Move cpp code to directory csrcs (#42)

* move cpp code to csrcs

* move cpp code to csrcs
This commit is contained in:
Jason
2022-07-26 17:59:02 +08:00
committed by GitHub
parent 7fa3afa9de
commit ffbc5cc42d
128 changed files with 1 additions and 1 deletions

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@@ -1,88 +0,0 @@
// 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.
#pragma once
#include <pybind11/numpy.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <type_traits>
#include "fastdeploy/fastdeploy_runtime.h"
#ifdef ENABLE_VISION
#include "fastdeploy/vision.h"
#endif
namespace fastdeploy {
void BindBackend(pybind11::module&);
void BindVision(pybind11::module&);
pybind11::dtype FDDataTypeToNumpyDataType(const FDDataType& fd_dtype);
FDDataType NumpyDataTypeToFDDataType(const pybind11::dtype& np_dtype);
void PyArrayToTensor(pybind11::array& pyarray, FDTensor* tensor,
bool share_buffer = false);
#ifdef ENABLE_VISION
cv::Mat PyArrayToCvMat(pybind11::array& pyarray);
#endif
template <typename T> FDDataType CTypeToFDDataType() {
if (std::is_same<T, int32_t>::value) {
return FDDataType::INT32;
} else if (std::is_same<T, int64_t>::value) {
return FDDataType::INT64;
} else if (std::is_same<T, float>::value) {
return FDDataType::FP32;
} else if (std::is_same<T, double>::value) {
return FDDataType::FP64;
}
FDASSERT(false,
"CTypeToFDDataType only support int32/int64/float32/float64 now.");
return FDDataType::FP32;
}
template <typename T>
std::vector<pybind11::array>
PyBackendInfer(T& self, const std::vector<std::string>& names,
std::vector<pybind11::array>& data) {
std::vector<FDTensor> inputs(data.size());
for (size_t i = 0; i < data.size(); ++i) {
// TODO(jiangjiajun) here is considered to use user memory directly
inputs[i].dtype = NumpyDataTypeToFDDataType(data[i].dtype());
inputs[i].shape.insert(inputs[i].shape.begin(), data[i].shape(),
data[i].shape() + data[i].ndim());
inputs[i].data.resize(data[i].nbytes());
memcpy(inputs[i].data.data(), data[i].mutable_data(), data[i].nbytes());
inputs[i].name = names[i];
}
std::vector<FDTensor> outputs(self.NumOutputs());
self.Infer(inputs, &outputs);
std::vector<pybind11::array> results;
results.reserve(outputs.size());
for (size_t i = 0; i < outputs.size(); ++i) {
auto numpy_dtype = FDDataTypeToNumpyDataType(outputs[i].dtype);
results.emplace_back(pybind11::array(numpy_dtype, outputs[i].shape));
memcpy(results[i].mutable_data(), outputs[i].data.data(),
outputs[i].Numel() * FDDataTypeSize(outputs[i].dtype));
}
return results;
}
} // namespace fastdeploy