第二次课程

CMakeLists.txt

@@ -4,12 +4,14 @@ project(kuiper_course)
 set(CMAKE_CXX_STANDARD 17)
 
 find_package(glog REQUIRED)
+include_directories(./include)
 
 set(link_lib glog pthread gtest)
 set(link_math_lib armadillo blas lapack)
-add_executable(kuiper_course main.cpp)
 set(EXECUTABLE_OUTPUT_PATH ${PROJECT_SOURCE_DIR}/bin)
 
+add_executable(kuiper_course main.cpp)
+
 target_include_directories(kuiper_course PUBLIC /usr/include/armadillo_bits)
 target_include_directories(kuiper_course PUBLIC ${GTEST_INCLUDE_DIRS})
 target_link_libraries(kuiper_course ${link_lib} ${link_math_lib})

include/data/tensor.hpp

@@ -0,0 +1,81 @@
+//
+// Created by fss on 22-12-16.
+//
+
+#ifndef KUIPER_COURSE_INCLUDE_TENSOR_HPP_
+#define KUIPER_COURSE_INCLUDE_TENSOR_HPP_
+#include <memory>
+#include <vector>
+#include <armadillo>
+
+namespace kuiper_infer {
+
+template<typename T>
+class Tensor {
+
+};
+
+template<>
+class Tensor<uint8_t> {
+  // 待实现
+};
+
+template<>
+class Tensor<float> {
+ public:
+  explicit Tensor() = default;
+
+  explicit Tensor(uint32_t channels, uint32_t rows, uint32_t cols);
+
+  Tensor(const Tensor &tensor);
+
+  Tensor<float> &operator=(const Tensor &tensor);
+
+  uint32_t rows() const;
+
+  uint32_t cols() const;
+
+  uint32_t channels() const;
+
+  uint32_t size() const;
+
+  void set_data(const arma::fcube &data);
+
+  bool empty() const;
+
+  float index(uint32_t offset) const;
+
+  std::vector<uint32_t> shapes() const;
+
+  arma::fcube &data();
+
+  const arma::fcube &data() const;
+
+  arma::fmat &at(uint32_t channel);
+
+  const arma::fmat &at(uint32_t channel) const;
+
+  float at(uint32_t channel, uint32_t row, uint32_t col) const;
+
+  float &at(uint32_t channel, uint32_t row, uint32_t col);
+
+  void Padding(const std::vector<uint32_t> &pads, float padding_value);
+
+  void Fill(float value);
+
+  void Fill(const std::vector<float> &values);
+
+  void Ones();
+
+  void Rand();
+
+  void Show();
+
+  void Flatten();
+
+ private:
+  std::vector<uint32_t> raw_shapes_;
+  arma::fcube data_;
+};
+}
+#endif //KUIPER_COURSE_INCLUDE_TENSOR_HPP_

main.cpp

@@ -1,12 +1,6 @@
-#include <iostream>
-#include <armadillo>
-int main() {
-  arma::fmat in_1(32, 32, arma::fill::ones);
-  arma::fmat in_2(32, 32, arma::fill::ones);
+#include <glog/logging.h>
 
-  arma::fmat out = in_1 + in_2;
-  std::cout << "rows " << out.n_rows << "\n";
-  std::cout << "cols " << out.n_cols << "\n";
-  std::cout << "value " << out.at(0) << "\n";
+int main() {
+  LOG(INFO) << "Kuiper Infer Course";
   return 0;
 }

