message: update fct name to follow the standard.
diff: @@ -42,19 +42,19 @@ limitations under the License.
  namespace tensorflow {
  namespace {
  -bool useCudaMallocAllocator() {
  +bool UseCudaMallocAllocator() {
  const char* debug_allocator_str = std::getenv("TF_GPU_ALLOCATOR");
  return debug_allocator_str != nullptr &&
  std::strcmp(debug_allocator_str, "cuda_malloc") == 0;
  }
  -bool useCudaMemoryGuardAllocator() {
  +bool UseCudaMemoryGuardAllocator() {
  const char* debug_allocator_str = std::getenv("TF_GPU_ALLOCATOR");
  return debug_allocator_str != nullptr &&
  std::strcmp(debug_allocator_str, "memory_guard") == 0;
  }
  -bool useCudaMallocAsyncAllocator() {
  +bool UseCudaMallocAsyncAllocator() {
  const char* debug_allocator_str = std::getenv("TF_GPU_ALLOCATOR");
  return debug_allocator_str != nullptr &&
  std::strcmp(debug_allocator_str, "cuda_malloc_async") == 0;
  @@ -134,18 +134,18 @@ Allocator* GPUProcessState::GetGPUAllocator(const GPUOptions& options,
  // If true, checks for memory overwrites by writing
  // distinctive patterns on both ends of allocated memory.
  - if (useCudaMemoryGuardAllocator()) {
  + if (UseCudaMemoryGuardAllocator()) {
  LOG(INFO) << "Using memory guard allocator for GPU.";
  gpu_allocator = new GPUDebugAllocator(gpu_allocator, platform_gpu_id);
  gpu_allocator = new GPUNanResetAllocator(gpu_allocator, platform_gpu_id);
  - } else if (useCudaMallocAllocator()) {
  + } else if (UseCudaMallocAllocator()) {
  LOG(INFO) << "Using CUDA malloc allocator for GPU.";
  // If true, passes all allocation requests through to cudaMalloc
  // useful for doing memory debugging with tools like cuda-memcheck
  // **WARNING** probably will not work in a multi-gpu scenario
  gpu_allocator =
  new GPUcudaMallocAllocator(gpu_allocator, platform_gpu_id);
  - } else if (useCudaMallocAsyncAllocator()) {
  + } else if (UseCudaMallocAsyncAllocator()) {
  LOG(INFO) << "Using CUDA malloc Async allocator for GPU.";
  // If true, passes all allocation requests through to cudaMallocAsync
  // TODO: useful for doing memory debugging with tools like cuda-memcheck
  