mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 00:33:03 +08:00
5046574b95
* fix error for part of detection model * fix error for part of detection model * add patch paddle inference
90 lines
3.3 KiB
C++
90 lines
3.3 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// 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 "fastdeploy/backends/paddle/paddle_backend.h"
|
|
|
|
namespace fastdeploy {
|
|
paddle_infer::PlaceType ConvertFDDeviceToPlace(Device device) {
|
|
if (device == Device::GPU) {
|
|
return paddle_infer::PlaceType::kGPU;
|
|
}
|
|
return paddle_infer::PlaceType::kCPU;
|
|
}
|
|
|
|
void ShareTensorFromFDTensor(paddle_infer::Tensor* tensor,
|
|
FDTensor& fd_tensor) {
|
|
std::vector<int> shape(fd_tensor.shape.begin(), fd_tensor.shape.end());
|
|
tensor->Reshape(shape);
|
|
auto place = ConvertFDDeviceToPlace(fd_tensor.device);
|
|
if (fd_tensor.dtype == FDDataType::FP32) {
|
|
tensor->ShareExternalData(static_cast<const float*>(fd_tensor.Data()),
|
|
shape, place);
|
|
return;
|
|
} else if (fd_tensor.dtype == FDDataType::INT32) {
|
|
tensor->ShareExternalData(static_cast<const int32_t*>(fd_tensor.Data()),
|
|
shape, place);
|
|
return;
|
|
} else if (fd_tensor.dtype == FDDataType::INT64) {
|
|
tensor->ShareExternalData(static_cast<const int64_t*>(fd_tensor.Data()),
|
|
shape, place);
|
|
return;
|
|
}
|
|
FDASSERT(false, "Unexpected data type(%s) while infer with PaddleBackend.",
|
|
Str(fd_tensor.dtype).c_str());
|
|
}
|
|
|
|
void CopyTensorToCpu(std::unique_ptr<paddle_infer::Tensor>& tensor,
|
|
FDTensor* fd_tensor) {
|
|
auto fd_dtype = PaddleDataTypeToFD(tensor->type());
|
|
std::vector<int64_t> shape;
|
|
auto tmp_shape = tensor->shape();
|
|
shape.assign(tmp_shape.begin(), tmp_shape.end());
|
|
fd_tensor->Allocate(shape, fd_dtype, tensor->name());
|
|
if (fd_tensor->dtype == FDDataType::FP32) {
|
|
tensor->CopyToCpu(static_cast<float*>(fd_tensor->MutableData()));
|
|
return;
|
|
} else if (fd_tensor->dtype == FDDataType::INT32) {
|
|
tensor->CopyToCpu(static_cast<int32_t*>(fd_tensor->MutableData()));
|
|
return;
|
|
} else if (fd_tensor->dtype == FDDataType::INT64) {
|
|
tensor->CopyToCpu(static_cast<int64_t*>(fd_tensor->MutableData()));
|
|
return;
|
|
}
|
|
FDASSERT(false, "Unexpected data type(%s) while infer with PaddleBackend.",
|
|
Str(fd_tensor->dtype).c_str());
|
|
}
|
|
|
|
FDDataType PaddleDataTypeToFD(const paddle_infer::DataType& dtype) {
|
|
auto fd_dtype = FDDataType::FP32;
|
|
if (dtype == paddle_infer::FLOAT32) {
|
|
fd_dtype = FDDataType::FP32;
|
|
} else if (dtype == paddle_infer::INT64) {
|
|
fd_dtype = FDDataType::INT64;
|
|
} else if (dtype == paddle_infer::INT32) {
|
|
fd_dtype = FDDataType::INT32;
|
|
} else if (dtype == paddle_infer::UINT8) {
|
|
fd_dtype = FDDataType::UINT8;
|
|
} else if (dtype == paddle_infer::INT8) {
|
|
fd_dtype = FDDataType::INT8;
|
|
}else {
|
|
FDASSERT(
|
|
false,
|
|
"Unexpected data type: %d while call CopyTensorToCpu in PaddleBackend.",
|
|
int(dtype));
|
|
}
|
|
return fd_dtype;
|
|
}
|
|
|
|
} // namespace fastdeploy
|