fix: 分离文件

include/backwardad.hpp

@@ -1,7 +1,7 @@
 #pragma once
 #include <vector>
-#include <cmath>
+#include "types/gradient.hpp"
-#include "dual.hpp"
+#include "gradient.hpp"
 
 namespace backwardad {
 

include/dual.hpp

@@ -1,9 +1,6 @@
 /*对偶数的声明部分*/
 #pragma once
-#include <iostream>
-#include <vector>
 #include <cmath>
-#include "types/common.hpp"
 #include "types/dual.hpp"
 
 // 前向自动微分的运算部分，两个deriv相乘为0
@@ -63,123 +60,4 @@ namespace forwardad{
     inline Dual atan(const Dual& x) {
         return Dual(std::atan(x.value), x.deriv / (1 + x.value * x.value));
     }
-}// namespace forwardad
+}// namespace forwardad
-
-namespace backwardad {
-    inline Node operator+(const Node& a, const Node& b) {
-        Node out(a.value() + b.value());
-        out.inputs() = {a, b};
-        out.backward() = [out, a, b]() {
-            a.add_gradient(out.gradient()); // da = dout * 1
-            b.add_gradient(out.gradient()); // db = dout * 1
-        };
-        return out;
-    }
-
-    inline Node operator-(const Node& a, const Node& b) {
-        Node out(a.value() - b.value());
-        out.inputs() = {a, b};
-        out.backward() = [out, a, b]() {
-            a.add_gradient(out.gradient()); // da = dout * 1
-            b.add_gradient(-out.gradient()); // db = dout * (-1)
-        };
-        return out;
-    }
-
-    inline Node operator*(const Node& a, const Node& b) {
-        Node out(a.value() * b.value());
-        out.inputs() = {a, b};
-        out.backward() = [out, a, b]() {
-            a.add_gradient(out.gradient() * b.value()); // da = dout * b
-            b.add_gradient(out.gradient() * a.value()); // db = dout * a
-        };
-        return out;
-    }
-
-    inline Node operator/(const Node& a, const Node& b) {
-        Node out(a.value() / b.value());
-        out.inputs() = {a, b};
-        out.backward() = [out, a, b]() {
-            a.add_gradient(out.gradient() / b.value()); // da = dout * (1/b)
-            b.add_gradient(-out.gradient() * a.value() / (b.value() * b.value())); // db = dout * (-a/b^2)
-        };
-        return out;
-    }
-
-    // 下面的函数需要用到链式法则(使用泰勒展开后保留一次项)
-    // 三角函数
-    inline Node sin(const Node& x) {
-        Node out(std::sin(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(out.gradient() * std::cos(x.value())); // dx = dout * cos(x)
-        };
-        return out;
-    }
-
-    inline Node cos(const Node& x) {
-        Node out(std::cos(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(-out.gradient() * std::sin(x.value())); // dx = dout * (-sin(x))
-        };
-        return out;
-    }
-
-    // 指数和对数
-    inline Node exp(const Node& x) {
-        Node out(std::exp(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(out.gradient() * out.value()); // dx = dout * exp(x) = dout * out.value
-        };
-        return out;
-    }
-
-    inline Node log(const Node& x) {
-        Node out(std::log(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(out.gradient() / x.value()); // dx = dout * (1/x)
-        };
-        return out;
-    }
-
-    inline Node pow(const Node& x, double n) {
-        Node out(std::pow(x.value(), n));
-        out.inputs() = {x};
-        out.backward() = [out, x, n]() {
-            x.add_gradient(out.gradient() * n * std::pow(x.value(), n - 1)); // dx = dout * (n * x^(n-1))
-        };
-        return out;
-    }
-
-    // 反三角函数
-    inline Node asin(const Node& x) {
-        Node out(std::asin(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(out.gradient() / std::sqrt(1 - x.value() * x.value())); // dx = dout * (1/sqrt(1-x^2))
-        };
-        return out;
-    }
-
-    inline Node acos(const Node& x) {
-        Node out(std::acos(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(-out.gradient() / std::sqrt(1 - x.value() * x.value())); // dx = dout * (-1/sqrt(1-x^2))
-        };
-        return out;
-    }
-
-    inline Node atan(const Node& x) {
-        Node out(std::atan(x.value()));
-        out.inputs() = {x};
-        out.backward() = [out, x]() {
-            x.add_gradient(out.gradient() / (1 + x.value() * x.value())); // dx = dout * (1/(1+x^2))
-        };
-        return out;
-    }
-
-}

