COMPMID-344 Updated doxygen
Change-Id: I32f7b84daa560e460b77216add529c8fa8b327ae
diff --git a/tests/TensorLibrary.cpp b/tests/TensorLibrary.cpp
new file mode 100644
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--- /dev/null
+++ b/tests/TensorLibrary.cpp
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+/*
+ * Copyright (c) 2017 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.
+ */
+#include "TensorLibrary.h"
+
+#include "TypePrinter.h"
+#include "UserConfiguration.h"
+#include "Utils.h"
+
+#include "arm_compute/core/ITensor.h"
+
+#include <cctype>
+#include <fstream>
+#include <limits>
+#include <map>
+#include <mutex>
+#include <sstream>
+#include <stdexcept>
+#include <tuple>
+#include <unordered_map>
+#include <utility>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace
+{
+void convert_rgb_to_u8(const RawTensor &src, RawTensor &dst)
+{
+ const size_t min_size = std::min(src.size(), dst.size());
+
+ for(size_t i = 0, j = 0; i < min_size; i += 3, ++j)
+ {
+ dst.data()[j] = 0.2126f * src.data()[i + 0] + 0.7152f * src.data()[i + 1] + 0.0722f * src.data()[i + 2];
+ }
+}
+
+void convert_rgb_to_u16(const RawTensor &src, RawTensor &dst)
+{
+ const size_t min_size = std::min(src.size(), dst.size());
+
+ for(size_t i = 0, j = 0; i < min_size; i += 3, ++j)
+ {
+ reinterpret_cast<uint16_t *>(dst.data())[j] = 0.2126f * src.data()[i + 0] + 0.7152f * src.data()[i + 1] + 0.0722f * src.data()[i + 2];
+ }
+}
+
+void convert_rgb_to_s16(const RawTensor &src, RawTensor &dst)
+{
+ const size_t min_size = std::min(src.size(), dst.size());
+
+ for(size_t i = 0, j = 0; i < min_size; i += 3, ++j)
+ {
+ reinterpret_cast<int16_t *>(dst.data())[j] = 0.2126f * src.data()[i + 0] + 0.7152f * src.data()[i + 1] + 0.0722f * src.data()[i + 2];
+ }
+}
+
+void extract_r_from_rgb(const RawTensor &src, RawTensor &dst)
+{
+ const size_t min_size = std::min(src.size(), dst.size());
+
+ for(size_t i = 0, j = 0; i < min_size; i += 3, ++j)
+ {
+ dst.data()[j] = src.data()[i];
+ }
+}
+
+void extract_g_from_rgb(const RawTensor &src, RawTensor &dst)
+{
+ const size_t min_size = std::min(src.size(), dst.size());
+
+ for(size_t i = 1, j = 0; i < min_size; i += 3, ++j)
+ {
+ dst.data()[j] = src.data()[i];
+ }
+}
+
+void discard_comments(std::ifstream &fs)
+{
+ while(fs.peek() == '#')
+ {
+ fs.ignore(std::numeric_limits<std::streamsize>::max(), '\n');
+ }
+}
+
+void discard_comments_and_spaces(std::ifstream &fs)
+{
+ while(true)
+ {
+ discard_comments(fs);
+
+ if(isspace(fs.peek()) == 0)
+ {
+ break;
+ }
+
+ fs.ignore(1);
+ }
+}
+
+std::tuple<unsigned int, unsigned int, int> parse_ppm_header(std::ifstream &fs)
+{
+ // Check the PPM magic number is valid
+ std::array<char, 2> magic_number{ { 0 } };
+ fs >> magic_number[0] >> magic_number[1];
+
+ if(magic_number[0] != 'P' || magic_number[1] != '6')
+ {
+ throw std::runtime_error("Only raw PPM format is suported");
+ }
+
+ discard_comments_and_spaces(fs);
+
+ unsigned int width = 0;
+ fs >> width;
+
+ discard_comments_and_spaces(fs);
+
+ unsigned int height = 0;
+ fs >> height;
+
+ discard_comments_and_spaces(fs);
+
+ int max_value = 0;
+ fs >> max_value;
+
+ if(!fs.good())
+ {
+ throw std::runtime_error("Cannot read image dimensions");
+ }
+
+ if(max_value != 255)
+ {
+ throw std::runtime_error("RawTensor doesn't have 8-bit values");
+ }
+
+ discard_comments(fs);
+
+ if(isspace(fs.peek()) == 0)
+ {
+ throw std::runtime_error("Invalid PPM header");
+ }
+
+ fs.ignore(1);
+
+ return std::make_tuple(width, height, max_value);
+}
+
+RawTensor load_ppm(const std::string &path)
+{
+ std::ifstream file(path, std::ios::in | std::ios::binary);
+
+ if(!file.good())
+ {
+ throw std::runtime_error("Could not load PPM image: " + path);
+ }
+
+ unsigned int width = 0;
+ unsigned int height = 0;
+
+ std::tie(width, height, std::ignore) = parse_ppm_header(file);
+
+ RawTensor raw(TensorShape(width, height), Format::RGB888);
+
+ // Check if the file is large enough to fill the image
+ const size_t current_position = file.tellg();
