From c01d9802552e44bf228de141c572d1e8419a16a9 Mon Sep 17 00:00:00 2001 From: makefunstuff Date: Tue, 9 Jul 2024 00:23:25 +0300 Subject: wip --- src/monkey_brain/main.zig | 59 ++++++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 58 insertions(+), 1 deletion(-) (limited to 'src/monkey_brain/main.zig') diff --git a/src/monkey_brain/main.zig b/src/monkey_brain/main.zig index d488c54..52ff9e5 100644 --- a/src/monkey_brain/main.zig +++ b/src/monkey_brain/main.zig @@ -1,5 +1,62 @@ const std = @import("std"); +const testing = std.testing; + +const input_size: usize = 2; +const training_set_size: usize = 4; +const learning_rate: f64 = 0.1; +const epochs: u64 = 100 * 1000; + +fn sigmoid(x: f64) f64 { + return 1.0 / (1.0 + std.math.exp(-x)); +} + +fn sigmoid_derivative(output: f64) f64 { + return output * (1.0 - output); +} + +fn predict(weights: [input_size]f64, bias: f64, inputs: [input_size]f64) f64 { + var total: f64 = 0.0; + for (0..input_size) |i| { + total += weights[i] * inputs[i]; + } + total += bias; + return sigmoid(total); +} + +fn train(weights: *[input_size]f64, bias: *f64, training_data: [training_set_size][input_size]f64, labels: [training_set_size]f64) void { + for (0..epochs) |_| { + for (0..training_set_size) |i| { + const prediction = predict(weights.*, bias.*, training_data[i]); + const err = labels[i] - prediction; + const adjustment = err * sigmoid_derivative(prediction); + + for (0..input_size) |j| { + weights[j] += learning_rate * adjustment * training_data[i][j]; + } + bias.* += learning_rate * adjustment; + } + } +} pub fn main() !void { - std.debug.print("uga buga", .{}); + const w1 = std.crypto.random.float(f64); + const w2 = std.crypto.random.float(f64); + + var weights: [input_size]f64 = .{ w1, w2 }; + var bias: f64 = 0.0; + + const training_data: [training_set_size][input_size]f64 = .{ .{ 0, 0 }, .{ 0, 1 }, .{ 1, 0 }, .{ 1, 1 } }; + + const labels: [training_set_size]f64 = .{ 0, 0, 0, 1 }; + + train(&weights, &bias, training_data, labels); + + for (0..training_set_size) |i| { + const prediction = predict(weights, bias, training_data[i]); + std.log.info("Input {} {}, Predicted output: {}", .{ training_data[i][0], training_data[i][1], prediction }); + } +} + +test "hello" { + try testing.expect(true); } -- cgit 1.4.1-2-gfad0