| /* |
| * Copyright (c) 2017-2019 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #ifndef __ARM_COMPUTE_UTILS_GRAPH_UTILS_H__ |
| #define __ARM_COMPUTE_UTILS_GRAPH_UTILS_H__ |
| |
| #include "arm_compute/core/PixelValue.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/utils/misc/Utility.h" |
| #include "arm_compute/graph/Graph.h" |
| #include "arm_compute/graph/ITensorAccessor.h" |
| #include "arm_compute/graph/Types.h" |
| #include "arm_compute/runtime/Tensor.h" |
| |
| #include "utils/CommonGraphOptions.h" |
| |
| #include <array> |
| #include <random> |
| #include <string> |
| #include <vector> |
| |
| namespace arm_compute |
| { |
| namespace graph_utils |
| { |
| /** Preprocessor interface **/ |
| class IPreprocessor |
| { |
| public: |
| /** Default destructor. */ |
| virtual ~IPreprocessor() = default; |
| /** Preprocess the given tensor. |
| * |
| * @param[in] tensor Tensor to preprocess. |
| */ |
| virtual void preprocess(ITensor &tensor) = 0; |
| }; |
| |
| /** Caffe preproccessor */ |
| class CaffePreproccessor : public IPreprocessor |
| { |
| public: |
| /** Default Constructor |
| * |
| * @param[in] mean Mean array in RGB ordering |
| * @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); |
| void preprocess(ITensor &tensor) override; |
| |
| private: |
| template <typename T> |
| void preprocess_typed(ITensor &tensor); |
| |
| std::array<float, 3> _mean; |
| bool _bgr; |
| float _scale; |
| }; |
| |
| /** TF preproccessor */ |
| class TFPreproccessor : public IPreprocessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] min_range Min normalization range. (Defaults to -1.f) |
| * @param[in] max_range Max normalization range. (Defaults to 1.f) |
| */ |
| TFPreproccessor(float min_range = -1.f, float max_range = 1.f); |
| |
| // Inherited overriden methods |
| void preprocess(ITensor &tensor) override; |
| |
| private: |
| template <typename T> |
| void preprocess_typed(ITensor &tensor); |
| |
| float _min_range; |
| float _max_range; |
| }; |
| |
| /** PPM writer class */ |
| class PPMWriter : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] name PPM file name |
| * @param[in] maximum Maximum elements to access |
| */ |
| PPMWriter(std::string name, unsigned int maximum = 1); |
| /** Allows instances to move constructed */ |
| PPMWriter(PPMWriter &&) = default; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| const std::string _name; |
| unsigned int _iterator; |
| unsigned int _maximum; |
| }; |
| |
| /** Dummy accessor class */ |
| class DummyAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] maximum Maximum elements to write |
| */ |
| DummyAccessor(unsigned int maximum = 1); |
| /** Allows instances to move constructed */ |
| DummyAccessor(DummyAccessor &&) = default; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| unsigned int _iterator; |
| unsigned int _maximum; |
| }; |
| |
| /** NumPy accessor class */ |
| class NumPyAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] npy_path Path to npy file. |
| * @param[in] shape Shape of the numpy tensor data. |
| * @param[in] data_type DataType of the numpy tensor data. |
| * @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); |
| /** 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) */ |
| NumPyAccessor(const NumPyAccessor &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| NumPyAccessor &operator=(const NumPyAccessor &) = delete; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| template <typename T> |
| void access_numpy_tensor(ITensor &tensor, T tolerance); |
| |
| Tensor _npy_tensor; |
| const std::string _filename; |
| std::ostream &_output_stream; |
| }; |
| |
| /** SaveNumPy accessor class */ |
| class SaveNumPyAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] npy_name Npy file name. |
| * @param[in] is_fortran (Optional) If true, save tensor in fortran order. |
| */ |
| SaveNumPyAccessor(const std::string npy_name, const bool is_fortran = false); |
| /** Allow instances of this class to be move constructed */ |
| SaveNumPyAccessor(SaveNumPyAccessor &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| SaveNumPyAccessor(const SaveNumPyAccessor &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| SaveNumPyAccessor &operator=(const SaveNumPyAccessor &) = delete; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| const std::string _npy_name; |
| const bool _is_fortran; |
| }; |
| |
| /** Print accessor class |
| * @note The print accessor will print only when asserts are enabled. |
| * */ |
