C++ Example - 1.4 English

Vitis AI User Guide (UG1414)

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1.4 English
// get dpu subgraph by parsing model file
auto runner = vart::Runner::create_runner(subgraph, "run");
// populate input/output tensors
auto job_data = runner->execute_async(inputs, outputs);
runner->wait(job_data.first, -1);
// process outputs

Xilinx provides a C wrapper for the C++ DpuRunner class:

void* DpuPyRunnerCreate(char* path);
void DpuPyRunnerGetInputTensors(void* runner, DpuPyTensor** tensors, int* tensor_cnt);
void DpuPyRunnerGetOutputTensors(void* runner, DpuPyTensor** tensors, int* tensor_cnt);
int DpuPyRunnerGetTensorFormat(void* runner);
int DpuPyRunnerExecuteAsync(void* runner, void** indata, void** outdata,int batch_sz, int* status);
int DpuPyRunnerWait(void* runner, int jobId);
void DpuPyRunnerDestroy(void* runner);

Vitis AI also provides a Python ctypes Runner class that mirrors the C++ class, using the C DpuRunner implementation:

class Runner:
def __init__(self, path)
def get_input_tensors(self)
def get_output_tensors(self)
def get_tensor_format(self)
def execute_async(self, inputs, outputs)
# differences from the C++ API:
# 1. inputs and outputs are numpy arrays with C memory layout
#    the numpy arrays should be reused as their internal buffer 
#    pointers are passed to the runtime. These buffer pointers
#    may be memory-mapped to the FPGA DDR for performance.
# 2. returns job_id, throws exception on error
def wait(self, job_id)