pytorch/caffe2/python/dlpack.h

/*!
 *  Copyright (c) 2017 by Contributors
 * \file dlpack.h
 * \brief The common header of DLPack.
 */
#ifndef DLPACK_DLPACK_H_
#define DLPACK_DLPACK_H_

#ifdef __cplusplus
#define DLPACK_EXTERN_C extern "C"
#else
#define DLPACK_EXTERN_C
#endif

/*! \brief The current version of dlpack */
#define DLPACK_VERSION 60

/*! \brief DLPACK_DLL prefix for windows */
#ifdef _WIN32
#ifdef DLPACK_EXPORTS
#define DLPACK_DLL __declspec(dllexport)
#else
#define DLPACK_DLL __declspec(dllimport)
#endif
#else
#define DLPACK_DLL
#endif

#include <stddef.h>
#include <stdint.h>

#ifdef __cplusplus
extern "C" {
#endif
/*!
 * \brief The device type in DLDevice.
 */
typedef enum {
  /*! \brief CPU device */
  kDLCPU = 1,
  /*! \brief CUDA GPU device */
  kDLCUDA = 2,
  /*!
   * \brief Pinned CUDA CPU memory by cudaMallocHost
   */
  kDLCUDAHost = 3,
  /*! \brief OpenCL devices. */
  kDLOpenCL = 4,
  /*! \brief Vulkan buffer for next generation graphics. */
  kDLVulkan = 7,
  /*! \brief Metal for Apple GPU. */
  kDLMetal = 8,
  /*! \brief Verilog simulator buffer */
  kDLVPI = 9,
  /*! \brief ROCm GPUs for AMD GPUs */
  kDLROCM = 10,
  /*!
   * \brief Pinned ROCm CPU memory allocated by hipMallocHost
   */
  kDLROCMHost = 11,
  /*!
   * \brief Reserved extension device type,
   * used for quickly test extension device
   * The semantics can differ depending on the implementation.
   */
  kDLExtDev = 12,
  /*!
   * \brief CUDA managed/unified memory allocated by cudaMallocManaged
   */
  kDLCUDAManaged = 13,
} DLDeviceType;

/*!
 * \brief A Device for Tensor and operator.
 */
typedef struct {
  /*! \brief The device type used in the device. */
  DLDeviceType device_type;
  /*!
   * \brief The device index.
   * For vanilla CPU memory, pinned memory, or managed memory, this is set to 0.
   */
  int device_id;
} DLDevice;

/*!
 * \brief The type code options DLDataType.
 */
typedef enum {
  /*! \brief signed integer */
  kDLInt = 0U,
  /*! \brief unsigned integer */
  kDLUInt = 1U,
  /*! \brief IEEE floating point */
  kDLFloat = 2U,
  /*!
   * \brief Opaque handle type, reserved for testing purposes.
   * Frameworks need to agree on the handle data type for the exchange to be
   * well-defined.
   */
  kDLOpaqueHandle = 3U,
  /*! \brief bfloat16 */
  kDLBfloat = 4U,
  /*!
   * \brief complex number
   * (C/C++/Python layout: compact struct per complex number)
   */
  kDLComplex = 5U,
} DLDataTypeCode;

/*!
 * \brief The data type the tensor can hold.
 *
 *  Examples
 *   - float: type_code = 2, bits = 32, lanes=1
 *   - float4(vectorized 4 float): type_code = 2, bits = 32, lanes=4
 *   - int8: type_code = 0, bits = 8, lanes=1
 *   - std::complex<float>: type_code = 5, bits = 64, lanes = 1
 */
typedef struct {
  /*!
   * \brief Type code of base types.
   * We keep it uint8_t instead of DLDataTypeCode for minimal memory
   * footprint, but the value should be one of DLDataTypeCode enum values.
   * */
  uint8_t code;
  /*!
   * \brief Number of bits, common choices are 8, 16, 32.
   */
  uint8_t bits;
  /*! \brief Number of lanes in the type, used for vector types. */
  uint16_t lanes;
} DLDataType;

/*!
 * \brief Plain C Tensor object, does not manage memory.
 */
typedef struct {
  /*!
   * \brief The opaque data pointer points to the allocated data. This will be
   * CUDA device pointer or cl_mem handle in OpenCL. This pointer is always
   * aligned to 256 bytes as in CUDA.
   *
   * For given DLTensor, the size of memory required to store the contents of
   * data is calculated as follows:
   *
   * \code{.c}
   * static inline size_t GetDataSize(const DLTensor* t) {
   *   size_t size = 1;
   *   for (tvm_index_t i = 0; i < t->ndim; ++i) {
   *     size *= t->shape[i];
   *   }
   *   size *= (t->dtype.bits * t->dtype.lanes + 7) / 8;
   *   return size;
   * }
   * \endcode
   */
  void* data;
  /*! \brief The device of the tensor */
  DLDevice device;
  /*! \brief Number of dimensions */
  int ndim;
  /*! \brief The data type of the pointer*/
  DLDataType dtype;
  /*! \brief The shape of the tensor */
  int64_t* shape;
  /*!
   * \brief strides of the tensor (in number of elements, not bytes)
   *  can be NULL, indicating tensor is compact and row-majored.
   */
  int64_t* strides;
  /*! \brief The offset in bytes to the beginning pointer to data */
  uint64_t byte_offset;
} DLTensor;

/*!
 * \brief C Tensor object, manage memory of DLTensor. This data structure is
 *  intended to facilitate the borrowing of DLTensor by another framework. It is
 *  not meant to transfer the tensor. When the borrowing framework doesn't need
 *  the tensor, it should call the deleter to notify the host that the resource
 *  is no longer needed.
 */
typedef struct DLManagedTensor {
  /*! \brief DLTensor which is being memory managed */
  DLTensor dl_tensor;
  /*! \brief the context of the original host framework of DLManagedTensor in
   *   which DLManagedTensor is used in the framework. It can also be NULL.
   */
  void* manager_ctx;
  /*! \brief Destructor signature void (*)(void*) - this should be called
   *   to destruct manager_ctx which holds the DLManagedTensor. It can be NULL
   *   if there is no way for the caller to provide a reasonable destructor.
   *   The destructors deletes the argument self as well.
   */
  void (*deleter)(struct DLManagedTensor* self);
} DLManagedTensor;
#ifdef __cplusplus
} // DLPACK_EXTERN_C
#endif
#endif // DLPACK_DLPACK_H_