| class PrintAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[out] output_stream (Optional) Output stream |
| * @param[in] io_fmt (Optional) Format information |
| */ |
| PrintAccessor(std::ostream &output_stream = std::cout, IOFormatInfo io_fmt = IOFormatInfo()); |
| /** Allow instances of this class to be move constructed */ |
| PrintAccessor(PrintAccessor &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| PrintAccessor(const PrintAccessor &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| PrintAccessor &operator=(const PrintAccessor &) = delete; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| std::ostream &_output_stream; |
| IOFormatInfo _io_fmt; |
| }; |
| |
| /** Image accessor class */ |
| class ImageAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] filename Image file |
| * @param[in] bgr (Optional) Fill the first plane with blue channel (default = false - RGB format) |
| * @param[in] preprocessor (Optional) Image pre-processing object |
| */ |
| ImageAccessor(std::string filename, bool bgr = true, std::unique_ptr<IPreprocessor> preprocessor = nullptr); |
| /** Allow instances of this class to be move constructed */ |
| ImageAccessor(ImageAccessor &&) = default; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| bool _already_loaded; |
| const std::string _filename; |
| const bool _bgr; |
| std::unique_ptr<IPreprocessor> _preprocessor; |
| }; |
| |
| /** Input Accessor used for network validation */ |
| class ValidationInputAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] image_list File containing all the images to validate |
| * @param[in] images_path Path to images. |
| * @param[in] bgr (Optional) Fill the first plane with blue channel (default = false - RGB format) |
| * @param[in] preprocessor (Optional) Image pre-processing object (default = nullptr) |
| * @param[in] start (Optional) Start range |
| * @param[in] end (Optional) End range |
| * @param[out] output_stream (Optional) Output stream |
| * |
| * @note Range is defined as [start, end] |
| */ |
| ValidationInputAccessor(const std::string &image_list, |
| std::string images_path, |
| std::unique_ptr<IPreprocessor> preprocessor = nullptr, |
| bool bgr = true, |
| unsigned int start = 0, |
| unsigned int end = 0, |
| std::ostream &output_stream = std::cout); |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| std::string _path; |
| std::vector<std::string> _images; |
| std::unique_ptr<IPreprocessor> _preprocessor; |
| bool _bgr; |
| size_t _offset; |
| std::ostream &_output_stream; |
| }; |
| |
| /** Output Accessor used for network validation */ |
| class ValidationOutputAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Default Constructor |
| * |
| * @param[in] image_list File containing all the images and labels results |
| * @param[out] output_stream (Optional) Output stream (Defaults to the standard output stream) |
| * @param[in] start (Optional) Start range |
| * @param[in] end (Optional) End range |
| * |
| * @note Range is defined as [start, end] |
| */ |
| ValidationOutputAccessor(const std::string &image_list, |
| std::ostream &output_stream = std::cout, |
| unsigned int start = 0, |
| unsigned int end = 0); |
| /** Reset accessor state */ |
| void reset(); |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| /** Access predictions of the tensor |
| * |
| * @tparam T Tensor elements type |
| * |
| * @param[in] tensor Tensor to read the predictions from |
| */ |
| template <typename T> |
| std::vector<size_t> access_predictions_tensor(ITensor &tensor); |
| /** Aggregates the results of a sample |
| * |
| * @param[in] res Vector containing the results of a graph |
| * @param[in,out] positive_samples Positive samples to be updated |
| * @param[in] top_n Top n accuracy to measure |
| * @param[in] correct_label Correct label of the current sample |
| */ |
| void aggregate_sample(const std::vector<size_t> &res, size_t &positive_samples, size_t top_n, size_t correct_label); |
| /** Reports top N accuracy |
| * |
| * @param[in] top_n Top N accuracy that is being reported |
| * @param[in] total_samples Total number of samples |
| * @param[in] positive_samples Positive samples |
| */ |
| void report_top_n(size_t top_n, size_t total_samples, size_t positive_samples); |
| |
| private: |
| std::vector<int> _results; |
| std::ostream &_output_stream; |
| size_t _offset; |
| size_t _positive_samples_top1; |
| size_t _positive_samples_top5; |
| }; |
| |
| /** Detection output accessor class */ |
| class DetectionOutputAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] labels_path Path to labels text file. |