include/forwardad.hpp

@@ -1,8 +1,6 @@
 /*前向自动微分的声明部分*/
 #pragma once
-#include <iostream>
 #include <vector>
-#include <functional>
 #include "dual.hpp"
 #include "types/common.hpp"
 

include/gradient.hpp

@@ -0,0 +1,121 @@
+#pragma once
+#include "types/gradient.hpp"
+
+namespace backwardad {
+    inline Node operator+(const Node& a, const Node& b) {
+        Node out(a.value() + b.value());
+        out.inputs() = {a, b};
+        out.backward() = [out, a, b]() {
+            a.add_gradient(out.gradient()); // da = dout * 1
+            b.add_gradient(out.gradient()); // db = dout * 1
+        };
+        return out;
+    }
+
+    inline Node operator-(const Node& a, const Node& b) {
+        Node out(a.value() - b.value());
+        out.inputs() = {a, b};
+        out.backward() = [out, a, b]() {
+            a.add_gradient(out.gradient()); // da = dout * 1
+            b.add_gradient(-out.gradient()); // db = dout * (-1)
+        };
+        return out;
+    }
+
+    inline Node operator*(const Node& a, const Node& b) {
+        Node out(a.value() * b.value());
+        out.inputs() = {a, b};
+        out.backward() = [out, a, b]() {
+            a.add_gradient(out.gradient() * b.value()); // da = dout * b
+            b.add_gradient(out.gradient() * a.value()); // db = dout * a
+        };
+        return out;
+    }
+
+    inline Node operator/(const Node& a, const Node& b) {
+        Node out(a.value() / b.value());
+        out.inputs() = {a, b};
+        out.backward() = [out, a, b]() {
+            a.add_gradient(out.gradient() / b.value()); // da = dout * (1/b)
+            b.add_gradient(-out.gradient() * a.value() / (b.value() * b.value())); // db = dout * (-a/b^2)
+        };
+        return out;
+    }
+
+    // 下面的函数需要用到链式法则(使用泰勒展开后保留一次项)
+    // 三角函数
+    inline Node sin(const Node& x) {
+        Node out(std::sin(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(out.gradient() * std::cos(x.value())); // dx = dout * cos(x)
+        };
+        return out;
+    }
+
+    inline Node cos(const Node& x) {
+        Node out(std::cos(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(-out.gradient() * std::sin(x.value())); // dx = dout * (-sin(x))
+        };
+        return out;
+    }
+
+    // 指数和对数
+    inline Node exp(const Node& x) {
+        Node out(std::exp(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(out.gradient() * out.value()); // dx = dout * exp(x) = dout * out.value
+        };
+        return out;
+    }
+
+    inline Node log(const Node& x) {
+        Node out(std::log(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(out.gradient() / x.value()); // dx = dout * (1/x)
+        };
+        return out;
+    }
+
+    inline Node pow(const Node& x, double n) {
+        Node out(std::pow(x.value(), n));
+        out.inputs() = {x};
+        out.backward() = [out, x, n]() {
+            x.add_gradient(out.gradient() * n * std::pow(x.value(), n - 1)); // dx = dout * (n * x^(n-1))
+        };
+        return out;
+    }
+
+    // 反三角函数
+    inline Node asin(const Node& x) {
+        Node out(std::asin(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(out.gradient() / std::sqrt(1 - x.value() * x.value())); // dx = dout * (1/sqrt(1-x^2))
+        };
+        return out;
+    }
+
+    inline Node acos(const Node& x) {
+        Node out(std::acos(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(-out.gradient() / std::sqrt(1 - x.value() * x.value())); // dx = dout * (-1/sqrt(1-x^2))
+        };
+        return out;
+    }
+
+    inline Node atan(const Node& x) {
+        Node out(std::atan(x.value()));
+        out.inputs() = {x};
+        out.backward() = [out, x]() {
+            x.add_gradient(out.gradient() / (1 + x.value() * x.value())); // dx = dout * (1/(1+x^2))
+        };
+        return out;
+    }
+
+}

