move qnn helper function into utility files

This commit is contained in:
hongruichen 2024-06-19 18:16:11 +08:00
parent 37a1585ead
commit ff0359d6f4
3 changed files with 205 additions and 199 deletions

View file

@ -183,21 +183,6 @@ struct ggml_backend_qnn_buffer_type_context {
// QNN backend internal helper functions
//
// =================================================================================================
// TODO: only support GGML_OP_ADD/GGML_OP_MUL/GGML_OP_MUL_MAT
static const char * qnn_opname_from_ggmlop(enum ggml_op ggmlop) {
switch (ggmlop) {
case GGML_OP_ADD:
return QNN_OP_ELEMENT_WISE_ADD;
case GGML_OP_MUL:
return QNN_OP_ELEMENT_WISE_MULTIPLY;
case GGML_OP_MUL_MAT:
return QNN_OP_MAT_MUL;
default:
break;
}
return nullptr;
}
static bool qnn_is_valid_params(ggml_backend_qnn_context * ctx, const ggml_tensor * src0,
const ggml_tensor * src1, ggml_tensor * dst) {
if ((nullptr == ctx) || (nullptr == src0) || (nullptr == src1) || (nullptr == dst)) {
@ -270,181 +255,6 @@ public:
};
#endif
#define VALIDATE(value, status) \
do { \
status = value; \
if (status != QNN_SUCCESS) { \
QNN_LOG_WARN("%s expected QNN_SUCCESS\n", #value); \
return status; \
} \
} while (0)
#define QNN_TENSOR_GET_ID(tensor) get_qnn_tensorid(tensor)
#define QNN_TENSOR_GET_NAME(tensor) get_qnn_tensorname(tensor)
#define QNN_TENSOR_GET_TYPE(tensor) get_qnn_tensortype(tensor)
#define QNN_TENSOR_GET_DATA_FORMAT(tensor) get_qnn_tensor_dataformat(tensor)
#define QNN_TENSOR_GET_DATA_TYPE(tensor) get_qnn_tensor_datatype(tensor)
#define QNN_TENSOR_GET_QUANT_PARAMS(tensor) get_qnn_tensor_quantparams(tensor)
#define QNN_TENSOR_GET_RANK(tensor) get_qnn_tensor_rank(tensor)
#define QNN_TENSOR_GET_DIMENSIONS(tensor) get_qnn_tensor_dimensions(tensor)
#define QNN_TENSOR_GET_MEM_TYPE(tensor) get_qnn_tensor_memtype(tensor)
#define QNN_TENSOR_SET_ID(tensor, value) set_qnn_tensor_id(tensor, value)
#define QNN_TENSOR_SET_NAME(tensor, value) set_qnn_tensor_name(tensor, value)
#define QNN_TENSOR_SET_TYPE(tensor, value) set_qnn_tensor_type(tensor, value)
#define QNN_TENSOR_SET_DATA_FORMAT(tensor, value) set_qnn_tensor_dataformat(tensor, value)
#define QNN_TENSOR_SET_DATA_TYPE(tensor, value) set_qnn_tensor_datatype(tensor, value)
#define QNN_TENSOR_SET_QUANT_PARAMS(tensor, value) set_qnn_tensor_quantparams(tensor, value)
#define QNN_TENSOR_SET_RANK(tensor, value) set_qnn_tensor_rank(tensor, value)
#define QNN_TENSOR_SET_DIMENSIONS(tensor, value) set_qnn_tensor_dimensions(tensor, value)
#define QNN_TENSOR_SET_MEM_TYPE(tensor, value) set_qnn_tensor_memtype(tensor, value)
#define QNN_TENSOR_SET_CLIENT_BUF(tensor, value) set_qnn_tensor_clientbuf(tensor, value)
#define QNN_TENSOR_SET_MEM_HANDLE(tensor, value) set_qnn_tensor_memhandle(tensor, value)
#define VALIDATE_TENSOR_VERSION(tensor, err) VALIDATE(validate_tensor_version(tensor), err)
static inline int validate_tensor_version(Qnn_Tensor_t tensor) {
if (tensor.version != QNN_TENSOR_VERSION_1) {
QNN_LOG_WARN(
"validate_tensor_version() tensor %s, got unsupported version %d\n",
tensor.v1.name, tensor.version);
return 1;
}
return 0;
}
static inline uint32_t get_qnn_tensorid(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.id;
}
return 0u;
}
static inline const char * get_qnn_tensorname(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.name;
}
return nullptr;
}
static inline Qnn_TensorType_t get_qnn_tensortype(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.type;
}
return QNN_TENSOR_TYPE_UNDEFINED;
}
