Added simple Zig implementation

.github/workflows/ci.yaml

@@ -112,3 +112,20 @@ jobs:
     - name: Tests
       working-directory: Java
       run: bats test.bats
+
+  zig:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Setup
+        run: |
+          sudo npm install -g bats
+
+      - name: Setup Zig
+        uses: mlugg/setup-zig@v1
+        with:
+          version: 0.14.0
+
+      - name: Tests
+        working-directory: Zig
+        run: bats test.bats

Zig/.gitignore

@@ -0,0 +1,2 @@
+zig-out
+.zig-cache

Zig/build.zig

@@ -0,0 +1,39 @@
+const std = @import("std");
+
+pub fn build(b: *std.Build) void {
+    const target = b.standardTargetOptions(.{});
+    const optimize = b.standardOptimizeOption(.{});
+
+    const exe_mod = b.createModule(.{
+        .root_source_file = b.path("src/main.zig"),
+        .target = target,
+        .optimize = optimize,
+    });
+
+    const exe = b.addExecutable(.{
+        .name = "NeuralNetworkInAllLangs",
+        .root_module = exe_mod,
+    });
+
+    b.installArtifact(exe);
+
+    const run_cmd = b.addRunArtifact(exe);
+
+    run_cmd.step.dependOn(b.getInstallStep());
+
+    if (b.args) |args| {
+        run_cmd.addArgs(args);
+    }
+
+    const run_step = b.step("run", "Run the app");
+    run_step.dependOn(&run_cmd.step);
+
+    const exe_unit_tests = b.addTest(.{
+        .root_module = exe_mod,
+    });
+
+    const run_exe_unit_tests = b.addRunArtifact(exe_unit_tests);
+
+    const test_step = b.step("test", "Run unit tests");
+    test_step.dependOn(&run_exe_unit_tests.step);
+}

Zig/build.zig.zon

@@ -0,0 +1,86 @@
+.{
+    // This is the default name used by packages depending on this one. For
+    // example, when a user runs `zig fetch --save <url>`, this field is used
+    // as the key in the `dependencies` table. Although the user can choose a
+    // different name, most users will stick with this provided value.
+    //
+    // It is redundant to include "zig" in this name because it is already
+    // within the Zig package namespace.
+    .name = .Zig,
+
+    // This is a [Semantic Version](https://semver.org/).
+    // In a future version of Zig it will be used for package deduplication.
+    .version = "0.0.0",
+
+    // Together with name, this represents a globally unique package
+    // identifier. This field is generated by the Zig toolchain when the
+    // package is first created, and then *never changes*. This allows
+    // unambiguous detection of one package being an updated version of
+    // another.
+    //
+    // When forking a Zig project, this id should be regenerated (delete the
+    // field and run `zig build`) if the upstream project is still maintained.
+    // Otherwise, the fork is *hostile*, attempting to take control over the
+    // original project's identity. Thus it is recommended to leave the comment
+    // on the following line intact, so that it shows up in code reviews that
+    // modify the field.
+    .fingerprint = 0xf9835661bb6dc018, // Changing this has security and trust implications.
+
+    // Tracks the earliest Zig version that the package considers to be a
+    // supported use case.
+    .minimum_zig_version = "0.14.0",
+
+    // This field is optional.
+    // Each dependency must either provide a `url` and `hash`, or a `path`.
+    // `zig build --fetch` can be used to fetch all dependencies of a package, recursively.
+    // Once all dependencies are fetched, `zig build` no longer requires
+    // internet connectivity.
+    .dependencies = .{
+        // See `zig fetch --save <url>` for a command-line interface for adding dependencies.
+        //.example = .{
+        //    // When updating this field to a new URL, be sure to delete the corresponding
+        //    // `hash`, otherwise you are communicating that you expect to find the old hash at
+        //    // the new URL. If the contents of a URL change this will result in a hash mismatch
+        //    // which will prevent zig from using it.
+        //    .url = "https://example.com/foo.tar.gz",
+        //
+        //    // This is computed from the file contents of the directory of files that is
+        //    // obtained after fetching `url` and applying the inclusion rules given by
+        //    // `paths`.
+        //    //
+        //    // This field is the source of truth; packages do not come from a `url`; they
+        //    // come from a `hash`. `url` is just one of many possible mirrors for how to
+        //    // obtain a package matching this `hash`.
+        //    //
+        //    // Uses the [multihash](https://multiformats.io/multihash/) format.
+        //    .hash = "...",
+        //
+        //    // When this is provided, the package is found in a directory relative to the
+        //    // build root. In this case the package's hash is irrelevant and therefore not
+        //    // computed. This field and `url` are mutually exclusive.
+        //    .path = "foo",
+        //
+        //    // When this is set to `true`, a package is declared to be lazily
+        //    // fetched. This makes the dependency only get fetched if it is
+        //    // actually used.
+        //    .lazy = false,
+        //},
+    },
+
+    // Specifies the set of files and directories that are included in this package.
+    // Only files and directories listed here are included in the `hash` that
+    // is computed for this package. Only files listed here will remain on disk
+    // when using the zig package manager. As a rule of thumb, one should list
+    // files required for compilation plus any license(s).
+    // Paths are relative to the build root. Use the empty string (`""`) to refer to
+    // the build root itself.
+    // A directory listed here means that all files within, recursively, are included.
+    .paths = .{
+        "build.zig",
+        "build.zig.zon",
+        "src",
+        // For example...
+        //"LICENSE",
+        //"README.md",
+    },
+}