| * @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); |
| /** 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) */ |
| DetectionOutputAccessor(const DetectionOutputAccessor &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| DetectionOutputAccessor &operator=(const DetectionOutputAccessor &) = delete; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| template <typename T> |
| void access_predictions_tensor(ITensor &tensor); |
| |
| std::vector<std::string> _labels; |
| std::vector<TensorShape> _tensor_shapes; |
| std::ostream &_output_stream; |
| }; |
| |
| /** Result accessor class */ |
| class TopNPredictionsAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] labels_path Path to labels text file. |
| * @param[in] top_n (Optional) Number of output classes to print |
| * @param[out] output_stream (Optional) Output stream |
| */ |
| TopNPredictionsAccessor(const std::string &labels_path, size_t top_n = 5, std::ostream &output_stream = std::cout); |
| /** Allow instances of this class to be move constructed */ |
| TopNPredictionsAccessor(TopNPredictionsAccessor &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| TopNPredictionsAccessor(const TopNPredictionsAccessor &) = delete; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| TopNPredictionsAccessor &operator=(const TopNPredictionsAccessor &) = delete; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| template <typename T> |
| void access_predictions_tensor(ITensor &tensor); |
| |
| std::vector<std::string> _labels; |
| std::ostream &_output_stream; |
| size_t _top_n; |
| }; |
| |
| /** Random accessor class */ |
| class RandomAccessor final : public graph::ITensorAccessor |
| { |
| public: |
| /** Constructor |
| * |
| * @param[in] lower Lower bound value. |
| * @param[in] upper Upper bound value. |
| * @param[in] seed (Optional) Seed used to initialise the random number generator. |
| */ |
| RandomAccessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0); |
| /** Allows instances to move constructed */ |
| RandomAccessor(RandomAccessor &&) = default; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| template <typename T, typename D> |
| void fill(ITensor &tensor, D &&distribution); |
| PixelValue _lower; |
| PixelValue _upper; |
| std::random_device::result_type _seed; |
| }; |
| |
| /** Numpy Binary loader class*/ |
| class NumPyBinLoader final : public graph::ITensorAccessor |
| { |
| public: |
| /** Default Constructor |
| * |
| * @param[in] filename Binary file name |
| * @param[in] file_layout (Optional) Layout of the numpy tensor data. Defaults to NCHW |
| */ |
| NumPyBinLoader(std::string filename, DataLayout file_layout = DataLayout::NCHW); |
| /** Allows instances to move constructed */ |
| NumPyBinLoader(NumPyBinLoader &&) = default; |
| |
| // Inherited methods overriden: |
| bool access_tensor(ITensor &tensor) override; |
| |
| private: |
| bool _already_loaded; |
| const std::string _filename; |
| const DataLayout _file_layout; |
| }; |
| |
| /** Generates appropriate random accessor |
| * |
| * @param[in] lower Lower random values bound |
| * @param[in] upper Upper random values bound |
| * @param[in] seed Random generator seed |
| * |
| * @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) |
| { |
| return arm_compute::support::cpp14::make_unique<RandomAccessor>(lower, upper, seed); |
| } |
| |
| /** Generates appropriate weights accessor according to the specified path |
| * |
| * @note If path is empty will generate a DummyAccessor else will generate a NumPyBinLoader |
| * |
| * @param[in] path Path to the data files |
| * @param[in] data_file Relative path to the data files from path |
| * @param[in] file_layout (Optional) Layout of file. Defaults to NCHW |
| * |
| * @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) |
| { |
| if(path.empty()) |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(path + data_file, file_layout); |
| } |
| } |
| |
| /** Generates appropriate input accessor according to the specified graph parameters |
| * |
| * @param[in] graph_parameters Graph parameters |
| * @param[in] preprocessor (Optional) Preproccessor object |
| * @param[in] bgr (Optional) Fill the first plane with blue channel (default = true) |
| * |
| * @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) |
| { |
| 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); |
| } |
| 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")) |
| { |
| return arm_compute::support::cpp14::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")) |