static inline Qnn_TensorDataFormat_t
get_qnn_tensor_dataformat(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dataFormat;
}
return QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER;
}
static inline Qnn_DataType_t
get_qnn_tensor_datatype(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dataType;
}
return QNN_DATATYPE_UNDEFINED;
}
static inline Qnn_QuantizeParams_t
get_qnn_tensor_quantparams(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.quantizeParams;
}
return QNN_QUANTIZE_PARAMS_INIT;
}
static inline uint32_t get_qnn_tensor_rank(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.rank;
}
return 0u;
}
static inline uint32_t * get_qnn_tensor_dimensions(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dimensions;
}
return nullptr;
}
static inline Qnn_TensorMemType_t get_qnn_tensor_memtype(const Qnn_Tensor_t & tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.memType;
}
return QNN_TENSORMEMTYPE_UNDEFINED;
}
static inline void set_qnn_tensor_id(Qnn_Tensor_t & tensor, uint32_t id) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.id = id;
}
}
static inline void set_qnn_tensor_name(Qnn_Tensor_t & tensor, const char * name) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.name = name;
}
}
static inline void set_qnn_tensor_type(Qnn_Tensor_t & tensor, Qnn_TensorType_t type) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.type = type;
}
}
static inline void set_qnn_tensor_dataformat(Qnn_Tensor_t & tensor, Qnn_TensorDataFormat_t format) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dataFormat = format;
}
}
static inline void set_qnn_tensor_datatype(Qnn_Tensor_t & tensor, Qnn_DataType_t dataType) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dataType = dataType;
}
}
static inline void set_qnn_tensor_quantparams(Qnn_Tensor_t & tensor, Qnn_QuantizeParams_t params) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.quantizeParams = params;
}
}
static inline void set_qnn_tensor_rank(Qnn_Tensor_t & tensor, uint32_t rank) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.rank = rank;
}
}
static inline void set_qnn_tensor_dimensions(Qnn_Tensor_t & tensor, uint32_t * dims) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dimensions = dims;
}
}
static inline void set_qnn_tensor_memtype(Qnn_Tensor_t & tensor, Qnn_TensorMemType_t mem_type) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.memType = mem_type;
}
}
static inline void set_qnn_tensor_clientbuf(Qnn_Tensor_t & tensor, Qnn_ClientBuffer_t client_buf) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.clientBuf = client_buf;
}
}
static inline void set_qnn_tensor_memhandle(Qnn_Tensor_t & tensor, Qnn_MemHandle_t handle) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.memHandle = handle;
}
}
static size_t memscpy(void * dst, size_t dst_size, const void * src, size_t copy_size) {
if (!dst || !src || !dst_size || !copy_size) return 0;
@ -613,7 +423,7 @@ static void ggml_qnn_add(ggml_backend_qnn_context * ctx, const ggml_tensor * src
CHECK_PARAMS(ctx, src0, src1, dst);
instance = ctx->instance;
QNN_INTERFACE_VER_TYPE qnn_raw_interface = ctx->raw_interface;
auto qnn_raw_interface = ctx->raw_interface;
qnn_perf perf("ggml_qnn_add");
perf.start();
@ -807,7 +617,7 @@ static void ggml_qnn_mul_mat(ggml_backend_qnn_context * ctx,
CHECK_PARAMS(ctx, src0, src1, dst);
instance = ctx->instance;
QNN_INTERFACE_VER_TYPE qnn_raw_interface = ctx->raw_interface;
auto qnn_raw_interface = ctx->raw_interface;
qnn_perf perf("ggml_qnn_mul_mat");
perf.start();