Zig/src/main.zig

@@ -0,0 +1,104 @@
+const std = @import("std");
+const Trainer = @import("neural.zig").Trainer;
+
+fn rand() f64 {
+    const P: u32 = 2147483647;
+    const A: u32 = 16807;
+    const S = struct {
+        var current: u32 = 1;
+    };
+
+    S.current = S.current *% A % P;
+
+    return @as(f64, @floatFromInt(S.current)) / @as(f64, @floatFromInt(P));
+}
+
+fn _xor(i: u32, j: u32) u32 {
+    return i ^ j;
+}
+
+fn _xnor(i: u32, j: u32) u32 {
+    return 1 - _xor(i, j);
+}
+
+fn _or(i: u32, j: u32) u32 {
+    return i | j;
+}
+
+fn _and(i: u32, j: u32) u32 {
+    return i & j;
+}
+
+fn _nor(i: u32, j: u32) u32 {
+    return 1 - _or(i, j);
+}
+
+fn _nand(i: u32, j: u32) u32 {
+    return 1 - _and(i, j);
+}
+
+fn DataItem(comptime I: usize, comptime O: usize) type {
+    return struct {
+        input: [I]f64,
+        output: [O]f64,
+    };
+}
+
+pub fn main() !void {
+    var dba = std.heap.DebugAllocator(.{}){};
+    defer std.debug.assert(dba.deinit() == .ok);
+    const allocator = dba.allocator();
+
+    var all_data = try allocator.alloc(DataItem(2, 6), 4);
+    defer allocator.free(all_data);
+
+    for ([_]u32{ 0, 1 }) |i| {
+        for ([_]u32{ 0, 1 }) |j| {
+            all_data[i * 2 + j] = .{
+                .input = .{ @floatFromInt(i), @floatFromInt(j) },
+                .output = .{
+                    @floatFromInt(_xor(i, j)),
+                    @floatFromInt(_xnor(i, j)),
+                    @floatFromInt(_or(i, j)),
+                    @floatFromInt(_and(i, j)),
+                    @floatFromInt(_nor(i, j)),
+                    @floatFromInt(_nand(i, j)),
+                },
+            };
+        }
+    }
+
+    var trainer = try Trainer.init(allocator, 2, 2, 6, rand);
+    defer trainer.deinit(allocator);
+
+    const steps = 4000;
+    const lr: f64 = 1.0;
+
+    for (0..steps) |i| {
+        var example = all_data[i % 4];
+        try trainer.train(&example.input, &example.output, lr);
+    }
+
+    std.debug.print("Result after {d} iterations\n", .{steps});
+    std.debug.print("        XOR  XNOR    OR   AND   NOR  NAND\n", .{});
+    for (0..all_data.len) |i| {
+        var example = all_data[i];
+        const pred = try trainer.network.predict(allocator, &example.input);
+        defer allocator.free(pred);
+        std.debug.print(
+            "{d:.0},{d:.0} = {d:.3} {d:.3} {d:.3} {d:.3} {d:.3} {d:.3}\n",
+            .{
+                example.input[0],
+                example.input[1],
+                pred[0],
+                pred[1],
+                pred[2],
+                pred[3],
+                pred[4],
+                pred[5],
+            },
+        );
+    }
+
+    trainer.network.print();
+}