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// CNN v3 — Decoder level 0 + output
// NearestUp2x(dec1) + cat(enc0_skip) -> Conv(8->4, 3x3, zero-pad) + FiLM + ReLU + Sigmoid
//
// Inputs: dec1_tex (rgba16float, 4ch) half-res
// enc0_tex (rgba16float, 4ch) full-res (skip connection)
// Output: output_tex (rgba16float, 4ch) full-res (dispatch at full-res dims)
//
// Weight layout (f16, OIHW + bias):
// [0 .. 8*4*9) conv: w[out][in][ky][kx] (in=8: 4 dec1 + 4 enc0 skip)
// [288 .. +4) bias: b[out]
//
// Parity note: sigmoid applied directly to dec0 output (matches train_cnn_v3.py forward()).
#include "cnn_v3/common"
const DEC0_IN: u32 = 8u;
const DEC0_OUT: u32 = 4u;
struct Params {
weight_offset: u32,
_pad: vec3u,
gamma: vec4f,
beta: vec4f,
}
@group(0) @binding(0) var dec1_tex: texture_2d<f32>;
@group(0) @binding(1) var enc0_tex: texture_2d<f32>;
@group(0) @binding(2) var<storage, read> weights: array<u32>;
@group(0) @binding(3) var<uniform> params: Params;
@group(0) @binding(4) var output_tex: texture_storage_2d<rgba16float, write>;
// Load 8 concatenated channels at full-res coord:
// ch 0-3: dec1 nearest-up (dec1_tex[coord/2])
// ch 4-7: enc0 skip (enc0_tex[coord])
// Returns zeros for OOB coord (zero-padding for the conv).
fn load_dec0_concat(coord: vec2i, full_dims: vec2i) -> array<f32, 8> {
if (coord.x < 0 || coord.y < 0 || coord.x >= full_dims.x || coord.y >= full_dims.y) {
return array<f32, 8>(0., 0., 0., 0., 0., 0., 0., 0.);
}
let half_dims = vec2i(textureDimensions(dec1_tex));
let hc = clamp(coord / 2, vec2i(0), half_dims - vec2i(1));
let d = textureLoad(dec1_tex, hc, 0);
let e = textureLoad(enc0_tex, coord, 0);
return array<f32, 8>(d.x, d.y, d.z, d.w, e.x, e.y, e.z, e.w);
}
@compute @workgroup_size(8, 8)
fn dec0_main(@builtin(global_invocation_id) id: vec3u) {
let full_dims = vec2i(textureDimensions(enc0_tex));
let coord = vec2i(id.xy);
if (coord.x >= full_dims.x || coord.y >= full_dims.y) { return; }
let wo = params.weight_offset;
var out: array<f32, DEC0_OUT>;
for (var o: u32 = 0u; o < DEC0_OUT; o++) {
var sum = get_w(wo, DEC0_OUT * DEC0_IN * 9u + o); // bias
for (var ky: i32 = -1; ky <= 1; ky++) {
for (var kx: i32 = -1; kx <= 1; kx++) {
let feat = load_dec0_concat(coord + vec2i(kx, ky), full_dims);
let ki = u32(ky + 1) * 3u + u32(kx + 1);
for (var i: u32 = 0u; i < DEC0_IN; i++) {
sum += get_w(wo, o * DEC0_IN * 9u + i * 9u + ki) * feat[i];
}
}
}
// FiLM + ReLU + Sigmoid (matches training forward())
let v = max(0.0, params.gamma[o] * sum + params.beta[o]);
out[o] = 1.0 / (1.0 + exp(-v));
}
textureStore(output_tex, coord, vec4f(out[0], out[1], out[2], out[3]));
}
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