From 8f2c7c513bc54bf127ff2ab00da1694fb981f442 Mon Sep 17 00:00:00 2001 From: makefunstuff Date: Tue, 9 Jul 2024 00:49:37 +0300 Subject: refactoring --- src/monkey_brain/main.zig | 80 +--------------------------- src/monkey_brain/multi_layer_perceptron.zig | 0 src/monkey_brain/perceptron.zig | 81 +++++++++++++++++++++++++++++ src/monkey_brain/test.zig | 2 +- 4 files changed, 84 insertions(+), 79 deletions(-) create mode 100644 src/monkey_brain/multi_layer_perceptron.zig create mode 100644 src/monkey_brain/perceptron.zig (limited to 'src/monkey_brain') diff --git a/src/monkey_brain/main.zig b/src/monkey_brain/main.zig index 5d0e616..611dcd1 100644 --- a/src/monkey_brain/main.zig +++ b/src/monkey_brain/main.zig @@ -1,81 +1,5 @@ -const std = @import("std"); -const testing = std.testing; -const math = std.math; - -const input_size: usize = 2; -const training_set_size: usize = 4; -const learning_rate: f64 = 0.1; -const epochs: u64 = 1000000; - -fn sigmoid(x: f64) f64 { - return 1.0 / (1.0 + 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 = bias; - for (inputs, 0..) |input, i| { - total += weights[i] * input; - } - 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 (training_data, labels) |inputs, label| { - const prediction = predict(weights.*, bias.*, inputs); - const err = label - prediction; - const adjustment = err * sigmoid_derivative(prediction); - for (inputs, 0..) |input, j| { - weights[j] += learning_rate * adjustment * input; - } - bias.* += learning_rate * adjustment; - } - } -} +const perceptron = @import("perceptron.zig"); pub fn main() !void { - var weights = [_]f64{ std.crypto.random.float(f64), std.crypto.random.float(f64) }; - var bias: f64 = std.crypto.random.float(f64); - - const training_data = [_][input_size]f64{ - .{ 0, 0 }, - .{ 0, 1 }, - .{ 1, 0 }, - .{ 1, 1 }, - }; - const labels = [_]f64{ 0, 1, 1, 1 }; // OR operation - - train(&weights, &bias, training_data, labels); - - std.debug.print("Trained weights: {d}, {d}\n", .{ weights[0], weights[1] }); - std.debug.print("Trained bias: {d}\n", .{bias}); - - for (training_data, labels) |inputs, expected| { - const prediction = predict(weights, bias, inputs); - std.debug.print("Input: {d}, {d}, Predicted: {d:.4}, Expected: {d}\n", .{ inputs[0], inputs[1], prediction, expected }); - } -} - -test "OR gate" { - var weights = [_]f64{ 0, 0 }; - var bias: f64 = 0; - - const training_data = [_][input_size]f64{ - .{ 0, 0 }, - .{ 0, 1 }, - .{ 1, 0 }, - .{ 1, 1 }, - }; - const labels = [_]f64{ 0, 1, 1, 1 }; - - train(&weights, &bias, training_data, labels); - - for (training_data, labels) |inputs, expected| { - const prediction = predict(weights, bias, inputs); - try testing.expect((prediction - expected) < 0.1); - } + try perceptron.demo(); } diff --git a/src/monkey_brain/multi_layer_perceptron.zig b/src/monkey_brain/multi_layer_perceptron.zig new file mode 100644 index 0000000..e69de29 diff --git a/src/monkey_brain/perceptron.zig b/src/monkey_brain/perceptron.zig new file mode 100644 index 0000000..c65fc41 --- /dev/null +++ b/src/monkey_brain/perceptron.zig @@ -0,0 +1,81 @@ +const std = @import("std"); +const testing = std.testing; +const math = std.math; + +const input_size: usize = 2; +const training_set_size: usize = 4; +const learning_rate: f64 = 0.1; +const epochs: u64 = 1000000; + +fn sigmoid(x: f64) f64 { + return 1.0 / (1.0 + 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 = bias; + for (inputs, 0..) |input, i| { + total += weights[i] * input; + } + 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 (training_data, labels) |inputs, label| { + const prediction = predict(weights.*, bias.*, inputs); + const err = label - prediction; + const adjustment = err * sigmoid_derivative(prediction); + for (inputs, 0..) |input, j| { + weights[j] += learning_rate * adjustment * input; + } + bias.* += learning_rate * adjustment; + } + } +} + +pub fn demo() !void { + var weights = [_]f64{ std.crypto.random.float(f64), std.crypto.random.float(f64) }; + var bias: f64 = std.crypto.random.float(f64); + + const training_data = [_][input_size]f64{ + .{ 0, 0 }, + .{ 0, 1 }, + .{ 1, 0 }, + .{ 1, 1 }, + }; + const labels = [_]f64{ 0, 1, 1, 1 }; // OR operation + + train(&weights, &bias, training_data, labels); + + std.debug.print("Trained weights: {d}, {d}\n", .{ weights[0], weights[1] }); + std.debug.print("Trained bias: {d}\n", .{bias}); + + for (training_data, labels) |inputs, expected| { + const prediction = predict(weights, bias, inputs); + std.debug.print("Input: {d}, {d}, Predicted: {d:.4}, Expected: {d}\n", .{ inputs[0], inputs[1], prediction, expected }); + } +} + +test "OR gate" { + var weights = [_]f64{ 0, 0 }; + var bias: f64 = 0; + + const training_data = [_][input_size]f64{ + .{ 0, 0 }, + .{ 0, 1 }, + .{ 1, 0 }, + .{ 1, 1 }, + }; + const labels = [_]f64{ 0, 1, 1, 1 }; + + train(&weights, &bias, training_data, labels); + + for (training_data, labels) |inputs, expected| { + const prediction = predict(weights, bias, inputs); + try testing.expect((prediction - expected) < 0.1); + } +} diff --git a/src/monkey_brain/test.zig b/src/monkey_brain/test.zig index 7a71043..4d4a04b 100644 --- a/src/monkey_brain/test.zig +++ b/src/monkey_brain/test.zig @@ -1,4 +1,4 @@ -pub const main = @import("main.zig"); +pub const perceptron = @import("perceptron.zig"); test { @import("std").testing.refAllDecls(@This()); -- cgit 1.4.1-2-gfad0