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7f4a0afc68280b27f4ffe3e10326c1a877a7be56
neural_network_runtime/frameworks/native/transform.cpp
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yangyongjie 7f4a0afc68 !1 Add Neural Network Runtime code 
* add neural network runtime
2022-10-28 02:32:29 +00:00

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/*
* Copyright (c) 2022 Huawei Device Co., Ltd.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "transform.h"
#include "memory_manager.h"
#include "common/log.h"
namespace OHOS {
namespace NeuralNetworkRuntime {
const uint32_t BIT8_TO_BYTE = 1;
const uint32_t BIT16_TO_BYTE = 2;
const uint32_t BIT32_TO_BYTE = 4;
const uint32_t BIT64_TO_BYTE = 8;
OH_NN_DeviceType HDIToNN::TransHDIDeviceType(const V1_0::DeviceType& iDeviceType)
{
switch (iDeviceType) {
case V1_0::DeviceType::CPU:
return OH_NN_CPU;
case V1_0::DeviceType::GPU:
return OH_NN_GPU;
case V1_0::DeviceType::ACCELERATOR:
return OH_NN_ACCELERATOR;
default:
return OH_NN_OTHERS;
}
}
DeviceStatus HDIToNN::TransHDIDeviceStatus(const V1_0::DeviceStatus& iDeviceStatus)
{
switch (iDeviceStatus) {
case V1_0::DeviceStatus::AVAILABLE:
return DeviceStatus::AVAILABLE;
case V1_0::DeviceStatus::BUSY:
return DeviceStatus::BUSY;
case V1_0::DeviceStatus::OFFLINE:
return DeviceStatus::OFFLINE;
default:
return DeviceStatus::UNKNOWN;
}
}
V1_0::PerformanceMode NNToHDI::TransPerformanceMode(const OH_NN_PerformanceMode& mode)
{
switch (mode) {
case OH_NN_PERFORMANCE_LOW:
return V1_0::PerformanceMode::PERFORMANCE_LOW;
case OH_NN_PERFORMANCE_MEDIUM:
return V1_0::PerformanceMode::PERFORMANCE_MEDIUM;
case OH_NN_PERFORMANCE_HIGH:
return V1_0::PerformanceMode::PERFORMANCE_HIGH;
case OH_NN_PERFORMANCE_EXTREME:
return V1_0::PerformanceMode::PERFORMANCE_EXTREME;
default:
return V1_0::PerformanceMode::PERFORMANCE_NONE;
}
}
V1_0::Priority NNToHDI::TransPriority(const OH_NN_Priority& priority)
{
switch (priority) {
case OH_NN_PRIORITY_LOW:
return V1_0::Priority::PRIORITY_LOW;
case OH_NN_PRIORITY_MEDIUM:
return V1_0::Priority::PRIORITY_MEDIUM;
case OH_NN_PRIORITY_HIGH:
return V1_0::Priority::PRIORITY_HIGH;
default:
return V1_0::Priority::PRIORITY_NONE;
}
}
V1_0::DataType NNToHDI::TransDataType(const OH_NN_DataType& dataType)
{
switch (dataType) {
case OH_NN_BOOL:
return V1_0::DataType::DATA_TYPE_BOOL;
case OH_NN_INT8:
return V1_0::DataType::DATA_TYPE_INT8;
case OH_NN_INT16:
return V1_0::DataType::DATA_TYPE_INT16;
case OH_NN_INT32:
return V1_0::DataType::DATA_TYPE_INT32;
case OH_NN_INT64:
return V1_0::DataType::DATA_TYPE_INT64;
case OH_NN_UINT8:
return V1_0::DataType::DATA_TYPE_UINT8;
case OH_NN_UINT16:
return V1_0::DataType::DATA_TYPE_UINT16;
case OH_NN_UINT32:
return V1_0::DataType::DATA_TYPE_UINT32;
case OH_NN_UINT64:
return V1_0::DataType::DATA_TYPE_UINT64;
case OH_NN_FLOAT16:
return V1_0::DataType::DATA_TYPE_FLOAT16;
case OH_NN_FLOAT32:
return V1_0::DataType::DATA_TYPE_FLOAT32;
case OH_NN_FLOAT64:
return V1_0::DataType::DATA_TYPE_FLOAT64;
default:
return V1_0::DataType::DATA_TYPE_UNKNOWN;
}
}
V1_0::Format NNToHDI::TransFormat(const OH_NN_Format& format)
{
switch (format) {
case OH_NN_FORMAT_NCHW:
return V1_0::Format::FORMAT_NCHW;
case OH_NN_FORMAT_NHWC:
return V1_0::Format::FORMAT_NHWC;
default:
return V1_0::Format::FORMAT_NONE;
}
}
V1_0::IOTensor NNToHDI::TransIOTensor(const IOTensor& tensor)
{
V1_0::IOTensor iTensor;
iTensor.name = tensor.name;
iTensor.dataType = TransDataType(tensor.dataType);
iTensor.dimensions = tensor.dimensions;
iTensor.format = TransFormat(tensor.format);
V1_0::SharedBuffer iBuffer {INVALID_FD, 0, 0, 0};
if (tensor.data != nullptr) {
auto memManager = MemoryManager::GetInstance();
Memory memory;
auto ret = memManager->GetMemory(tensor.data, memory);
if (ret != OH_NN_SUCCESS) {
LOGE("Invalid Tensor buffer, cannot transform to fd.");
} else {
iBuffer.fd = memory.fd;
iBuffer.bufferSize = memory.length;
iBuffer.offset = 0;
iBuffer.dataSize = memory.length;
