init

trainer.py

@@ -0,0 +1,32 @@
+from network import Network
+import json
+import random
+
+class Trainer:
+    def __init__(self, network: Network, train_file):
+        self.network = network
+
+        with open(train_file, "r") as file:
+            f_data = file.read()
+            self.data = json.loads(f_data)
+
+    def adjust(self, check_vec, layer_idx):
+        layer = self.network.layers[layer_idx]
+
+        for i, neuron in enumerate(layer):
+            error = check_vec[i] - neuron.value
+            neuron.adjust(error)
+
+    def train(self, iters):
+        for i in range(0, iters):
+            print(f"Train {(i / iters) * 100}%")
+            sample = random.choice(self.data)
+            in_vec = sample[0]
+            check_vec = sample[1]
+
+            self.network.fire(in_vec)
+
+            self.adjust(check_vec, len(self.network.layers) - 1)
+
+
+