source/data/tensor.cpp

@@ -0,0 +1,171 @@
+//
+// Created by fss on 22-12-16.
+//
+#include "data/tensor.hpp"
+#include <glog/logging.h>
+#include <memory>
+
+namespace kuiper_infer {
+
+Tensor<float>::Tensor(uint32_t channels, uint32_t rows, uint32_t cols) {
+  data_ = arma::fcube(rows, cols, channels);
+}
+
+Tensor<float>::Tensor(const Tensor &tensor) {
+  this->data_ = tensor.data_;
+  this->raw_shapes_ = tensor.raw_shapes_;
+}
+
+Tensor<float> &Tensor<float>::operator=(const Tensor &tensor) {
+  if (this != &tensor) {
+    this->data_ = tensor.data_;
+    this->raw_shapes_ = tensor.raw_shapes_;
+  }
+  return *this;
+}
+
+uint32_t Tensor<float>::rows() const {
+  CHECK(!this->data_.empty());
+  return this->data_.n_rows;
+}
+
+uint32_t Tensor<float>::cols() const {
+  CHECK(!this->data_.empty());
+  return this->data_.n_cols;
+}
+
+uint32_t Tensor<float>::channels() const {
+  CHECK(!this->data_.empty());
+  return this->data_.n_slices;
+}
+
+uint32_t Tensor<float>::size() const {
+  CHECK(!this->data_.empty());
+  return this->data_.size();
+}
+
+void Tensor<float>::set_data(const arma::fcube &data) {
+  CHECK(data.n_rows == this->data_.n_rows) << data.n_rows << " != " << this->data_.n_rows;
+  CHECK(data.n_cols == this->data_.n_cols) << data.n_cols << " != " << this->data_.n_cols;
+  CHECK(data.n_slices == this->data_.n_slices) << data.n_slices << " != " << this->data_.n_slices;
+  this->data_ = data;
+}
+
+bool Tensor<float>::empty() const {
+  return this->data_.empty();
+}
+
+float Tensor<float>::index(uint32_t offset) const {
+  CHECK(offset < this->data_.size());
+  return this->data_.at(offset);
+}
+
+std::vector<uint32_t> Tensor<float>::shapes() const {
+  CHECK(!this->data_.empty());
+  return {this->channels(), this->rows(), this->cols()};
+}
+
+arma::fcube &Tensor<float>::data() {
+  return this->data_;
+}
+
+const arma::fcube &Tensor<float>::data() const {
+  return this->data_;
+}
+
+arma::fmat &Tensor<float>::at(uint32_t channel) {
+  CHECK_LT(channel, this->channels());
+  return this->data_.slice(channel);
+}
+
+const arma::fmat &Tensor<float>::at(uint32_t channel) const {
+  CHECK_LT(channel, this->channels());
+  return this->data_.slice(channel);
+}
+
+float Tensor<float>::at(uint32_t channel, uint32_t row, uint32_t col) const {
+  CHECK_LT(row, this->rows());
+  CHECK_LT(col, this->cols());
+  CHECK_LT(channel, this->channels());
+  return this->data_.at(row, col, channel);
+}
+
+float &Tensor<float>::at(uint32_t channel, uint32_t row, uint32_t col) {
+  CHECK_LT(row, this->rows());
+  CHECK_LT(col, this->cols());
+  CHECK_LT(channel, this->channels());
+  return this->data_.at(row, col, channel);
+}
+
+void Tensor<float>::Padding(const std::vector<uint32_t> &pads, float padding_value) {
+  CHECK(!this->data_.empty());
+  CHECK_EQ(pads.size(), 4);
+  uint32_t pad_rows1 = pads.at(0);  // up
+  uint32_t pad_rows2 = pads.at(1);  // bottom
+  uint32_t pad_cols1 = pads.at(2);  // left
+  uint32_t pad_cols2 = pads.at(3);  // right
+
+  //todo 请把代码补充在这里1
+
+}
+
+void Tensor<float>::Fill(float value) {
+  CHECK(!this->data_.empty());
+  this->data_.fill(value);
+}
+
+void Tensor<float>::Fill(const std::vector<float> &values) {
+  CHECK(!this->data_.empty());
+  const uint32_t total_elems = this->data_.size();
+  CHECK_EQ(values.size(), total_elems);
+
+  const uint32_t rows = this->rows();
+  const uint32_t cols = this->cols();
+  const uint32_t planes = rows * cols;
+  const uint32_t channels = this->data_.n_slices;
+
+  //todo 请把代码补充在这里2
+}
+
+void Tensor<float>::Show() {
+  for (uint32_t i = 0; i < this->channels(); ++i) {
+    LOG(INFO) << "Channel: " << i;
+    LOG(INFO) << "\n" << this->data_.slice(i);
+  }
+}
+
+void Tensor<float>::Flatten() {
+  CHECK(!this->data_.empty());
+  const uint32_t size = this->data_.size();
+  arma::fcube linear_cube(size, 1, 1);
+
+  uint32_t channel = this->channels();
+  uint32_t rows = this->rows();
+  uint32_t cols = this->cols();
+  uint32_t index = 0;
+
+  for (uint32_t c = 0; c < channel; ++c) {
+    const arma::fmat &matrix = this->data_.slice(c);
+
+    for (uint32_t r = 0; r < rows; ++r) {
+      for (uint32_t c_ = 0; c_ < cols; ++c_) {
+        linear_cube.at(index, 0, 0) = matrix.at(r, c_);
+        index += 1;
+      }
+    }
+  }
+  CHECK_EQ(index, size);
+  this->data_ = linear_cube;
+  this->raw_shapes_ = std::vector<uint32_t>{size};
+}
+
+void Tensor<float>::Rand() {
+  CHECK(!this->data_.empty());
+  this->data_.randn();
+}
+
+void Tensor<float>::Ones() {
+  CHECK(!this->data_.empty());
+  this->data_.fill(1.);
+}
+}

