jacobian

commit 5a1e4177e6292021e578b43e862f81782c89fe11
parent 7d08eb02d8394b83a83313721ff9295e30b6863c
Author: David Freifeld <freifeld.david@gmail.com>
Date:   Sun,  7 Jun 2020 15:57:34 -0700

Basic neural net initialization

Diffstat:
M
bpnn.c
 | 
62
++++++++++++++++++++++++++++++++++++++++++++++++++++++++------

1 file changed, 56 insertions(+), 6 deletions(-)
diff --git a/bpnn.c b/bpnn.c
@@ -1,9 +1,12 @@
 #include <stdio.h>
+#include <math.h>
 
 #include "../mapreduce/mapreduce.h"
 #include "../mapreduce/server.h"
 #include "../mapreduce/worker.h"
 
+#define BUFSIZE 2048
+
 struct node;
 
 struct edge {
@@ -28,20 +31,67 @@ struct network {
   int length;
 };
 
-float activate (float value) {
-
+float activate (double value) {
+  // Sigmoid
+  value = 1/(1+pow(M_E, -value));
 }
 
 struct network initialize (char* path, int inputs, int neurons, int layers, int outputs) {
-  struct layer input;
-  for (int i = 0; i < 4; i++) {
-    input.nodes[i].activation = 0; // Needs some sort of scaling
+  // Read from CSV
+  FILE* fptr = fopen(path, "r");
+  double data[inputs];
+  fscanf(fptr, "%d,%d,%d,%d,*d", &data[0], &data[1], &data[2], &data[3]);
+
+  // Initialize network
+  struct network net;
+  net.layers = malloc((layers + 2) * sizeof(struct layer));
+
+  // Initialize input nodes
+  for (int i = 0; i < inputs; i++) {
+    net.layers[0].nodes[i].activation = activate(data[i]);
+  }
+
+  // Init hidden layer nodes and output nodes to 0 (will be replaced by feedforward)
+  for (int i = 1; i < layers; i++) {
+    for (int j = 0; j < neurons; j++) {
+      net.layers[i].nodes[j].activation = 0;
+    }
+  }
+  for (int i = 0; i < outputs; i++) {
+      net.layers[layers-1].nodes[i].activation = 0;
+  }
+
+  // Init edges between layers with random numbers TODO make a function to initialize edges between two layers for the love of God
+  for (int i = 0; i < inputs; i++) {
+    for (int j = 0; j < neurons; j++) {
+      struct edge connection = {&net.layers[0].nodes[i], &net.layers[1].nodes[j], rand()};
+      net.layers[0].nodes[i].outgoing[j] = connection;
+      net.layers[1].nodes[j].incoming[i] = connection;
+    }
+  }
+  for (int i = 0; i < layers-1; i++) {
+    for (int j = 0; j < neurons; j++) {
+      for (int k = 0; k < neurons; k++) {
+        struct edge connection = {&net.layers[i].nodes[j], &net.layers[i+1].nodes[k], rand()};
+        net.layers[i].nodes[j].outgoing[k] = connection;
+        net.layers[i+1].nodes[k].incoming[j] = connection;
+      }
+    }
+  }
+  for (int i = 0; i < neurons; i++) {
+    for (int j = 0; j < outputs; j++) {
+      struct edge connection = {&net.layers[0].nodes[i], &net.layers[1].nodes[j], rand()};
+      net.layers[0].nodes[i].outgoing[j] = connection;
+      net.layers[1].nodes[j].incoming[i] = connection;
+    }
   }
+  // Epic, everything's initialized TODO add biases!
+  return net;
 }
 
 struct int_pair* map (struct str_pair file)
 {
-  
+  initialize("./data_banknote_authentication.txt", 4, 5, 2, 2);
 }
 
 struct int_pair* reduce (struct int_pair* input)