}
}
iTensor.data = iBuffer;
return iTensor;
}
uint32_t GetTypeSize(OH_NN_DataType type)
{
switch (type) {
case OH_NN_BOOL:
return sizeof(bool);
case OH_NN_INT8:
case OH_NN_UINT8:
return BIT8_TO_BYTE;
case OH_NN_INT16:
case OH_NN_UINT16:
case OH_NN_FLOAT16:
return BIT16_TO_BYTE;
case OH_NN_INT32:
case OH_NN_UINT32:
case OH_NN_FLOAT32:
return BIT32_TO_BYTE;
case OH_NN_INT64:
case OH_NN_UINT64:
case OH_NN_FLOAT64:
return BIT64_TO_BYTE;
default:
return 0;
}
}
mindspore::lite::DataType NNToMS::TransformDataType(OH_NN_DataType type)
{
switch (type) {
case OH_NN_BOOL:
return mindspore::lite::DATA_TYPE_BOOL;
case OH_NN_INT8:
return mindspore::lite::DATA_TYPE_INT8;
case OH_NN_INT16:
return mindspore::lite::DATA_TYPE_INT16;
case OH_NN_INT32:
return mindspore::lite::DATA_TYPE_INT32;
case OH_NN_INT64:
return mindspore::lite::DATA_TYPE_INT64;
case OH_NN_UINT8:
return mindspore::lite::DATA_TYPE_UINT8;
case OH_NN_UINT16:
return mindspore::lite::DATA_TYPE_UINT16;
case OH_NN_UINT32:
return mindspore::lite::DATA_TYPE_UINT32;
case OH_NN_UINT64:
return mindspore::lite::DATA_TYPE_UINT64;
case OH_NN_FLOAT16:
return mindspore::lite::DATA_TYPE_FLOAT16;
case OH_NN_FLOAT32:
return mindspore::lite::DATA_TYPE_FLOAT32;
case OH_NN_FLOAT64:
return mindspore::lite::DATA_TYPE_FLOAT64;
default:
return mindspore::lite::DATA_TYPE_UNKNOWN;
}
}
mindspore::lite::Format NNToMS::TransformFormat(OH_NN_Format type)
{
switch (type) {
case OH_NN_FORMAT_NCHW:
return mindspore::lite::FORMAT_NCHW;
case OH_NN_FORMAT_NHWC:
return mindspore::lite::FORMAT_NHWC;
default:
return mindspore::lite::FORMAT_NHWC;
}
}
mindspore::lite::ActivationType NNToMS::TransfromFusionType(OH_NN_FuseType type)
{
switch (type) {
case OH_NN_FUSED_NONE:
return mindspore::lite::ACTIVATION_TYPE_NO_ACTIVATION;
case OH_NN_FUSED_RELU:
return mindspore::lite::ACTIVATION_TYPE_RELU;
case OH_NN_FUSED_RELU6:
return mindspore::lite::ACTIVATION_TYPE_RELU6;
default:
return mindspore::lite::ACTIVATION_TYPE_UNKNOWN;
}
}
mindspore::lite::QuantType NNToMS::TransformQuantType(OHOS::NeuralNetworkRuntime::Ops::OpsQuantType type)
{
switch (type) {
case OHOS::NeuralNetworkRuntime::Ops::OpsQuantType::QUANT_NONE:
return mindspore::lite::QUANT_TYPE_NONE;
case OHOS::NeuralNetworkRuntime::Ops::OpsQuantType::QUANT_ALL:
return mindspore::lite::QUANT_TYPE_ALL;
default: return mindspore::lite::QUANT_TYPE_NONE;
}
}
mindspore::lite::PadMode NNToMS::TransformPadModeValue(int8_t padMode)
{
// The value is an optional value of the int8_t type. The value 0 indicates the same,
// and the value 1 indicates valid.
return (padMode == 0) ? mindspore::lite::PadMode::PAD_MODE_SAME :
mindspore::lite::PadMode::PAD_MODE_VALID;
}
OH_NN_DataType MSToNN::TransformDataType(mindspore::lite::DataType type)
{
switch (type) {
case mindspore::lite::DATA_TYPE_BOOL:
return OH_NN_BOOL;
case mindspore::lite::DATA_TYPE_INT8:
return OH_NN_INT8;
case mindspore::lite::DATA_TYPE_INT16:
return OH_NN_INT16;
case mindspore::lite::DATA_TYPE_INT32:
return OH_NN_INT32;
case mindspore::lite::DATA_TYPE_INT64:
return OH_NN_INT64;
case mindspore::lite::DATA_TYPE_UINT8:
return OH_NN_UINT8;
case mindspore::lite::DATA_TYPE_UINT16:
return OH_NN_UINT16;
case mindspore::lite::DATA_TYPE_UINT32:
return OH_NN_UINT32;
case mindspore::lite::DATA_TYPE_UINT64:
return OH_NN_UINT64;
case mindspore::lite::DATA_TYPE_FLOAT16:
return OH_NN_FLOAT16;
case mindspore::lite::DATA_TYPE_FLOAT32:
return OH_NN_FLOAT32;
case mindspore::lite::DATA_TYPE_FLOAT64:
return OH_NN_FLOAT64;
default:
return OH_NN_UNKNOWN;
}
}
std::vector<QuantParam> MSToNN::TransformQuantParams(std::vector<mindspore::lite::QuantParam> msQuantParams)
{
std::vector<QuantParam> nnQuantParam;
for (const mindspore::lite::QuantParam& param : msQuantParams) {
nnQuantParam.emplace_back((QuantParam){param.numBits, param.scale, param.zeroPoint});
}
return nnQuantParam;
}
} // namespace NeuralNetworkRuntime
} // namespace OHOS
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