test/CMakeLists.txt

@@ -4,7 +4,8 @@ aux_source_directory(../test DIR_TEST)
 set(link_lib glog gtest pthread  )
 set(link_math_lib armadillo blas lapack)
 
-add_executable(test_kuiper_course ${DIR_TEST})
+aux_source_directory(../source/data DIR_DATA)
+add_executable(test_kuiper_course ${DIR_TEST} ${DIR_DATA})
 
 link_directories(/usr/local/lib/)
 target_link_libraries(test_kuiper_course ${link_lib} ${link_math_lib})

test/test_first.cpp

@@ -14,29 +14,29 @@ TEST(test_first, demo1) {
   ASSERT_EQ(in_1.size(), 32 * 32);
 }
 
-TEST(test_first, linear) {
-  arma::fmat A = "1,2,3;"
-                 "4,5,6;"
-                 "7,8,9;";
-
-  arma::fmat X = "1,1,1;"
-                 "1,1,1;"
-                 "1,1,1;";
-
-  arma::fmat bias = "1,1,1;"
-                    "1,1,1;"
-                    "1,1,1;";
-
-  arma::fmat output(3, 3);
-  //todo 在此处插入代码，完成output = AxX + bias的运算
-  // output = ?
-
-  const uint32_t cols = 3;
-  for (uint32_t c = 0; c < cols; ++c) {
-    float *col_ptr = output.colptr(c);
-    ASSERT_EQ(*(col_ptr + 0), 7);
-    ASSERT_EQ(*(col_ptr + 1), 16);
-    ASSERT_EQ(*(col_ptr + 2), 25);
-  }
-  LOG(INFO) << "\n" <<"Result Passed!";
-}
+//TEST(test_first, linear) {
+//  arma::fmat A = "1,2,3;"
+//                 "4,5,6;"
+//                 "7,8,9;";
+//
+//  arma::fmat X = "1,1,1;"
+//                 "1,1,1;"
+//                 "1,1,1;";
+//
+//  arma::fmat bias = "1,1,1;"
+//                    "1,1,1;"
+//                    "1,1,1;";
+//
+//  arma::fmat output(3, 3);
+//  //todo 在此处插入代码，完成output = AxX + bias的运算
+//  // output = ?
+//
+//  const uint32_t cols = 3;
+//  for (uint32_t c = 0; c < cols; ++c) {
+//    float *col_ptr = output.colptr(c);
+//    ASSERT_EQ(*(col_ptr + 0), 7);
+//    ASSERT_EQ(*(col_ptr + 1), 16);
+//    ASSERT_EQ(*(col_ptr + 2), 25);
+//  }
+//  LOG(INFO) << "\n" <<"Result Passed!";
+//}