diff options
Diffstat (limited to 'utils/GraphUtils.h')
| -rw-r--r-- | utils/GraphUtils.h | 155 |
1 files changed, 81 insertions, 74 deletions
diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h index d6bae3ea3f..b48300bd01 100644 --- a/utils/GraphUtils.h +++ b/utils/GraphUtils.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2021 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -66,7 +66,7 @@ public: * @param[in] bgr Boolean specifying if the preprocessing should assume BGR format * @param[in] scale Scale value */ - CaffePreproccessor(std::array<float, 3> mean = std::array<float, 3> { { 0, 0, 0 } }, bool bgr = true, float scale = 1.f); + CaffePreproccessor(std::array<float, 3> mean = std::array<float, 3>{{0, 0, 0}}, bool bgr = true, float scale = 1.f); void preprocess(ITensor &tensor) override; private: @@ -74,8 +74,8 @@ private: void preprocess_typed(ITensor &tensor); std::array<float, 3> _mean; - bool _bgr; - float _scale; + bool _bgr; + float _scale; }; /** TF preproccessor */ @@ -135,6 +135,7 @@ public: DummyAccessor(DummyAccessor &&) = default; // Inherited methods overriden: + bool access_tensor_data() override; bool access_tensor(ITensor &tensor) override; private: @@ -154,7 +155,11 @@ public: * @param[in] data_layout (Optional) DataLayout of the numpy tensor data. * @param[out] output_stream (Optional) Output stream */ - NumPyAccessor(std::string npy_path, TensorShape shape, DataType data_type, DataLayout data_layout = DataLayout::NCHW, std::ostream &output_stream = std::cout); + NumPyAccessor(std::string npy_path, + TensorShape shape, + DataType data_type, + DataLayout data_layout = DataLayout::NCHW, + std::ostream &output_stream = std::cout); /** Allow instances of this class to be move constructed */ NumPyAccessor(NumPyAccessor &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ @@ -352,7 +357,9 @@ public: * @param[in] imgs_tensor_shapes Network input images tensor shapes. * @param[out] output_stream (Optional) Output stream */ - DetectionOutputAccessor(const std::string &labels_path, std::vector<TensorShape> &imgs_tensor_shapes, std::ostream &output_stream = std::cout); + DetectionOutputAccessor(const std::string &labels_path, + std::vector<TensorShape> &imgs_tensor_shapes, + std::ostream &output_stream = std::cout); /** Allow instances of this class to be move constructed */ DetectionOutputAccessor(DetectionOutputAccessor &&) = default; /** Prevent instances of this class from being copied (As this class contains pointers) */ @@ -421,7 +428,7 @@ public: private: template <typename T, typename D> - void fill(ITensor &tensor, D &&distribution); + void fill(ITensor &tensor, D &&distribution); PixelValue _lower; PixelValue _upper; std::random_device::result_type _seed; @@ -457,9 +464,10 @@ private: * * @return A ramdom accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_random_accessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) +inline std::unique_ptr<graph::ITensorAccessor> +get_random_accessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) { - return arm_compute::support::cpp14::make_unique<RandomAccessor>(lower, upper, seed); + return std::make_unique<RandomAccessor>(lower, upper, seed); } /** Generates appropriate weights accessor according to the specified path @@ -472,17 +480,16 @@ inline std::unique_ptr<graph::ITensorAccessor> get_random_accessor(PixelValue lo * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_weights_accessor(const std::string &path, - const std::string &data_file, - DataLayout file_layout = DataLayout::NCHW) +inline std::unique_ptr<graph::ITensorAccessor> +get_weights_accessor(const std::string &path, const std::string &data_file, DataLayout file_layout = DataLayout::NCHW) { - if(path.empty()) + if (path.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(); + return std::make_unique<DummyAccessor>(); } else { - return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(path + data_file, file_layout); + return std::make_unique<NumPyBinLoader>(path + data_file, file_layout); } } @@ -494,36 +501,34 @@ inline std::unique_ptr<graph::ITensorAccessor> get_weights_accessor(const std::s * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, - std::unique_ptr<IPreprocessor> preprocessor = nullptr, - bool bgr = true) +inline std::unique_ptr<graph::ITensorAccessor> +get_input_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, + std::unique_ptr<IPreprocessor> preprocessor = nullptr, + bool bgr = true) { - if(!graph_parameters.validation_file.empty()) + if (!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationInputAccessor>(graph_parameters.validation_file, - graph_parameters.validation_path, - std::move(preprocessor), - bgr, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationInputAccessor>( + graph_parameters.validation_file, graph_parameters.validation_path, std::move(preprocessor), bgr, + graph_parameters.validation_range_start, graph_parameters.validation_range_end); } else { const std::string &image_file = graph_parameters.image; const std::string &image_file_lower = lower_string(image_file); - if(arm_compute::utility::endswith(image_file_lower, ".npy")) + if (arm_compute::utility::endswith(image_file_lower, ".npy")) { - return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(image_file, graph_parameters.data_layout); + return std::make_unique<NumPyBinLoader>(image_file, graph_parameters.data_layout); } - else if(arm_compute::utility::endswith(image_file_lower, ".jpeg") - || arm_compute::utility::endswith(image_file_lower, ".jpg") - || arm_compute::utility::endswith(image_file_lower, ".ppm")) + else if (arm_compute::utility::endswith(image_file_lower, ".jpeg") || + arm_compute::utility::endswith(image_file_lower, ".jpg") || + arm_compute::utility::endswith(image_file_lower, ".ppm")) { - return arm_compute::support::cpp14::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor)); + return std::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor)); } else { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(); + return std::make_unique<DummyAccessor>(); } } } @@ -540,26 +545,26 @@ inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const arm_comp * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, - size_t top_n = 5, - bool is_validation = false, - std::ostream &output_stream = std::cout) +inline std::unique_ptr<graph::ITensorAccessor> +get_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, + size_t top_n = 5, + bool is_validation = false, + std::ostream &output_stream = std::cout) { ARM_COMPUTE_UNUSED(is_validation); - if(!graph_parameters.validation_file.empty()) + if (!