+ file.seekg(0, std::ios_base::end);
+ const size_t end_position = file.tellg();
+ file.seekg(current_position, std::ios_base::beg);
+
+ if((end_position - current_position) < raw.size())
+ {
+ throw std::runtime_error("Not enough data in file");
+ }
+
+ file.read(reinterpret_cast<std::fstream::char_type *>(raw.data()), raw.size());
+
+ if(!file.good())
+ {
+ throw std::runtime_error("Failure while reading image buffer");
+ }
+
+ return raw;
+}
+} // namespace
+
+TensorLibrary::TensorLibrary(std::string path)
+ : _library_path(std::move(path)), _seed{ std::random_device()() }
+{
+}
+
+TensorLibrary::TensorLibrary(std::string path, std::random_device::result_type seed)
+ : _library_path(std::move(path)), _seed{ seed }
+{
+}
+
+std::random_device::result_type TensorLibrary::seed() const
+{
+ return _seed;
+}
+
+void TensorLibrary::fill(RawTensor &raw, const std::string &name, Format format) const
+{
+ //FIXME: Should be done by swapping cached buffers
+ const RawTensor &src = get(name, format);
+ std::copy_n(src.data(), raw.size(), raw.data());
+}
+
+void TensorLibrary::fill(RawTensor &raw, const std::string &name, Channel channel) const
+{
+ fill(raw, name, get_format_for_channel(channel), channel);
+}
+
+void TensorLibrary::fill(RawTensor &raw, const std::string &name, Format format, Channel channel) const
+{
+ const RawTensor &src = get(name, format, channel);
+ std::copy_n(src.data(), raw.size(), raw.data());
+}
+
+const TensorLibrary::Loader &TensorLibrary::get_loader(const std::string &extension) const
+{
+ static std::unordered_map<std::string, Loader> loaders =
+ {
+ { "ppm", load_ppm }
+ };
+
+ const auto it = loaders.find(extension);
+
+ if(it != loaders.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ throw std::invalid_argument("Cannot load image with extension '" + extension + "'");
+ }
+}
+
+const TensorLibrary::Converter &TensorLibrary::get_converter(Format src, Format dst) const
+{
+ static std::map<std::pair<Format, Format>, Converter> converters =
+ {
+ { std::make_pair(Format::RGB888, Format::U8), convert_rgb_to_u8 },
+ { std::make_pair(Format::RGB888, Format::U16), convert_rgb_to_u16 },
+ { std::make_pair(Format::RGB888, Format::S16), convert_rgb_to_s16 }
+ };
+
+ const auto it = converters.find(std::make_pair(src, dst));
+
+ if(it != converters.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ std::stringstream msg;
+ msg << "Cannot convert from format '" << src << "' to format '" << dst << "'\n";
+ throw std::invalid_argument(msg.str());
+ }
+}
+
+const TensorLibrary::Converter &TensorLibrary::get_converter(DataType src, Format dst) const
+{
+ static std::map<std::pair<DataType, Format>, Converter> converters = {};
+
+ const auto it = converters.find(std::make_pair(src, dst));
+
+ if(it != converters.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ std::stringstream msg;
+ msg << "Cannot convert from data type '" << src << "' to format '" << dst << "'\n";
+ throw std::invalid_argument(msg.str());
+ }
+}
+
+const TensorLibrary::Converter &TensorLibrary::get_converter(DataType src, DataType dst) const
+{
+ static std::map<std::pair<DataType, DataType>, Converter> converters = {};
+
+ const auto it = converters.find(std::make_pair(src, dst));
+
+ if(it != converters.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ std::stringstream msg;
+ msg << "Cannot convert from data type '" << src << "' to data type '" << dst << "'\n";
+ throw std::invalid_argument(msg.str());
+ }
+}
+
+const TensorLibrary::Converter &TensorLibrary::get_converter(Format src, DataType dst) const
+{
+ static std::map<std::pair<Format, DataType>, Converter> converters = {};
+
+ const auto it = converters.find(std::make_pair(src, dst));
+
+ if(it != converters.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ std::stringstream msg;
+ msg << "Cannot convert from format '" << src << "' to data type '" << dst << "'\n";
+ throw std::invalid_argument(msg.str());
+ }
+}
+
+const TensorLibrary::Extractor &TensorLibrary::get_extractor(Format format, Channel channel) const