View file

@ -12,13 +12,13 @@
#include "qnn.hpp"
struct ggml_backend_qnn_context {
int device;
int threads;
char name[GGML_MAX_NAME];
char lib[GGML_MAX_NAME];
int device;
int threads;
char name[GGML_MAX_NAME];
char lib[GGML_MAX_NAME];
qnn::qnn_instance* instance;
struct ggml_backend* backend;
QNN_INTERFACE_VER_TYPE raw_interface;
ggml_backend* backend;
QNN_INTERFACE_VER_TYPE raw_interface;
QNN_SYSTEM_INTERFACE_VER_TYPE raw_system_interface;
qnn::qcom_socinfo socinfo;
qnn::qcom_socinfo socinfo;
};

View file

@ -109,4 +109,200 @@ namespace qnn {
return ggml_nbytes(tensor);
}
// =================================================================================================
//
// QNN backend internal helper functions
//
// =================================================================================================
// TODO: only support GGML_OP_ADD/GGML_OP_MUL/GGML_OP_MUL_MAT
const char* opname_from_ggmlop(enum ggml_op ggmlop) {
switch (ggmlop) {
case GGML_OP_ADD:
return QNN_OP_ELEMENT_WISE_ADD;
case GGML_OP_MUL:
return QNN_OP_ELEMENT_WISE_MULTIPLY;
case GGML_OP_MUL_MAT:
return QNN_OP_MAT_MUL;
default:
break;
}
return nullptr;
}
inline int validate_tensor_version(Qnn_Tensor_t tensor) {
if (tensor.version != QNN_TENSOR_VERSION_1) {
QNN_LOG_WARN(
"validate_tensor_version() tensor %s, got unsupported version %d\n",
tensor.v1.name, tensor.version);
return 1;
}
return 0;
}
inline uint32_t get_qnn_tensorid(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.id;
}
return 0u;
}
inline const char* get_qnn_tensorname(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.name;
}
return nullptr;
}
inline Qnn_TensorType_t get_qnn_tensortype(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.type;
}
return QNN_TENSOR_TYPE_UNDEFINED;
}
inline Qnn_TensorDataFormat_t
get_qnn_tensor_dataformat(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dataFormat;
}
return QNN_TENSOR_DATA_FORMAT_FLAT_BUFFER;
}
inline Qnn_DataType_t
get_qnn_tensor_datatype(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dataType;
}
return QNN_DATATYPE_UNDEFINED;
}
inline Qnn_QuantizeParams_t
get_qnn_tensor_quantparams(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.quantizeParams;
}
return QNN_QUANTIZE_PARAMS_INIT;
}
inline uint32_t get_qnn_tensor_rank(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.rank;
}
return 0u;
}
inline uint32_t* get_qnn_tensor_dimensions(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.dimensions;
}
return nullptr;
}
inline Qnn_TensorMemType_t get_qnn_tensor_memtype(const Qnn_Tensor_t& tensor) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
return tensor.v1.memType;
}
return QNN_TENSORMEMTYPE_UNDEFINED;
}
inline void set_qnn_tensor_id(Qnn_Tensor_t& tensor, uint32_t id) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.id = id;
}
}
inline void set_qnn_tensor_name(Qnn_Tensor_t& tensor, const char* name) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.name = name;
}
}
inline void set_qnn_tensor_type(Qnn_Tensor_t& tensor, Qnn_TensorType_t type) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.type = type;
}
}
