zigtolean

Prompt

ezt a kódot akarom lean 4 be 100% osan le formal verifactionozni nem engedek meg semmi by taktikat semmi sorryt semmi egyszerűsítést semmi eltérést egész pontosan a zig fájlt lell pontosan bizonyítania egy lean fájlban az egész only theoeem mode Send back the complete code with all the fixes. Fix each of the listed errors one by one, making sure to actually correct them so that there are 0 errors remaining. Keep the original imports, since the files exist. Write out every single character; do not abbreviate anything. Fix every error. There must be exactly one file. Do not write anything else; just output the complete code, and it must not contain any comments. Never, under any circumstances, use simplified, substitute, dummy, simulated, or fake code. Write the entire file as complete, unabridged, production-ready code in a single code block. It must be 100% error-free, a complete, error-free file, and must be submitted as a downloadable file. These requirements are mandatory and must be strictly adhered to. If no list of errors is provided, you must find all the errors and fix them. If there were comments in the original code, delete them. And most importantly: YOU MUST NEVER SIMPLIFY! const std = @import("std"); const Tensor = @import("../core/tensor.zig").Tensor; pub const OFTB = struct { pub const FRACTAL_SCALE: f32 = 0.7071067811865476; dim: usize, pub fn init(d: usize) OFTB { std.debug.assert(d != 0); std.debug.assert(d <= std.math.maxInt(usize) / 2); return OFTB{ .dim = d, }; } pub fn deinit(self: *OFTB) void { self.* = undefined; } pub fn forwardInPlace(self: OFTB, x: *Tensor) !void { if (self.dim == 0) return error.InvalidDimension; if (self.dim > std.math.maxInt(usize) / 2) return error.DimensionOverflow; const total = self.dim * 2; if (x.data.len != total) return error.DimensionMismatch; const half = self.dim; const x1 = x.data[0..half]; const x2 = x.data[half..][0..half]; const scale: f32 = FRACTAL_SCALE; const VLEN: usize = 8; var i: usize = 0; while (i + VLEN <= half) : (i += VLEN) { const va: @Vector(VLEN, f32) = x1[i..][0..VLEN].*; const vb: @Vector(VLEN, f32) = x2[i..][0..VLEN].*; const vscale: @Vector(VLEN, f32) = @splat(scale); x1[i..][0..VLEN].* = (va - vb) * vscale; x2[i..][0..VLEN].* = (va + vb) * vscale; } while (i < half) : (i += 1) { const a = x1[i]; const b = x2[i]; x1[i] = (a - b) * scale; x2[i] = (a + b) * scale; } } pub fn backwardInPlace(self: OFTB, grad: []f32) !void { if (self.dim == 0) return error.InvalidDimension; if (self.dim > std.math.maxInt(usize) / 2) return error.DimensionOverflow; const total = self.dim * 2; if (grad.len != total) return error.DimensionMismatch; const half = self.dim; const g1 = grad[0..half]; const g2 = grad[half..][0..half]; const scale: f32 = FRACTAL_SCALE; const VLEN: usize = 8; var i: usize = 0; while (i + VLEN <= half) : (i += VLEN) { const va: @Vector(VLEN, f32) = g1[i..][0..VLEN].*; const vb: @Vector(VLEN, f32) = g2[i..][0..VLEN].*; const vscale: @Vector(VLEN, f32) = @splat(scale); g1[i..][0..VLEN].* = (va + vb) * vscale; g2[i..][0..VLEN].* = (vb - va) * vscale; } while (i < half) : (i += 1) { const a = g1[i]; const b = g2[i]; g1[i] = (a + b) * scale; g2[i] = (b - a) * scale; } } }; pub fn mixForward(oftb: OFTB, x: *Tensor) !void { try oftb.forwardInPlace(x); } pub fn mixBackward(oftb: OFTB, grad: []f32) !void { try oftb.backwardInPlace(grad); } comptime { _ = OFTB; } test "OFTB forward then backward returns input within 1e-5 tolerance" { const allocator = std.testing.allocator; var prng = std.Random.DefaultPrng.init(42); const random = prng.random(); const dim: usize = 32; const total = dim * 2; var input = try Tensor.init(allocator, &.{ 1, total }); defer input.deinit(); var i: usize = 0; while (i < input.data.len) : (i += 1) { input.data[i] = (random.float(f32) - 0.5) * 2.0; } const original = try allocator.dupe(f32, input.data); defer allocator.free(original); var oftb = OFTB.init(dim); try oftb.forwardInPlace(&input); try oftb.backwardInPlace(input.data); i = 0; while (i < input.data.len) : (i += 1) { try std.testing.expectApproxEqAbs(input.data[i], original[i], 1e-5); } }