jacobian

commit ea7d9e1c72c35308586bf7cf473d09412d02a2ec
parent 761debbb9ef1e9cc9c2c5f86b07a4f90ed9b204d
Author: David Freifeld <freifeld.david@gmail.com>
Date:   Sun, 28 Mar 2021 20:28:58 -0700

Network interactivity aids and visualization in demo

Diffstat:
M
src/bpnn.cpp
 | 
12
++++++++++++
M
src/bpnn.hpp
 | 
10
++++++++++
M
src/pybind.cpp
 | 
17
++++++++++++++---

3 files changed, 36 insertions(+), 3 deletions(-)
diff --git a/src/bpnn.cpp b/src/bpnn.cpp
@@ -25,6 +25,7 @@ Layer::Layer(int batch_sz, int nodes)
     }
 }
 
+
 void Layer::init_weights(Layer next)
 {
     v = new Eigen::MatrixXf (contents->cols(), next.contents->cols());
@@ -294,6 +295,17 @@ void Network::validate(const char* path)
 
 #include "optimizers.cpp"
 
+void Network::interactive_next_batch()
+{
+    if (batches < instances/batch_size-batch_size) next_batch(data);
+    else {
+        batches = 0;
+        data = open(TRAIN_BIN_PATH, O_RDONLY | O_NONBLOCK);
+        decay(learning_rate);
+    }
+    batches++;
+}
+
 void Network::train()
 {
     float cost_sum = 0;
diff --git a/src/bpnn.hpp b/src/bpnn.hpp
@@ -15,6 +15,7 @@
 
 #define BUFFER_SIZE 600*1024
 #define LARGE_BUF 600*1024*15
+#define MATRIX_NULL Eigen::MatrixXf::Constant(0,1,1)
 enum Regularization {L1, L2};
 
 class Layer {
@@ -32,6 +33,14 @@ public:
     Layer(float* vals, int rows, int columns);
     void operator=(const Layer& that);
     void init_weights(Layer next);
+
+    Eigen::MatrixXf get_contents() {return *contents;}
+    Eigen::MatrixXf get_weights() {if (weights == nullptr) return MATRIX_NULL; else return *weights;}
+    Eigen::MatrixXf get_bias() {return *bias;}
+    Eigen::MatrixXf get_dZ() {return *v;}
+    Eigen::MatrixXf get_v() {if (weights == nullptr) return MATRIX_NULL; else return *v;}
+    Eigen::MatrixXf get_m() {if (weights == nullptr) return MATRIX_NULL; else return *m;}
+
 };
 
 class Network {
@@ -78,6 +87,7 @@ public:
     void feedforward();
     void softmax();
     void list_net();
+    void interactive_next_batch();
     float cost();
     float accuracy();
     Eigen::MatrixXf backpropagate();
diff --git a/src/pybind.cpp b/src/pybind.cpp
@@ -6,6 +6,7 @@
 //
 
 #include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
 #include <pybind11/functional.h>
 #include <pybind11/eigen.h>
 
@@ -21,7 +22,15 @@ PYBIND11_MODULE(_jacobian, m)
         .value("L2", Regularization::L2)
         .export_values();
     py::class_<Layer>(m, "Layer")
-        .def(py::init<int, int>());
+        .def(py::init<int, int>())
+        .def("get_contents", &Layer::get_contents)
+        .def("get_weights", &Layer::get_weights)
+        .def("get_bias", &Layer::get_bias)
+        .def("get_v", &Layer::get_v)
+        .def("get_m", &Layer::get_m)
+        .def("get_dZ", &Layer::get_dZ)
+        .def_readonly("activation", &Layer::activation)
+        .def_readonly("activation_deriv", &Layer::activation);
     py::class_<Network>(m, "Network")
         .def(py::init<char *, int, float, float, Regularization, float,
                   float, bool, float>(),
@@ -40,13 +49,15 @@ PYBIND11_MODULE(_jacobian, m)
         .def("feedforward", &Network::feedforward)
         .def("backpropagate", &Network::backpropagate)
         .def("list_net", &Network::list_net)
+        .def("next_batch", &Network::interactive_next_batch)
         .def("cost", &Network::cost)
         .def("accuracy", &Network::accuracy)
         .def("train", &Network::train)
-        .def("get_acc", &Network::get_acc)
         .def("get_cost", &Network::get_cost)
+        .def("get_acc", &Network::get_acc)
+        .def("get_val_cost", &Network::get_val_cost)
         .def("get_val_acc", &Network::get_val_acc)
-        .def("get_val_cost", &Network::get_val_cost);
+        .def_readonly("layers", &Network::layers);
     m.def("linear", &linear, py::arg("x"));
     m.def("linear_deriv", &linear_deriv, py::arg("x"));
     m.def("sigmoid", &sigmoid, py::arg("x"));