| { |
| return arm_compute::support::cpp14::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor)); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(); |
| } |
| } |
| } |
| |
| /** Generates appropriate output accessor according to the specified graph parameters |
| * |
| * @note If the output accessor is requested to validate the graph then ValidationOutputAccessor is generated |
| * else if output_accessor_file is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor |
| * |
| * @param[in] graph_parameters Graph parameters |
| * @param[in] top_n (Optional) Number of output classes to print (default = 5) |
| * @param[in] is_validation (Optional) Validation flag (default = false) |
| * @param[out] output_stream (Optional) Output stream (default = std::cout) |
| * |
| * @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) |
| { |
| ARM_COMPUTE_UNUSED(is_validation); |
| 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); |
| } |
| else if(graph_parameters.labels.empty()) |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream); |
| } |
| } |
| /** Generates appropriate output accessor according to the specified graph parameters |
| * |
| * @note If the output accessor is requested to validate the graph then ValidationOutputAccessor is generated |
| * else if output_accessor_file is empty will generate a DummyAccessor else will generate a TopNPredictionsAccessor |
| * |
| * @param[in] graph_parameters Graph parameters |
| * @param[in] tensor_shapes Network input images tensor shapes. |
| * @param[in] is_validation (Optional) Validation flag (default = false) |
| * @param[out] output_stream (Optional) Output stream (default = std::cout) |
| * |
| * @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) |
| { |
| ARM_COMPUTE_UNUSED(is_validation); |
| 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); |
| } |
| else if(graph_parameters.labels.empty()) |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream); |
| } |
| } |
| /** Generates appropriate npy output accessor according to the specified npy_path |
| * |
| * @note If npy_path is empty will generate a DummyAccessor else will generate a NpyAccessor |
| * |
| * @param[in] npy_path Path to npy file. |
| * @param[in] shape Shape of the numpy tensor data. |
| * @param[in] data_type DataType of the numpy tensor data. |
| * @param[in] data_layout DataLayout of the numpy tensor data. |
| * @param[out] output_stream (Optional) Output stream |
| * |
| * @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, |
| std::ostream &output_stream = std::cout) |
| { |
| if(npy_path.empty()) |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<NumPyAccessor>(npy_path, shape, data_type, data_layout, output_stream); |
| } |
| } |
| |
| /** Generates appropriate npy output accessor according to the specified npy_path |
| * |
| * @note If npy_path is empty will generate a DummyAccessor else will generate a SaveNpyAccessor |
| * |
| * @param[in] npy_name Npy filename. |
| * @param[in] is_fortran (Optional) If true, save tensor in fortran order. |
| * |
| * @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) |
| { |
| if(npy_name.empty()) |
| { |
| return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); |
| } |
| else |
| { |
| return arm_compute::support::cpp14::make_unique<SaveNumPyAccessor>(npy_name, is_fortran); |
| } |
| } |
| |
| /** Generates print tensor accessor |
| * |
| * @param[out] output_stream (Optional) Output stream |
| * |
| * @return A print tensor accessor |
| */ |
| 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); |
| } |
| |
| /** Permutes a given tensor shape given the input and output data layout |
| * |
| * @param[in] tensor_shape Tensor shape to permute |
| * @param[in] in_data_layout Input tensor shape data layout |
| * @param[in] out_data_layout Output tensor shape data layout |
| * |
| * @return Permuted tensor shape |
| */ |
| inline TensorShape permute_shape(TensorShape tensor_shape, DataLayout in_data_layout, DataLayout 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::permute(tensor_shape, perm_vec); |
| } |
| return tensor_shape; |
| } |
| |
| /** 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) |
| * |
| * @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)) |
| { |
| return graph::Target::CL; |
| } |
| else if(target == 3) |
| { |
| return graph::Target::GC; |
| } |
| else |
| { |
| return graph::Target::NEON; |
| } |
| } |
| } // namespace graph_utils |
| } // namespace arm_compute |
| |
| #endif /* __ARM_COMPUTE_UTILS_GRAPH_UTILS_H__ */ |
