/*
All modification made by Intel Corporation: © 2016 Intel Corporation

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Copyright (c) 2014, 2015, The Regents of the University of California (Regents)
All rights reserved.

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Copyright (c) 2014, 2015, the respective contributors
All rights reserved.
For the list of contributors go to https://github.com/BVLC/caffe/blob/master/CONTRIBUTORS.md


Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

    * Redistributions of source code must retain the above copyright notice,
      this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
    * Neither the name of Intel Corporation nor the names of its contributors
      may be used to endorse or promote products derived from this software
      without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE
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*/

#ifndef CAFFE_UTIL_DEVICE_ALTERNATE_H_
#define CAFFE_UTIL_DEVICE_ALTERNATE_H_

#ifdef CPU_ONLY  // CPU-only Caffe.

#include <vector>

// Stub out GPU calls as unavailable.

#define NO_GPU LOG(FATAL) << "Cannot use GPU in CPU-only Caffe: check mode."

#define STUB_GPU(classname) \
template <typename Dtype> \
void classname<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom, \
    const vector<Blob<Dtype>*>& top) { NO_GPU; } \
template <typename Dtype> \
void classname<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top, \
    const vector<bool>& propagate_down, \
    const vector<Blob<Dtype>*>& bottom) { NO_GPU; } \

#define STUB_GPU_FORWARD(classname, funcname) \
template <typename Dtype> \
void classname<Dtype>::funcname##_##gpu(const vector<Blob<Dtype>*>& bottom, \
    const vector<Blob<Dtype>*>& top) { NO_GPU; } \

#define STUB_GPU_BACKWARD(classname, funcname) \
template <typename Dtype> \
void classname<Dtype>::funcname##_##gpu(const vector<Blob<Dtype>*>& top, \
    const vector<bool>& propagate_down, \
    const vector<Blob<Dtype>*>& bottom) { NO_GPU; } \

#else  // Normal GPU + CPU Caffe.

#include <cublas_v2.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <curand.h>
#include <driver_types.h>  // cuda driver types
#ifdef USE_CUDNN  // cuDNN acceleration library.
#include "caffe/util/cudnn.hpp"
#endif

//
// CUDA macros
//

// CUDA: various checks for different function calls.
#define CUDA_CHECK(condition) \
  /* Code block avoids redefinition of cudaError_t error */ \
  do { \
    cudaError_t error = condition; \
    CHECK_EQ(error, cudaSuccess) << " " << cudaGetErrorString(error); \
  } while (0)

#define CUBLAS_CHECK(condition) \
  do { \
    cublasStatus_t status = condition; \
    CHECK_EQ(status, CUBLAS_STATUS_SUCCESS) << " " \
      << caffe::cublasGetErrorString(status); \
  } while (0)

#define CURAND_CHECK(condition) \
  do { \
    curandStatus_t status = condition; \
    CHECK_EQ(status, CURAND_STATUS_SUCCESS) << " " \
      << caffe::curandGetErrorString(status); \
  } while (0)

// CUDA: grid stride looping
#define CUDA_KERNEL_LOOP(i, n) \
  for (int i = blockIdx.x * blockDim.x + threadIdx.x; \
       i < (n); \
       i += blockDim.x * gridDim.x)

// CUDA: check for error after kernel execution and exit loudly if there is one.
#define CUDA_POST_KERNEL_CHECK CUDA_CHECK(cudaPeekAtLastError())

namespace caffe {

// CUDA: library error reporting.
const char* cublasGetErrorString(cublasStatus_t error);
const char* curandGetErrorString(curandStatus_t error);

// CUDA: use 512 threads per block
const int CAFFE_CUDA_NUM_THREADS = 512;

// CUDA: number of blocks for threads.
inline int CAFFE_GET_BLOCKS(const int N) {
  return (N + CAFFE_CUDA_NUM_THREADS - 1) / CAFFE_CUDA_NUM_THREADS;
}

}  // namespace caffe

#endif  // CPU_ONLY

#endif  // CAFFE_UTIL_DEVICE_ALTERNATE_H_
