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+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+// Description: Utility functions handling command line arguments and network input info for DLA's runtime.
+//              Loosely based off OpenVino's benchmark_app/utils.hpp
+//              [openvinotoolkit/openvino › samples/cpp/benchmark_app/utils.hpp]
+//              Future OpenVino uplifts should refer to the file listed above.
+
+#pragma once
+
+#include <map>
+#include <string>
+#include <vector>
+
+#include "dla_runtime_log.h"
+
+#define MULTIGRAPH_SEP ',' /* seperator used in argument line when multigraph activated */
+
+// Constants
+constexpr size_t BYTE_TO_MEGABYTE = 1024 * 1024;
+constexpr size_t MAX_COUT_WITHOUT_VERBOSE = 20;  // How many couts can be printed w/o VERBOSE=1
+
+typedef std::chrono::high_resolution_clock Time;
+typedef std::chrono::nanoseconds ns;
+
+#ifdef USE_OPENCV
+// This is the full list of image extensions supported by the opencv reader:
+// "bmp", "dib", "jpeg", "jpg", "jpe",
+// "jp2", "png", "pbm", "pgm", "ppm",
+// "sr", "ras", "tiff", "tif"
+// However, the ones in the list below are already
+// tested using the synthetic graphs infrastructure.
+// Only jpeg, jpg, jpe extensions of very high quality
+// and with subsampling disabled were tested.
+// TODO(meldafra): Check why the remaining extensions are not passing and fix them
+static const std::vector<std::string> supported_image_extensions = {
+    "bmp", "png", "pbm", "pgm", "ppm", "jpeg", "jpg", "jpe"};
+
+#else
+static const std::vector<std::string> supported_image_extensions = {"bmp"};
+#endif
+static const std::vector<std::string> supported_binary_extensions = {"bin"};
+static const std::vector<std::string> supported_video_extensions = {"mp4", "gif"};
+
+/**
+ * @brief Namespace dla_benchmark contains utility functions for working with network inputs.
+ */
+namespace dla_benchmark {
+struct InputInfo {
+  ov::element::Type type;
+  ov::PartialShape partial_shape;
+  ov::Shape data_shape;
+  ov::Layout layout;
+  std::vector<float> scale_values;
+  std::vector<float> mean_values;
+  bool IsImage() const;
+  bool IsImageInfo() const;
+  bool IsVideo() const;
+  size_t GetWidth() const;
+  size_t GetHeight() const;
+  size_t GetChannels() const;
+  size_t GetBatch() const;
+  size_t GetDepth() const;
+};
+
+struct OutputInfo {
+  std::string name;
+  ov::Shape shape;
+};
+
+using InputsInfo = std::map<std::string, InputInfo>;
+using OutputsInfoVec = std::vector<OutputInfo>;
+using PartialShapes = std::map<std::string, ngraph::PartialShape>;
+
+struct InferenceMetaData {
+  std::vector<std::string> input_files;  // Input files used inferencing
+  std::string groundtruth_loc;  // The directory that contains the groundtruth files
+  unsigned int batch_size;  // The batch size used in the inference
+  unsigned int niter;  // The number of iterations set by -niter in dla_benchmark
+  unsigned int nireq;  // The number of inference requests set by -nireq in dla_benchmark
+  dla_benchmark::InputsInfo model_input_info;  // the metadata of the model input
+  dla_benchmark::OutputsInfoVec model_output_info;  // the metadata of the model output
+};
+}  // namespace dla_benchmark
+
+/**
+ * @brief Parses number of streams for each device from a string argument.
+ *
+ * @param devices vector of supported DLA devices, ie FPGA, CPU
+ * @param values_string string arg of the format: <device1>:<value1>,<device2>:<value2>
+ * @return A map of device : number of streams
+ */
+std::map<std::string, uint32_t> ParseNStreamsValuePerDevice(const std::vector<std::string>& devices,
+                                                            const std::string& values_string);
+/**
+ * @brief Splits a string into substrings using a specified delimiter.
+ *
+ * @param s The input string to be split.
+ * @param delim The delimiter character used to separate the substrings.
+ * @return A vector of strings containing the substrings from the input string.
+ */
+std::vector<std::string> split(const std::string& s, char delim);
+
+/**
+ * @brief Splits a string of floats into floats using a specified delimiter.
+ *
+ * @param s The input string to be split.
+ * @param delim The delimiter character used to separate the floats.
+ * @return A vector of floats containing the floats from the input string.
+ */
+std::vector<float> SplitFloat(const std::string& s, char delim);
+
+// To enable multigraph operations to all CNNNetworks, inputs are mutable
+template <typename T, typename S, typename Functor>
+inline std::vector<T> VectorMap(std::vector<S>& inputs, Functor fn) {
+  std::vector<T> results;
+  for (auto& input : inputs) results.push_back(fn(input));
+  return results;
+}
+
+// Supports temporary object or constant expression
+template <typename T, typename S, typename Functor>
+inline std::vector<T> VectorMap(const std::vector<S>& inputs, Functor fn) {
+  std::vector<T> results;
+  for (auto& input : inputs) results.push_back(fn(input));
+  return results;
+}
+
+template <typename T, typename S, typename Functor>
+inline std::vector<T> vectorMapWithIndex(const std::vector<S>& inputs, Functor fn) {
+  std::vector<T> results;
+  uint32_t index = 0;
+  for (auto& input : inputs) results.push_back(fn(input, index++));
+  return results;
+}
+
+/**
+ * @brief Splits command-line input arguments containing multiple image file paths
+ *        into separate vectors based on a specified separator.