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, - output_stream, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, output_stream, + graph_parameters.validation_range_start, + graph_parameters.validation_range_end); } - else if(graph_parameters.labels.empty()) + else if (graph_parameters.labels.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream); + return std::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream); } } /** Generates appropriate output accessor according to the specified graph parameters @@ -574,26 +579,26 @@ inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_com * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, - std::vector<TensorShape> tensor_shapes, - bool is_validation = false, - std::ostream &output_stream = std::cout) +inline std::unique_ptr<graph::ITensorAccessor> +get_detection_output_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, + std::vector<TensorShape> tensor_shapes, + bool is_validation = false, + std::ostream &output_stream = std::cout) { ARM_COMPUTE_UNUSED(is_validation); - if(!graph_parameters.validation_file.empty()) + if (!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, - output_stream, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, output_stream, + graph_parameters.validation_range_start, + graph_parameters.validation_range_end); } - else if(graph_parameters.labels.empty()) + else if (graph_parameters.labels.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream); + return std::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream); } } /** Generates appropriate npy output accessor according to the specified npy_path @@ -608,16 +613,19 @@ inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(con * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_npy_output_accessor(const std::string &npy_path, TensorShape shape, DataType data_type, DataLayout data_layout = DataLayout::NCHW, +inline std::unique_ptr<graph::ITensorAccessor> get_npy_output_accessor(const std::string &npy_path, + TensorShape shape, + DataType data_type, + DataLayout data_layout = DataLayout::NCHW, std::ostream &output_stream = std::cout) { - if(npy_path.empty()) + if (npy_path.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<NumPyAccessor>(npy_path, shape, data_type, data_layout, output_stream); + return std::make_unique<NumPyAccessor>(npy_path, shape, data_type, data_layout, output_stream); } } @@ -630,15 +638,16 @@ inline std::unique_ptr<graph::ITensorAccessor> get_npy_output_accessor(const std * * @return An appropriate tensor accessor */ -inline std::unique_ptr<graph::ITensorAccessor> get_save_npy_output_accessor(const std::string &npy_name, const bool is_fortran = false) +inline std::unique_ptr<graph::ITensorAccessor> get_save_npy_output_accessor(const std::string &npy_name, + const bool is_fortran = false) { - if(npy_name.empty()) + if (npy_name.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<SaveNumPyAccessor>(npy_name, is_fortran); + return std::make_unique<SaveNumPyAccessor>(npy_name, is_fortran); } } @@ -650,7 +659,7 @@ inline std::unique_ptr<graph::ITensorAccessor> get_save_npy_output_accessor(cons */ inline std::unique_ptr<graph::ITensorAccessor> get_print_output_accessor(std::ostream &output_stream = std::cout) { - return arm_compute::support::cpp14::make_unique<PrintAccessor>(output_stream); + return std::make_unique<PrintAccessor>(output_stream); } /** Permutes a given tensor shape given the input and output data layout @@ -663,9 +672,11 @@ inline std::unique_ptr<graph::ITensorAccessor> get_print_output_accessor(std::os */ inline TensorShape permute_shape(TensorShape tensor_shape, DataLayout in_data_layout, DataLayout out_data_layout) { - if(in_data_layout != out_data_layout) + if (in_data_layout != out_data_layout) { - arm_compute::PermutationVector perm_vec = (in_data_layout == DataLayout::NCHW) ? arm_compute::PermutationVector(2U, 0U, 1U) : arm_compute::PermutationVector(1U, 2U, 0U); + arm_compute::PermutationVector perm_vec = (in_data_layout == DataLayout::NCHW) + ? arm_compute::PermutationVector(2U, 0U, 1U) + : arm_compute::PermutationVector(1U, 2U, 0U); arm_compute::permute(tensor_shape, perm_vec); } return tensor_shape; @@ -673,21 +684,17 @@ inline TensorShape permute_shape(TensorShape tensor_shape, DataLayout in_data_la /** Utility function to return the TargetHint * - * @param[in] target Integer value which expresses the selected target. Must be 0 for NEON or 1 for OpenCL or 2 (OpenCL with Tuner) + * @param[in] target Integer value which expresses the selected target. Must be 0 for Arm® Neon™ or 1 for OpenCL or 2 (OpenCL with Tuner) * * @return the TargetHint */ inline graph::Target set_target_hint(int target) { - ARM_COMPUTE_ERROR_ON_MSG(target > 3, "Invalid target. Target must be 0 (NEON), 1 (OpenCL), 2 (OpenCL + Tuner), 3 (GLES)"); - if((target == 1 || target == 2)) + ARM_COMPUTE_ERROR_ON_MSG(target > 2, "Invalid target. Target must be 0 (NEON), 1 (OpenCL), 2 (OpenCL + Tuner)"); + if ((target == 1 || target == 2)) { return graph::Target::CL; } - else if(target == 3) - { - return graph::Target::GC; - } else { return graph::Target::NEON; |