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36124f6205
* check in cmake * move backend_ops to csrc/backend_ops * check in preprocess, model, some codebase and their c-apis * check in CMakeLists.txt * check in parts of test_csrc * commit everything else * add readme * update core's BUILD_INTERFACE directory * skip codespell on third_party * update trt_net and ort_net's CMakeLists * ignore clion's build directory * check in pybind11 * add onnx.proto. Remove MMDeploy's dependency on ncnn's source code * export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON * remove useless message * target include directory is wrong * change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net * skip install directory * update project's cmake * remove useless code * set CMAKE_BUILD_TYPE to Release by force if it isn't set by user * update custom ops CMakeLists * pass object target's source lists * fix lint end-of-file * fix lint: trailing whitespace * fix codespell hook * remove bicubic_interpolate to csrc/backend_ops/ * set MMDEPLOY_BUILD_SDK OFF * change custom ops build command * add spdlog installation command * update docs on how to checkout pybind11 * move bicubic_interpolate to backend_ops/tensorrt directory * remove useless code * correct cmake * fix typo * fix typo * fix install directory * correct sdk's readme * set cub dir when cuda version < 11.0 * change directory where clang-format will apply to * fix build command * add .clang-format * change clang-format style from google to file * reformat csrc/backend_ops * format sdk's code * turn off clang-format for some files * add -Xcompiler=-fno-gnu-unique * fix trt topk initialize * check in config for sdk demo * update cmake script and csrc's readme * correct config's path * add cuda include directory, otherwise compile failed in case of tensorrt8.2 * clang-format onnx2ncnn.cpp Co-authored-by: zhangli <lzhang329@gmail.com> Co-authored-by: grimoire <yaoqian@sensetime.com>
55 lines
1.5 KiB
C++
Executable File
55 lines
1.5 KiB
C++
Executable File
// Copyright (c) OpenMMLab. All rights reserved.
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#include "constantofshape.h"
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#include "../ncnn_ops_definer.h"
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namespace mmdeploy {
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using namespace ncnn;
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DEFINE_LAYER_CREATOR(ConstantOfShape)
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DEFINE_NCNN_OPS(ConstantOfShape, ConstantOfShape)
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ConstantOfShape::ConstantOfShape() {
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one_blob_only = true;
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support_inplace = false;
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}
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int ConstantOfShape::load_param(const ParamDict& pd) {
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val = pd.get(0, 0.f);
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return 0;
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}
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int ConstantOfShape::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) const {
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int dims = bottom_blob.w - 1;
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const float* bottom_ptr = bottom_blob;
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const float* shape_ptr = bottom_ptr + 1;
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if (dims == 1) {
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int w = (int)(shape_ptr[0] + 0.5);
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size_t elemsize = sizeof(val);
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top_blob.create(w, elemsize, opt.blob_allocator);
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if (top_blob.empty()) return -100;
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top_blob.fill(val);
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return 0;
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}
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if (dims == 2) {
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int h = (int)(shape_ptr[0] + 0.5);
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int w = (int)(shape_ptr[1] + 0.5);
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size_t elemsize = sizeof(val);
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top_blob.create(w, h, elemsize, opt.blob_allocator);
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if (top_blob.empty()) return -100;
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top_blob.fill(val);
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return 0;
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}
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if (dims == 3) {
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int channels = (int)(shape_ptr[0] + 0.5);
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int h = (int)(shape_ptr[1] + 0.5);
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int w = (int)(shape_ptr[2] + 0.5);
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size_t elemsize = sizeof(val);
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top_blob.create(w, h, channels, elemsize, opt.blob_allocator);
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if (top_blob.empty()) return -100;
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top_blob.fill(val);
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return 0;
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}
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}
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} // namespace mmdeploy
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