feat: Resolvable guarded compute pipelines

apps/typegpu-docs/src/content/docs/fundamentals/utils.mdx

@@ -118,6 +118,16 @@ The default workgroup sizes are:
 The callback is not called if the global invocation id of a thread would exceed the size in any dimension.
 :::
 
+:::tip
+`TgpuGuardedComputePipeline` provides getters for the underlying pipeline and the size buffer.
+Those might be useful for `tgpu.resolve`, since you cannot resolve a guarded pipeline directly.
+
+```ts
+const innerPipeline = doubleUpPipeline.with(bindGroup1).pipeline;
+tgpu.resolve({ externals: { innerPipeline } });
+```
+:::
+
 ## *console.log*
 
 Yes, you read that correctly, TypeGPU implements logging to the console on the GPU!

packages/typegpu/src/core/root/init.ts

@@ -187,6 +187,14 @@ export class TgpuGuardedComputePipelineImpl<TArgs extends number[]>
     // Yeah, i know we flush here... but it's only a matter of time!
     this.#root.flush();
   }
+
+  get pipeline() {
+    return this.#pipeline;
+  }
+
+  get sizeUniform() {
+    return this.#sizeUniform;
+  }
 }
 
 class WithBindingImpl implements WithBinding {

packages/typegpu/src/core/root/rootTypes.ts

@@ -13,6 +13,7 @@ import type {
   AnyWgslData,
   U16,
   U32,
+  Vec3u,
   Void,
   WgslArray,
 } from '../../data/wgslTypes.ts';
@@ -94,6 +95,17 @@ export interface TgpuGuardedComputePipeline<TArgs extends number[] = number[]> {
    * "guarded" by a bounds check.
    */
   dispatchThreads(...args: TArgs): void;
+
+  /**
+   * The underlying pipeline used during `dispatchThreads`.
+   */
+  pipeline: TgpuComputePipeline;
+
+  /**
+   * The buffer used to automatically pass the thread count to the underlying pipeline during `dispatchThreads`.
+   * For pipelines with a dimension count lower than 3, the remaining coordinates are expected to be 1.
+   */
+  sizeUniform: TgpuUniform<Vec3u>;
 }
 
 export interface WithCompute {

packages/typegpu/tests/pipeline-resolution.test.ts

@@ -0,0 +1,140 @@
+import { describe, expect } from 'vitest';
+import * as d from '../src/data/index.ts';
+import tgpu from '../src/index.ts';
+import { it } from './utils/extendedIt.ts';
+
+describe('resolve', () => {
+  const Boid = d.struct({
+    position: d.vec2f,
+    color: d.vec4f,
+  });
+
+  const computeFn = tgpu['~unstable'].computeFn({
+    workgroupSize: [1, 1, 1],
+    in: { gid: d.builtin.globalInvocationId },
+  })(() => {
+    const myBoid = Boid({
+      position: d.vec2f(0, 0),
+      color: d.vec4f(1, 0, 0, 1),
+    });
+  });
+
+  const vertexFn = tgpu['~unstable'].vertexFn({
+    out: { pos: d.builtin.position, color: d.vec4f },
+  })(() => {
+    const myBoid = Boid();
+    return { pos: d.vec4f(myBoid.position, 0, 1), color: myBoid.color };
+  });
+
+  const fragmentFn = tgpu['~unstable'].fragmentFn({
+    in: { color: d.vec4f },
+    out: d.vec4f,
+  })((input) => {
+    return input.color;
+  });
+
+  it('can resolve a render pipeline', ({ root }) => {
+    const pipeline = root
+      .withVertex(vertexFn, {})
+      .withFragment(fragmentFn, { format: 'rgba8unorm' })
+      .createPipeline();
+
+    expect(tgpu.resolve({ externals: { pipeline } })).toMatchInlineSnapshot(`
+      "struct Boid_1 {
+        position: vec2f,
+        color: vec4f,
+      }
+
+      struct vertexFn_Output_2 {
+        @builtin(position) pos: vec4f,
+        @location(0) color: vec4f,
+      }
+
+      @vertex fn vertexFn_0() -> vertexFn_Output_2 {
+        var myBoid = Boid_1();
+        return vertexFn_Output_2(vec4f(myBoid.position, 0, 1), myBoid.color);
+      }
+
+      struct fragmentFn_Input_4 {
+        @location(0) color: vec4f,
+      }
+
+      @fragment fn fragmentFn_3(input: fragmentFn_Input_4) -> @location(0) vec4f {
+        return input.color;
+      }"
+    `);
+  });
+
+  it('can resolve a compute pipeline', ({ root }) => {
+    const pipeline = root
+      .withCompute(computeFn)
+      .createPipeline();
+
+    expect(tgpu.resolve({ externals: { pipeline } })).toMatchInlineSnapshot(`
+      "struct Boid_1 {
+        position: vec2f,
+        color: vec4f,
+      }
+
+      struct computeFn_Input_2 {
+        @builtin(global_invocation_id) gid: vec3u,
+      }
+
+      @compute @workgroup_size(1, 1, 1) fn computeFn_0(_arg_0: computeFn_Input_2) {
+        var myBoid = Boid_1(vec2f(), vec4f(1, 0, 0, 1));
+      }"
+    `);
+  });
+
+  it('can resolve a guarded compute pipeline', ({ root }) => {
+    const pipelineGuard = root.createGuardedComputePipeline((x, y, z) => {
+      'use gpu';
+      const myBoid = Boid({
+        position: d.vec2f(0, 0),
+        color: d.vec4f(x, y, z, 1),
+      });
+    });
+
+    expect(tgpu.resolve({ externals: { pipeline: pipelineGuard.pipeline } }))
+      .toMatchInlineSnapshot(`
+        "@group(0) @binding(0) var<uniform> sizeUniform_1: vec3u;
+
+        struct Boid_3 {
+          position: vec2f,
+          color: vec4f,
+        }
+
+        fn wrappedCallback_2(x: u32, y: u32, z: u32) {
+          var myBoid = Boid_3(vec2f(), vec4f(f32(x), f32(y), f32(z), 1));
+        }
+
+        struct mainCompute_Input_4 {
+          @builtin(global_invocation_id) id: vec3u,
+        }
+
+        @compute @workgroup_size(8, 8, 4) fn mainCompute_0(in: mainCompute_Input_4)  {
+          if (any(in.id >= sizeUniform_1)) {
+            return;
+          }
+          wrappedCallback_2(in.id.x, in.id.y, in.id.z);
+        }"
+      `);
+  });
+
+  it('throws when resolving multiple pipelines', ({ root }) => {
+    const renderPipeline = root
+      .withVertex(vertexFn, {})
+      .withFragment(fragmentFn, { format: 'rgba8unorm' })
+      .createPipeline();
+
+    const computePipeline = root
+      .withCompute(computeFn)
+      .createPipeline();
+
+    expect(() =>
+      tgpu.resolve({ externals: { renderPipeline, computePipeline } })
+    ).toThrowErrorMatchingInlineSnapshot(
+      `[Error: Found 2 pipelines but can only resolve one at a time.]`,
+    );
+  });
+});