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[XPU] Support XPU via Paddle Inference backend (#1987)

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* [backend] Support XPU via Paddle Inference backend

* [backend] Support XPU via Paddle Inference backend

* [backend] Support XPU via Paddle Inference backend

* [XPU] support XPU benchmark via paddle inference

* [XPU] support XPU benchmark via paddle inference

* [benchmark] add xpu paddle h2d config files
This commit is contained in:
DefTruth
2023-05-25 14:13:40 +08:00
committed by GitHub
parent 24f32d10a7
commit 49c033a828
16 changed files with 262 additions and 57 deletions
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57
fastdeploy/runtime/runtime_option.cc
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@@ -79,14 +79,18 @@ void RuntimeOption::UseTimVX() {
paddle_lite_option.device = device;
}
void RuntimeOption::UseKunlunXin(int kunlunxin_id, int l3_workspace_size,
void RuntimeOption::UseKunlunXin(int kunlunxin_id,
int l3_workspace_size,
bool locked, bool autotune,
const std::string& autotune_file,
const std::string& precision,
bool adaptive_seqlen,
bool enable_multi_stream,
int64_t gm_default_size) {
#ifdef WITH_KUNLUNXIN
device = Device::KUNLUNXIN;
#ifdef ENABLE_LITE_BACKEND
paddle_lite_option.device = device;
paddle_lite_option.device_id = kunlunxin_id;
paddle_lite_option.kunlunxin_l3_workspace_size = l3_workspace_size;
@@ -97,6 +101,42 @@ void RuntimeOption::UseKunlunXin(int kunlunxin_id, int l3_workspace_size,
paddle_lite_option.kunlunxin_adaptive_seqlen = adaptive_seqlen;
paddle_lite_option.kunlunxin_enable_multi_stream = enable_multi_stream;
paddle_lite_option.kunlunxin_gm_default_size = gm_default_size;
#endif
#ifdef ENABLE_PADDLE_BACKEND
paddle_infer_option.device = device;
paddle_infer_option.xpu_option.kunlunxin_device_id = kunlunxin_id;
paddle_infer_option.xpu_option.kunlunxin_l3_workspace_size = l3_workspace_size;
paddle_infer_option.xpu_option.kunlunxin_locked = locked;
paddle_infer_option.xpu_option.kunlunxin_autotune = autotune;
paddle_infer_option.xpu_option.kunlunxin_autotune_file = autotune_file;
paddle_infer_option.xpu_option.kunlunxin_precision = precision;
paddle_infer_option.xpu_option.kunlunxin_adaptive_seqlen = adaptive_seqlen;
paddle_infer_option.xpu_option.kunlunxin_enable_multi_stream = enable_multi_stream;
// paddle_infer_option.xpu_option.kunlunxin_gm_default_size = gm_default_size;
// use paddle_infer_option.xpu_option.SetXpuConfig() for more options.
#endif
#else
FDWARNING << "The FastDeploy didn't compile with KUNLUNXIN, will force to use CPU."
<< std::endl;
device = Device::CPU;
#endif
}
void RuntimeOption::UseIpu(int device_num, int micro_batch_size,
bool enable_pipelining, int batches_per_step) {
#ifdef WITH_IPU
device = Device::IPU;
paddle_infer_option.ipu_option.ipu_device_num = device_num;
paddle_infer_option.ipu_option.ipu_micro_batch_size = micro_batch_size;
paddle_infer_option.ipu_option.ipu_enable_pipelining = enable_pipelining;
paddle_infer_option.ipu_option.ipu_batches_per_step = batches_per_step;
// use paddle_infer_option.ipu_option.SetIpuConfig() for more options.
#else
FDWARNING << "The FastDeploy didn't compile with IPU, will force to use CPU."
<< std::endl;
device = Device::CPU;
#endif
}
void RuntimeOption::UseAscend() {
@@ -484,19 +524,4 @@ void RuntimeOption::DisablePaddleTrtOPs(const std::vector<std::string>& ops) {
paddle_infer_option.DisableTrtOps(ops);
}
void RuntimeOption::UseIpu(int device_num, int micro_batch_size,
bool enable_pipelining, int batches_per_step) {
#ifdef WITH_IPU
device = Device::IPU;
ipu_device_num = device_num;
ipu_micro_batch_size = micro_batch_size;
ipu_enable_pipelining = enable_pipelining;
ipu_batches_per_step = batches_per_step;
#else
FDWARNING << "The FastDeploy didn't compile with IPU, will force to use CPU."
<< std::endl;
device = Device::CPU;
#endif
}
} // namespace fastdeploy