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[Sync][Internal] sync some internal paddle3d codes (PaddlePaddle#2108)
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,81 @@ | ||
| // Copyright (c) 2023 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 "flags.h" | ||
| #include "macros.h" | ||
| #include "option.h" | ||
|
|
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| namespace vision = fastdeploy::vision; | ||
| namespace benchmark = fastdeploy::benchmark; | ||
|
|
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| int main(int argc, char* argv[]) { | ||
| #if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION) | ||
| // Initialization | ||
| auto option = fastdeploy::RuntimeOption(); | ||
| if (!CreateRuntimeOption(&option, argc, argv, true)) { | ||
| return -1; | ||
| } | ||
| auto im = cv::imread(FLAGS_image); | ||
| std::unordered_map<std::string, std::string> config_info; | ||
| benchmark::ResultManager::LoadBenchmarkConfig(FLAGS_config_path, | ||
| &config_info); | ||
| std::string model_name, params_name, config_name; | ||
| auto model_format = fastdeploy::ModelFormat::PADDLE; | ||
| if (!UpdateModelResourceName(&model_name, ¶ms_name, &config_name, | ||
| &model_format, config_info, false)) { | ||
| return -1; | ||
| } | ||
| auto model_file = FLAGS_model + sep + model_name; | ||
| auto params_file = FLAGS_model + sep + params_name; | ||
| std::vector<float> cam_data{7.183351e+02, 0.000000e+00, 6.003891e+02, | ||
| 4.450382e+01, 0.000000e+00, 7.183351e+02, | ||
| 1.815122e+02, -5.951107e-01, 0.000000e+00, | ||
| 0.000000e+00, 1.000000e+00, 2.616315e-03}; | ||
| std::vector<float> lidar_data = { | ||
| 0.0048523, -0.9999298, -0.01081266, -0.00711321, | ||
| -0.00302069, 0.01079808, -0.99993706, -0.06176636, | ||
| 0.99998367, 0.00488465, -0.00296808, -0.26739058, | ||
| 0., 0., 0., 1.}; | ||
| if (config_info["backend"] == "paddle_trt") { | ||
| option.paddle_infer_option.collect_trt_shape = true; | ||
| option.paddle_infer_option.collect_trt_shape_by_device = true; | ||
| option.paddle_infer_option.trt_min_subgraph_size = 12; | ||
| option.paddle_infer_option.DisableTrtOps({"squeeze2"}); | ||
| option.trt_option.max_batch_size = 1; | ||
| } | ||
| if (config_info["backend"] == "paddle_trt" || | ||
| config_info["backend"] == "trt") { | ||
| // use custom data to perform collect shapes. | ||
| option.trt_option.SetShape("images", {1, 3, 375, 1242}, | ||
| {1, 3, 375, 1242}, {1, 3, 375, 1242}); | ||
| option.trt_option.SetShape("trans_lidar_to_cam", {1, 4, 4}, | ||
| {1, 4, 4}, {1, 4, 4}); | ||
| option.trt_option.SetShape("trans_cam_to_img", {1, 3, 4}, | ||
| {1, 3, 4}, {1, 3, 4}); | ||
| std::vector<float> image_data; | ||
| image_data.assign(im.data, im.data + 1*3*375*1242); | ||
| option.trt_option.SetInputData("trans_lidar_to_cam", lidar_data); | ||
| option.trt_option.SetInputData("trans_cam_to_img", cam_data); | ||
| option.trt_option.SetInputData("images", image_data); | ||
| } | ||
| auto model_cadnn = vision::perception::Caddn( | ||
| model_file, params_file, "", option, model_format); | ||
| vision::PerceptionResult res; | ||
| // Run profiling | ||
| BENCHMARK_MODEL(model_cadnn, model_cadnn.Predict(im, cam_data, lidar_data, &res)) | ||
| std::cout << res.Str() << std::endl; | ||
| #endif | ||
|
|
||
| return 0; | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,94 @@ | ||
| // 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. | ||
|
|
||
| #if defined(WITH_GPU) | ||
|
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| #include "grid_sample_3d.h" | ||
|
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| #include <vector> | ||
|
