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)