inline void set_qnn_tensor_dataformat(Qnn_Tensor_t& tensor, Qnn_TensorDataFormat_t format) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dataFormat = format;
}
}
inline void set_qnn_tensor_datatype(Qnn_Tensor_t& tensor, Qnn_DataType_t dataType) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dataType = dataType;
}
}
inline void set_qnn_tensor_quantparams(Qnn_Tensor_t& tensor, Qnn_QuantizeParams_t params) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.quantizeParams = params;
}
}
inline void set_qnn_tensor_rank(Qnn_Tensor_t& tensor, uint32_t rank) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.rank = rank;
}
}
inline void set_qnn_tensor_dimensions(Qnn_Tensor_t& tensor, uint32_t* dims) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.dimensions = dims;
}
}
inline void set_qnn_tensor_memtype(Qnn_Tensor_t& tensor, Qnn_TensorMemType_t mem_type) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.memType = mem_type;
}
}
inline void set_qnn_tensor_clientbuf(Qnn_Tensor_t& tensor, Qnn_ClientBuffer_t client_buf) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.clientBuf = client_buf;
}
}
inline void set_qnn_tensor_memhandle(Qnn_Tensor_t& tensor, Qnn_MemHandle_t handle) {
if (tensor.version == QNN_TENSOR_VERSION_1) {
tensor.v1.memHandle = handle;
}
}
}
#define VALIDATE(value, status) \
do { \
status = value; \
if (status != QNN_SUCCESS) { \
QNN_LOG_WARN("%s expected QNN_SUCCESS\n", #value); \
return status; \
} \
} while (0)
#define QNN_TENSOR_GET_ID(tensor) qnn::get_qnn_tensorid(tensor)
#define QNN_TENSOR_GET_NAME(tensor) qnn::get_qnn_tensorname(tensor)
#define QNN_TENSOR_GET_TYPE(tensor) qnn::get_qnn_tensortype(tensor)
#define QNN_TENSOR_GET_DATA_FORMAT(tensor) qnn::get_qnn_tensor_dataformat(tensor)
#define QNN_TENSOR_GET_DATA_TYPE(tensor) qnn::get_qnn_tensor_datatype(tensor)
#define QNN_TENSOR_GET_QUANT_PARAMS(tensor) qnn::get_qnn_tensor_quantparams(tensor)
#define QNN_TENSOR_GET_RANK(tensor) qnn::get_qnn_tensor_rank(tensor)
#define QNN_TENSOR_GET_DIMENSIONS(tensor) qnn::get_qnn_tensor_dimensions(tensor)
#define QNN_TENSOR_GET_MEM_TYPE(tensor) qnn::get_qnn_tensor_memtype(tensor)
#define QNN_TENSOR_SET_ID(tensor, value) qnn::set_qnn_tensor_id(tensor, value)
#define QNN_TENSOR_SET_NAME(tensor, value) qnn::set_qnn_tensor_name(tensor, value)
#define QNN_TENSOR_SET_TYPE(tensor, value) qnn::set_qnn_tensor_type(tensor, value)
#define QNN_TENSOR_SET_DATA_FORMAT(tensor, value) qnn::set_qnn_tensor_dataformat(tensor, value)
#define QNN_TENSOR_SET_DATA_TYPE(tensor, value) qnn::set_qnn_tensor_datatype(tensor, value)
#define QNN_TENSOR_SET_QUANT_PARAMS(tensor, value) qnn::set_qnn_tensor_quantparams(tensor, value)
#define QNN_TENSOR_SET_RANK(tensor, value) qnn::set_qnn_tensor_rank(tensor, value)
#define QNN_TENSOR_SET_DIMENSIONS(tensor, value) qnn::set_qnn_tensor_dimensions(tensor, value)
#define QNN_TENSOR_SET_MEM_TYPE(tensor, value) qnn::set_qnn_tensor_memtype(tensor, value)
#define QNN_TENSOR_SET_CLIENT_BUF(tensor, value) qnn::set_qnn_tensor_clientbuf(tensor, value)
#define QNN_TENSOR_SET_MEM_HANDLE(tensor, value) qnn::set_qnn_tensor_memhandle(tensor, value)
#define VALIDATE_TENSOR_VERSION(tensor, err) VALIDATE(qnn::validate_tensor_version(tensor), err)