DeviceLocality& locality,
                          Allocator* allocator)
-      : ThreadPoolDevice(options, name, memory_limit, locality, allocator) {
-    if (options.config.has_gpu_options()) {
-      force_gpu_compatible_ = options.config.gpu_options.force_gpu_compatible;
-    }
-  }
+      : ThreadPoolDevice(options, name, memory_limit, locality, allocator) {}
   ~GPUCompatibleCPUDevice() override {}
 
   Allocator* GetAllocator(AllocatorAttributes attr) override {
     ProcessState* ps = ProcessState::singleton();
-    if (attr.gpu_compatible() || force_gpu_compatible_) {
+    if (attr.gpu_compatible()) {
       return ps->GetCUDAHostAllocator(0);
     } else {
       // Call the parent's implementation.

tensorflow/core/protobuf/config.proto

@@ -64,18 +64,6 @@ message GPUOptions {
   // PollEvents calls, when the queue is empty.  If value is not
   // set or set to 0, gets set to a non-zero default.
   int32 polling_inactive_delay_msecs = 7;
-
-  // Force all tensors to be gpu_compatible. On a GPU-enabled TensorFlow,
-  // enabling this option forces all CPU tensors to be allocated with Cuda
-  // pinned memory. Normally, TensorFlow will infer which tensors should be
-  // allocated as the pinned memory. But in case where the inference is
-  // incomplete, this option can significantly speed up the cross-device memory
-  // copy performance as long as it fits the memory.
-  // Note that this option is not something that should be
-  // enabled by default for unknown or very large models, since all Cuda pinned
-  // memory is unpageable, having too much pinned memory might negatively impact
-  // the overall host system performance.
-  bool force_gpu_compatible = 8;
 };
 
 // Options passed to the graph optimizer

tensorflow/tools/api/golden/tensorflow.-g-p-u-options.pbtxt

@@ -22,10 +22,6 @@ tf_class {
     name: "Extensions"
     mtype: "<type \'getset_descriptor\'>"
   }
-  member {
-    name: "FORCE_GPU_COMPATIBLE_FIELD_NUMBER"
-    mtype: "<type \'int\'>"
-  }
   member {
     name: "PER_PROCESS_GPU_MEMORY_FRACTION_FIELD_NUMBER"
     mtype: "<type \'int\'>"