include/types/common.hpp

@@ -1,6 +1,6 @@
 /*返回数据结构体*/
 #pragma once
-#include <functional>
+#include "functional"
 #include <vector>
 
 struct ADResult{

include/types/dual.hpp

@@ -1,9 +1,6 @@
 /*对偶数的数据类型定义部分*/
 #pragma once
-#include <iostream>
+#include "types/common.hpp"
-#include <functional>
-#include <memory>
-#include <vector>
 
 namespace forwardad {
 struct Dual {
@@ -13,43 +10,4 @@ struct Dual {
     Dual(double v = 0.0, double d = 0.0) : value(v), deriv(d) {}
 
 };
-} // namespace forwardad
+} // namespace forwardad
-
-namespace backwardad{
-    struct NodeData;
-
-    struct Node{
-        std::shared_ptr<NodeData> ptr;
-
-        Node() = default;
-        explicit Node(double v);
-
-        double value() const;
-        double gradient() const;
-        void add_gradient(double g) const;
-        void set_gradient(double g) const;
-        const std::vector<Node>& inputs() const;
-        std::vector<Node>& inputs();
-        std::function<void()>& backward();
-        const std::function<void()>& backward() const;
-    };
-
-    struct NodeData {
-        double value;
-        double gradient;
-        std::vector<Node> inputs;
-        std::function<void()> backward;
-
-        explicit NodeData(double v) : value(v), gradient(0.0) {}
-    };
-
-    inline Node::Node(double v) : ptr(std::make_shared<NodeData>(v)) {}
-    inline double Node::value() const { return ptr->value; }
-    inline double Node::gradient() const { return ptr->gradient; }
-    inline void Node::add_gradient(double g) const { ptr->gradient += g; }
-    inline void Node::set_gradient(double g) const { ptr->gradient = g; }
-    inline const std::vector<Node>& Node::inputs() const { return ptr->inputs; }
-    inline std::vector<Node>& Node::inputs() { return ptr->inputs; }
-    inline std::function<void()>& Node::backward() { return ptr->backward; }
-    inline const std::function<void()>& Node::backward() const { return ptr->backward; }
-} // namespace backwardad

include/types/gradient.hpp

@@ -0,0 +1,40 @@
+#pragma once
+#include "types/common.hpp"
+namespace backwardad{
+    struct NodeData;
+
+    struct Node{
+        std::shared_ptr<NodeData> ptr;
+
+        Node() = default;
+        explicit Node(double v);
+
+        double value() const;
+        double gradient() const;
+        void add_gradient(double g) const;
+        void set_gradient(double g) const;
+        const std::vector<Node>& inputs() const;
+        std::vector<Node>& inputs();
+        std::function<void()>& backward();
+        const std::function<void()>& backward() const;
+    };
+
+    struct NodeData {
+        double value;
+        double gradient;
+        std::vector<Node> inputs;
+        std::function<void()> backward;
+
+        explicit NodeData(double v) : value(v), gradient(0.0) {}
+    };
+
+    inline Node::Node(double v) : ptr(std::make_shared<NodeData>(v)) {}
+    inline double Node::value() const { return ptr->value; }
+    inline double Node::gradient() const { return ptr->gradient; }
+    inline void Node::add_gradient(double g) const { ptr->gradient += g; }
+    inline void Node::set_gradient(double g) const { ptr->gradient = g; }
+    inline const std::vector<Node>& Node::inputs() const { return ptr->inputs; }
+    inline std::vector<Node>& Node::inputs() { return ptr->inputs; }
+    inline std::function<void()>& Node::backward() { return ptr->backward; }
+    inline const std::function<void()>& Node::backward() const { return ptr->backward; }
+} // namespace backwardad