/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_CORE_COMMON_RUNTIME_GPU_GPU_INIT_H_
#define TENSORFLOW_CORE_COMMON_RUNTIME_GPU_GPU_INIT_H_

#include <string>
#include "tensorflow/core/lib/core/status.h"

namespace stream_executor {
class Platform;
}  // namespace stream_executor

namespace tensorflow {

// Initializes the GPU platform and returns OK if the GPU
// platform could be initialized.
Status ValidateGPUMachineManager();

// Returns the GPU machine manager singleton, creating it and
// initializing the GPUs on the machine if needed the first time it is
// called.  Must only be called when there is a valid GPU environment
// in the process (e.g., ValidateGPUMachineManager() returns OK).
stream_executor::Platform* GPUMachineManager();

// Returns the string describing the name of the GPU platform in use.
// This value is "CUDA" by default, and
// "ROCM" when TF is built with `--config==rocm`
string GpuPlatformName();

}  // namespace tensorflow

#endif  // TENSORFLOW_CORE_COMMON_RUNTIME_GPU_GPU_INIT_H_
