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This section introduces some public classes and functions of PPLNN.

Engine

Defined in include/ppl/nn/engines/engine.h.

An Engine is a collection of op implementations running on specified devices such as CPU or Nvidia GPU.

Functions

ppl::common::RetCode Configure(uint32_t option, ...);

Sets various options for this engine. Parameters vary depending on the first parameter option.

X86EngineFactory

A built-in engine factory thas is used to create engines running on x86-compatitable CPUs.

Functions

Engine* X86EngineFactory::Create();

Creates a x86 engine instance.

CudaEngineFactory

A built-in engine factory thas is used to create engines running on NVIDIA GPUs.

Functions

Engine* CudaEngineFactory::Create();

Creates a CUDA engine instance.

OnnxRuntimeBuilderFactory

Defined in include/ppl/nn/models/onnx/onnx_runtime_builder_factory.h.

Used to create an OnnxRuntimeBuilder.

Functions

OnnxRuntimeBuilder* Create(const char* model_file,
                           std::vector<std::unique_ptr<Engine>>&&);

Creates an OnnxRuntimeBuilder instance from an ONNX model file. The first parameter is the model file path, the second is engines that may be used to evaluate the compute graph.

OnnxRuntimeBuilder* Create(const char* model_buf, uint64_t buf_len,
                           std::vector<std::unique_ptr<Engine>>&&);

Creates an OnnxRuntimeBuilder instance from an ONNX buffer.

OnnxRuntimeBuilder

Defined in include/ppl/nn/models/onnx/onnx_runtime_builder.h.

OnnxRuntimeBuilder is used to create Runtime instances. It contains read-only data that a Runtime needs.

Functions

Runtime* CreateRuntime(const RuntimeOptions&);

Creates a Runtime instance which is used to evaluate a compute graph. The parameter RuntimeOptions is defined in src/ppl/runtime/runtime_options.h.

Runtime

Defined in include/ppl/nn/runtime/runtime.h.

Runtime is the main structure for evaluating a model.

Functions

ppl::common::RetCode Configure(uint32_t option, ...);

Sets various runtime options defined in runtime_options.h. Parameters vary depending on the first parameter option.

uint32_t GetInputCount() const;

Gets the number of input of the associated graph.

Tensor* GetInputTensor(uint32_t idx) const;

Gets the input tensor at position idx. Note that idx should be less than the number of inputs.

ppl::common::RetCode Run();

Runs the model with given inputs. Input data MUST be filled via the returned value of GetInputTensor() before calling this function.

ppl::common::RetCode Sync();

Blocks current CPU thread until all operations are finished. Note that this function MUST be called before getting outputs or profiling statistics, in case some engine may run asynchronously.

uint32_t GetOutputCount() const;

Gets the number of outputs of the associated graph.

Tensor* GetOutputTensor(uint32_t idx) const;

Gets the output tensor at position idx. Note that idx should be less than the number of outputs.

ppl::common::RetCode GetProfilingStatistics(ProfilingStatistics*) const;

Gets profiling statistics of each kernel. Note that this function is available if PPLNN_ENABLE_KERNEL_PROFILING is enable.

Tensor

Defined in include/ppl/nn/runtime/tensor.h.

This structure represents the input/output data.

Functions

ppl::common::TensorShape& GetShape();
const ppl::common::TensorShape& GetShape() const;

Gets the shape of this tensor.

ppl::common::RetCode ReallocBuffer();

Reallocates a buffer according to its shape.

ppl::common::RetCode CopyToHost(void* dst) const;

Copies tensor's data to dst which points to a host memory. Note that dst MUST have enough space.

ppl::common::RetCode CopyFromHost(const void* src);

Copies data to inner buffer from src, which points to a host memory. Note that inner buffer MUST be allocated before calling this function.

ppl::common::RetCode ConvertToHost(void* dst, const ppl::common::TensorShape& dst_desc) const;

Converts tensor's data to dst with the shape dst_desc.

ppl::common::RetCode ConvertFromHost(const void* src, const ppl::common::TensorShape& src_desc);

Converts data to inner buffer from src with the shape src_desc. Note that inner buffer MUST be allocated before calling this function.

TensorShape

Defined in include/ppl/nn/common/tensor_shape.h.

Logger

Defined in src/ppl/common/log.h.

void SetCurrentLogger(Logger*);

Sets global logger for pplnn internal logging.

Logger* GetCurrentLogger();

Gets the logger for pplnn internal logging. Default is a StdioLogger that prints logs to stdout/stderr.

void Logger::SetLogLevel(uint32_t);
uint32_t Logger::GetLogLevel() const;

Sets/gets the level for logging. Any log level that is less than Logger::GetLogLevel() will not be logged.

All API references(in html format) can be generated by running doxygen docs/Doxyfile.