onert::backend::trix Namespace Reference

Namespaces
namespace	ops

Data Structures
class	Backend
class	BackendContext
class	BatchThreadPool
	Class that has a threadpool for batch-by-batch multi-threading. More...
class	Config
class	DevContext
	NPU device context of trix backend. More...
class	KernelGenerator

Typedefs
using	ModelID = uint32_t
using	Tensor = basic::Tensor
using	ExternalTensor = basic::ExternalTensor
using	TensorBuilder = basic::TensorBuilder

Functions
data_type	convertDataType (const ir::DataType type)
	Convert type of data from onert type to npu type.
template<typename T , std::enable_if_t< std::is_base_of_v< IPortableTensor, T >, bool > = true>
void	setDataInfo (const std::vector< T * > &tensors, tensors_data_info *info)
	Set the tensors_data_info object.
template<typename T , std::enable_if_t< std::is_base_of_v< IPortableTensor, T >, bool > = true>
void	setBuffers (const std::vector< T * > &tensors, generic_buffers *buf)
	Set the generic_buffers object.

Typedef Documentation

ExternalTensor

using onert::backend::trix::ExternalTensor = typedef basic::ExternalTensor

Definition at line 27 of file Tensor.h.

ModelID

using onert::backend::trix::ModelID = typedef uint32_t

Definition at line 30 of file DevContext.h.

Tensor

using onert::backend::trix::Tensor = typedef basic::Tensor

Definition at line 26 of file Tensor.h.

TensorBuilder

using onert::backend::trix::TensorBuilder = typedef basic::TensorBuilder

Definition at line 25 of file TensorBuilder.h.

Function Documentation

convertDataType()

data_type onert::backend::trix::convertDataType

(

const ir::DataType

type

)

Convert type of data from onert type to npu type.

Parameters

type	Data type in onert

Returns

data_type Data type in npu

Definition at line 22 of file Convert.cc.

{
  switch (type)
  {
    case ir::DataType::QUANT_UINT8_ASYMM:
      return DATA_TYPE_QASYMM8;
    case ir::DataType::QUANT_INT16_SYMM:
      return DATA_TYPE_QSYMM16;
    default:
      throw std::runtime_error("Unsupported data type");
  }
}

Referenced by setDataInfo().

setBuffers()

template<typename T , std::enable_if_t< std::is_base_of_v< IPortableTensor, T >, bool > = true>

void onert::backend::trix::setBuffers	(	const std::vector< T * > &	tensors,
		generic_buffers *	buf
	)

Set the generic_buffers object.

Template Parameters

T	Type of tensor based of IPortableTensor

Parameters

tensors	Tensors that have buffer information
buf	generic_buffers to be set

Definition at line 65 of file Convert.h.

{
  buf->num_buffers = static_cast<uint32_t>(tensors.size());
 
  for (uint32_t idx = 0; idx < buf->num_buffers; ++idx)
  {
    buf->bufs[idx].addr = tensors[idx]->buffer();
    buf->bufs[idx].size = static_cast<uint64_t>(tensors[idx]->total_size());
    buf->bufs[idx].type = BUFFER_MAPPED;
  }
}

Referenced by onert::backend::trix::ops::BulkLayer::run().

setDataInfo()

template<typename T , std::enable_if_t< std::is_base_of_v< IPortableTensor, T >, bool > = true>

void onert::backend::trix::setDataInfo	(	const std::vector< T * > &	tensors,
		tensors_data_info *	info
	)

Set the tensors_data_info object.

Template Parameters

T	Type of tensor based of IPortableTensor

Parameters

tensors	Tensors that have data information
info	tensors_data_info to be set

Definition at line 46 of file Convert.h.

{
  info->num_info = static_cast<uint32_t>(tensors.size());
 
  for (uint32_t idx = 0; idx < info->num_info; ++idx)
  {
    info->info[idx].layout = DATA_LAYOUT_NHWC;
    info->info[idx].type = convertDataType(tensors[idx]->data_type());
  }
}

References convertDataType(), and info.

Referenced by onert::backend::trix::ops::BulkLayer::run().