+{
+ static std::map<std::pair<Format, Channel>, Extractor> extractors =
+ {
+ { std::make_pair(Format::RGB888, Channel::R), extract_r_from_rgb },
+ { std::make_pair(Format::RGB888, Channel::G), extract_g_from_rgb }
+ };
+
+ const auto it = extractors.find(std::make_pair(format, channel));
+
+ if(it != extractors.end())
+ {
+ return it->second;
+ }
+ else
+ {
+ std::stringstream msg;
+ msg << "Cannot extract channel '" << channel << "' from format '" << format << "'\n";
+ throw std::invalid_argument(msg.str());
+ }
+}
+
+RawTensor TensorLibrary::load_image(const std::string &name) const
+{
+#ifdef _WIN32
+ const std::string image_path = ("\\images\\");
+#else
+ const std::string image_path = ("/images/");
+#endif
+
+ const std::string path = _library_path + image_path + name;
+ const std::string extension = path.substr(path.find_last_of('.') + 1);
+ return (*get_loader(extension))(path);
+}
+
+const RawTensor &TensorLibrary::find_or_create_raw_tensor(const std::string &name, Format format) const
+{
+ std::lock_guard<std::mutex> guard(_format_lock);
+
+ const RawTensor *ptr = _cache.find(std::make_tuple(name, format));
+
+ if(ptr != nullptr)
+ {
+ return *ptr;
+ }
+
+ RawTensor raw = load_image(name);
+
+ if(raw.format() != format)
+ {
+ //FIXME: Remove unnecessary copy
+ RawTensor dst(raw.shape(), format);
+ (*get_converter(raw.format(), format))(raw, dst);
+ raw = std::move(dst);
+ }
+
+ return _cache.add(std::make_tuple(name, format), std::move(raw));
+}
+
+const RawTensor &TensorLibrary::find_or_create_raw_tensor(const std::string &name, Format format, Channel channel) const
+{
+ std::lock_guard<std::mutex> guard(_channel_lock);
+
+ const RawTensor *ptr = _cache.find(std::make_tuple(name, format, channel));
+
+ if(ptr != nullptr)
+ {
+ return *ptr;
+ }
+
+ const RawTensor &src = get(name, format);
+ //FIXME: Need to change shape to match channel
+ RawTensor dst(src.shape(), get_channel_format(channel));
+
+ (*get_extractor(format, channel))(src, dst);
+
+ return _cache.add(std::make_tuple(name, format, channel), std::move(dst));
+}
+
+RawTensor TensorLibrary::get(const TensorShape &shape, DataType data_type, int num_channels, int fixed_point_position)
+{
+ return RawTensor(shape, data_type, num_channels, fixed_point_position);
+}
+
+RawTensor TensorLibrary::get(const TensorShape &shape, Format format)
+{
+ return RawTensor(shape, format);
+}
+
+const RawTensor &TensorLibrary::get(const std::string &name) const
+{
+ //FIXME: Format should be derived from the image name. Not be fixed to RGB.
+ return find_or_create_raw_tensor(name, Format::RGB888);
+}
+
+RawTensor TensorLibrary::get(const std::string &name)
+{
+ //FIXME: Format should be derived from the image name. Not be fixed to RGB.
+ return RawTensor(find_or_create_raw_tensor(name, Format::RGB888));
+}
+
+RawTensor TensorLibrary::get(const std::string &name, DataType data_type, int num_channels) const
+{
+ const RawTensor &raw = get(name);
+
+ return RawTensor(raw.shape(), data_type, num_channels);
+}
+
+const RawTensor &TensorLibrary::get(const std::string &name, Format format) const
+{
+ return find_or_create_raw_tensor(name, format);
+}
+
+RawTensor TensorLibrary::get(const std::string &name, Format format)
+{
+ return RawTensor(find_or_create_raw_tensor(name, format));
+}
+
+const RawTensor &TensorLibrary::get(const std::string &name, Channel channel) const
+{
+ return get(name, get_format_for_channel(channel), channel);
+}
+
+RawTensor TensorLibrary::get(const std::string &name, Channel channel)
+{
+ return RawTensor(get(name, get_format_for_channel(channel), channel));
+}
+
+const RawTensor &TensorLibrary::get(const std::string &name, Format format, Channel channel) const
+{
+ return find_or_create_raw_tensor(name, format, channel);
+}
+
+RawTensor TensorLibrary::get(const std::string &name, Format format, Channel channel)
+{
+ return RawTensor(find_or_create_raw_tensor(name, format, channel));
+}
+} // namespace test
+} // namespace arm_compute