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| #if defined(PADDLEINFERENCE_API_COMPAT_2_4_x) | ||
| #include "paddle/include/experimental/ext_all.h" | ||
| #elif defined(PADDLEINFERENCE_API_COMPAT_2_5_x) | ||
| #include "paddle/include/paddle/extension.h" | ||
| #else | ||
| #include "paddle/extension.h" | ||
| #endif | ||
|
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| namespace fastdeploy { | ||
| namespace paddle_custom_ops { | ||
|
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| std::vector<paddle::Tensor> GridSample3DCUDAForward( | ||
| const paddle::Tensor& x, const paddle::Tensor& grid, | ||
| const std::string& mode, const std::string& padding_mode, | ||
| bool align_corners); | ||
|
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| std::vector<paddle::Tensor> GridSample3DForward(const paddle::Tensor& x, | ||
| const paddle::Tensor& grid, | ||
| const std::string& mode, | ||
| const std::string& padding_mode, | ||
| bool align_corners) { | ||
| return GridSample3DCUDAForward(x, grid, mode, padding_mode, align_corners); | ||
| } | ||
|
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| std::vector<paddle::Tensor> GridSample3DCUDABackward( | ||
| const paddle::Tensor& x, const paddle::Tensor& grid, | ||
| const paddle::Tensor& grad_out, const std::string& mode, | ||
| const std::string& padding_mode, bool align_corners); | ||
|
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| std::vector<paddle::Tensor> GridSample3DBackward( | ||
| const paddle::Tensor& x, const paddle::Tensor& grid, | ||
| const paddle::Tensor& grad_out, const std::string& mode, | ||
| const std::string& padding_mode, bool align_corners) { | ||
| return GridSample3DCUDABackward(x, grid, grad_out, mode, padding_mode, | ||
| align_corners); | ||
| } | ||
|
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| std::vector<std::vector<int64_t>> GridSample3DInferShape( | ||
| std::vector<int64_t> x_shape, std::vector<int64_t> grid_shape) { | ||
| return { | ||
| {x_shape[0], x_shape[1], grid_shape[1], grid_shape[2], grid_shape[3]}}; | ||
| } | ||
|
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| std::vector<std::vector<int64_t>> GridSample3DInferBackShape( | ||
| std::vector<int64_t> x_shape, std::vector<int64_t> grid_shape) { | ||
| return {x_shape}; | ||
| } | ||
|
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| std::vector<paddle::DataType> GridSample3DInferDtype( | ||
| paddle::DataType x_dtype, paddle::DataType grid_dtype) { | ||
| return {x_dtype}; | ||
| } | ||
|
|
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| } // namespace fastdeploy | ||
| } // namespace paddle_custom_ops | ||
|
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| PD_BUILD_OP(grid_sample_3d) | ||
| .Inputs({"x", "grid"}) | ||
| .Attrs({"mode: std::string", "padding_mode: std::string", | ||
| "align_corners: bool"}) | ||
| .Outputs({"out"}) | ||
| .SetKernelFn(PD_KERNEL(fastdeploy::paddle_custom_ops::GridSample3DForward)) | ||
| .SetInferShapeFn(PD_INFER_SHAPE(fastdeploy::paddle_custom_ops::GridSample3DInferShape)) | ||
| .SetInferDtypeFn(PD_INFER_DTYPE(fastdeploy::paddle_custom_ops::GridSample3DInferDtype)); | ||
|
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| PD_BUILD_GRAD_OP(grid_sample_3d) | ||
| .Inputs({"x", "grid", paddle::Grad("out")}) | ||
| .Attrs({"mode: std::string", "padding_mode: std::string", | ||
| "align_corners: bool"}) | ||
| .Outputs({paddle::Grad("x")}) | ||
| .SetKernelFn(PD_KERNEL(fastdeploy::paddle_custom_ops::GridSample3DBackward)) | ||
| .SetInferShapeFn(PD_INFER_SHAPE(fastdeploy::paddle_custom_ops::GridSample3DInferBackShape)); | ||
|
|
||
| #endif |
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