+ * Modified from parseInputFilesArguments() in [openvinotoolkit/openvino ›
+ * inference-engine/samples/common/utils/src/args_helper.cpp]
+ *
+ * @param net_size The number of networks (multigraph functionality).
+ * @return A vector of vectors, where each inner vector contains image file paths
+ *         corresponding to a specific network graph.
+ */
+std::vector<std::vector<std::string>> SplitMultiInputFilesArguments(size_t net_size);
+
+/**
+ * @brief Returns the stem of a file path.
+ *
+ * The stem is the base name of the file without its extension. This function
+ * takes a file path as input and extracts the stem, which is the part of the
+ * file name before the last period ('.') character.
+ *
+ * @param path The input file path.
+ * @return The stem of the file, excluding the extension.
+ */
+std::string GetStem(std::string path);
+
+/**
+ * @brief Extracts the file extension from a given file name.
+ *
+ * @param name The file name from which to extract the extension.
+ * @return The file extension as a string, or an empty string if no extension is found.
+ */
+std::string GetExtension(const std::string& path);
+
+/**
+ * @brief Parses a list of devices from a string
+ *
+ * @param device_string The input string to be split. The delimiter is ':'
+ * @return A vector of strings containing the devices
+ */
+std::vector<std::string> ParseDevices(const std::string& device_string);
+
+/**
+ * @brief Gets information about a network's inputs.
+ *
+ * Reads all input nodes from a network, determines tensor layout, shapes, precision, etc.
+ * Saves into dla::benchmark::InputsInfo which maps each input info struct to an input name.
+ *
+ * @param batch_size Network batch size from the user via the batch size flag
+ * @param input_info Vector of input nodes. Obtained from ov::Model.inputs() or ov::CompiledModel.inputs()
+ * @param reshape_required boolean flag indicating that the model needs to be reshaped according to the batch size flag
+ * @param is_binary_data User flag indicating that the data is binary data and not image data
+ * @param mean_string CLI arg specifying image mean value. Example: input[255,255,255]. (Optional)
+ * @param scale_string CLI arg specifying image scale value. Example: input[255,255,255]. (Optional)
+ * @return dla::benchmark::InputsInfo which is a map of input names and its respective input information
+ */
+dla_benchmark::InputsInfo GetInputsInfo(const size_t batch_size,
+                                        const std::vector<ov::Output<const ov::Node>>& input_info,
+                                        bool& reshape_required,
+                                        const bool is_binary_data,
+                                        const std::string& mean_string,
+                                        const std::string& scale_string);
+
+/**
+ * @brief Gets information about a network's inputs.
+ *
+ * Reads all input nodes from a network, determines tensor layout, shapes, precision, etc.
+ * Saves into dla::benchmark::InputsInfo which maps each input info struct to an input name.
+ * Used in AOT flow where reshaping is not required (Handled by compiler)
+ *
+ * @param batch_size Network batch size from the user via the batch size flag
+ * @param input_info Vector of input nodes. Obtained from ov::Model.inputs() or ov::CompiledModel.inputs()
+ * @param is_binary_data User flag indicating that the data is binary data and not image data
+ * @return dla::benchmark::InputsInfo which is a map of input names and its respective input information
+ */
+dla_benchmark::InputsInfo GetInputsInfo(const size_t batch_size,
+                                        const std::vector<ov::Output<const ov::Node>>& input_info,
+                                        const bool isBinaryData);
+
+/**
+ * @brief Filters a list of file paths by specified file extensions (case insensitive).
+ *
+ * @param file_paths A vector of file paths to be filtered.
+ * @param extensions A vector of file extensions to filter by.
+ * @return A vector of filtered file paths that match the specified extensions.
+ */
+std::vector<std::string> FilterFilesByExtensions(const std::vector<std::string>& file_paths,
+                                                 const std::vector<std::string>& extensions);
+
+// Helper function to dump result.txt with tensor indicies
+void DumpResultTxtFile(const ov::Tensor& output_tensor,
+                       const ov::Output<const ov::Node>& output_node,
+                       const unsigned int output_size,
+                       std::ofstream& result_file);
+
+// Helper function to dump the output tensor as binaries in result.bin
+void DumpResultBinFile(const ov::Tensor& output_tensor,
+                       std::ofstream& result_file);
+
+// Helper function to dump the inference metadata into result_meta.json
+void DumpResultMetaJSONFile(const dla_benchmark::InferenceMetaData& metadata,
+                            std::ofstream& result_file);
+
+/**
+ * @brief Gets the appriopriate DLA supported tensor layout from a node.
+ *
+ * @param node Node to determine the tensor layout. Obtained from ov::Model.inputs()/outputs()
+ *             or ov::CompiledModel.inputs()/outputs()
+ * @param allow_partial_defined Whether to allow partial defined layout. When set true, DLA tolerates
+ *             dumping custom layouts e.g., when the rank of shape is 3. The layout will have ? in
+ *             all dimensions. e.g., [???].
+ *             This param should ONLY be used when dumping graph output of irregular layout.
+ * @return OpenVino's tensor layout object.
+ */
+ov::Layout GetTensorLayout(const ov::Output<ov::Node>& node, const bool allow_partial_defined = false);