def main():
l1 = NeuronLayer((28, 28), True, False)
l2 = NeuronLayer((10, 10))
l3 = NeuronLayer((10,), False, True)
network = NeuralNetwork()
network.add_layer(l1)
network.add_layer(l2)
network.add_layer(l3)
network.connect_layers()
pr = cProfile.Profile()
pr.enable()
training_images = os.path.abspath(os.path.join(MAIN_MODULE_PATH, "..", "data", "train-images.idx3-ubyte"))
training_labels = os.path.abspath(os.path.join(MAIN_MODULE_PATH, "..", "data", "train-labels.idx1-ubyte"))
network.load_data(training_images, training_labels)
test_images = os.path.join(MAIN_MODULE_PATH, "..", "data", "t10k-images.idx3-ubyte")
test_labels = os.path.join(MAIN_MODULE_PATH, "..", "data", "t10k-labels.idx1-ubyte")
network.load_test_data(test_images, test_labels)
network.SGD(0.1, 0.1, 30, 10)
pr.disable()
pr.print_stats(sort="cumtime")
from NeuralNet import NeuralNetwork
from NeuronLayer import NeuronLayer
import cProfile
import os
if __name__ == "__main__":
l1 = NeuronLayer((28, 28), True, False)
l2 = NeuronLayer((100, ))
l3 = NeuronLayer((10, ), False, True)
network = NeuralNetwork()
network.add_layer(l1)
network.add_layer(l2)
network.add_layer(l3)
network.connect_layers()
pr = cProfile.Profile()
pr.enable()
network.load_data(os.path.abspath("data/train-images.idx3-ubyte"),
os.path.abspath("data/train-labels.idx1-ubyte"))
network.load_test_data(os.path.abspath("data/t10k-images.idx3-ubyte"),
os.path.abspath("data/t10k-labels.idx1-ubyte"))
network.SGD(0.1, 0.1, 30, 10)
pr.disable()
pr.print_stats(sort="cumtime")