vbatts/llama.cpp
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add cpu backend as cross reference

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hongruichen 2024-07-15 10:50:33 +08:00
parent 4410fd6563
commit cd5a7331f7
1 changed files with 25 additions and 14 deletions
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39
tests/ggml-qnn/ggml-qnn-ut.cpp
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@ -244,7 +244,7 @@ static uint32_t get_tensor_rank(const ggml_tensor *tensor) {
static uint32_t get_tensor_data_size(const ggml_tensor *tensor) {
size_t data_size = ggml_row_size(tensor->type, tensor->ne[0]);
size_t n_dims = get_tensor_rank(tensor);
for (int i = 1; i < n_dims; i++) {
for (size_t i = 1; i < n_dims; i++) {
data_size *= tensor->ne[i];
}
@ -377,7 +377,8 @@ static constexpr const ggml_op_binary_t kBinaryOps[] = {
static_assert(kBinaryOps[GGML_OP_MUL_MAT] == ggml_mul_mat, "ggml_mul_mat at wrong index, check kBinaryOps");
static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
static void qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type, ggml_type qtype,
std::vector<uint8_t> &results) {
int64_t n_begin_time = 0LL;
int64_t n_end_time = 0LL;
int64_t n_duration = 0LL;
@ -393,11 +394,6 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
ggml_backend_t backend = nullptr;
ggml_backend_buffer_t buffer = nullptr;
ggml_type qtype = GGML_TYPE_I8;
qtype = GGML_TYPE_F16;
qtype = GGML_TYPE_Q8_0;
qtype = GGML_TYPE_F32;
std::vector<uint8_t> work_buffer;
QNN_LOG_DEBUG("enter qnn_ggml_op\n");
QNN_LOG_DEBUG("ggml op:%d(%s)\n", n_ggml_op_type, ggml_op_name((enum ggml_op)n_ggml_op_type));
@ -416,14 +412,14 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
backend = ggml_backend_qnn_init(n_backend_type, "/data/local/tmp/");
if (nullptr == backend) {
QNN_LOG_ERROR("create qnn backend %d(%s) failed\n", n_backend_type, get_qnn_backend_name(n_backend_type));
return 1;
return;
}
}
ctx = ggml_init(params);
if (!ctx) {
QNN_LOG_ERROR("%s: ggml_init() failed\n");
return 2;
return;
}
QNN_LOG_DEBUG("creating new tensors\n");
@ -455,7 +451,7 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
QNN_LOG_WARN("ggml op %d(%s) not supported", n_ggml_op_type, ggml_op_name((enum ggml_op)n_ggml_op_type));
ggml_free(ctx);
ggml_backend_free(backend);
return 3;
return;
}
ggml_set_output(dst);
@ -466,7 +462,7 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
QNN_LOG_ERROR("%s: failed to allocate backend buffer\n", __func__);
ggml_free(ctx);
ggml_backend_free(backend);
return 4;
return;
}
}
#endif
@ -484,6 +480,8 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
TENSOR_DUMP(src0);
TENSOR_DUMP(src1);
TENSOR_DUMP(dst);
results.resize(ggml_nbytes(dst));
memcpy(results.data(), ggml_get_data(dst), ggml_nbytes(dst));
} else {
QNN_LOG_DEBUG("%15s: type = %i (%5s) ne = %5" PRIi64 " x %5" PRIi64 " x %5" PRIi64
", nb = (%5zi, %5zi, %5zi)\n",
@ -507,7 +505,6 @@ static int qnn_op_ut(int num_threads, int n_backend_type, int n_ggml_op_type) {
n_duration = (n_end_time - n_begin_time) / 1000;
QNN_LOG_DEBUG("duration of ut GGML_OP_%s using QNN backend %s: %lld milliseconds\n",
ggml_op_name((enum ggml_op)n_ggml_op_type), get_qnn_backend_name(n_backend_type), n_duration);
return 0;
}
#define DEFINE_OP(op) { #op, op }
@ -517,6 +514,10 @@ static const std::unordered_map<std::string, int> kMapStringToGGMLOp = {
DEFINE_OP(GGML_OP_SQRT), DEFINE_OP(GGML_OP_MUL_MAT), DEFINE_OP(GGML_OP_LOG),
};
#define CONSOLE_RED "\033[31m"
#define CONSOLE_GREEN "\033[32m"
#define CONSOLE_RESET "\033[0m"
int main(int argc, char *argv[]) {
int num_threads = 4;
int n_backend_type = QNN_BACKEND_CPU;
@ -554,7 +555,17 @@ int main(int argc, char *argv[]) {
QNN_LOG_DEBUG("enter qnn_ggml_op\n");
QNN_LOG_DEBUG("backend %d, ggml op:%d(%s)", n_backend_type, n_ggml_op_type,
ggml_op_name((enum ggml_op)n_ggml_op_type));
qnn_op_ut(num_threads, n_backend_type, n_ggml_op_type);
return 0;
std::vector<uint8_t> results;
qnn_op_ut(num_threads, n_backend_type, n_ggml_op_type, GGML_TYPE_F32, results);
std::vector<uint8_t> cpu_results;
qnn_op_ut(num_threads, QNN_BACKEND_GGML, n_ggml_op_type, GGML_TYPE_F32, cpu_results);
if (results == cpu_results) {
QNN_LOG_INFO(CONSOLE_GREEN "[Result] results equal!" CONSOLE_RESET);
return 0;
} else {
QNN_LOG_ERROR(CONSOLE_RED "[Result] results not equal!" CONSOLE_RESET);
return 1;
}
}