docs: clarify user-defined NFloat and InterlockedAddF16Emulated in autodiff tutorial 2

[nv-slang-bot]

Summary

In docs/auto-diff-tutorial-2.md, the identifiers NFloat and InterlockedAddF16Emulated are used throughout the code listings but never declared. A reader can plausibly mistake NFloat for a built-in scalar type alongside float/half, and InterlockedAddF16Emulated looks like an HLSL Interlocked* intrinsic.

This PR adds a brief "Conventions Used in the Code Listings" subsection at the start of section 3, just before the first place these identifiers appear. It declares NFloat as a typealias for half and provides a one-line signature stub for InterlockedAddF16Emulated, with comments explaining why each exists.

The fix shape is intentionally different from the empty-struct stubs in #195 — NFloat is a typedef-like alias and the right form is typealias NFloat = half;, not an empty struct.

Why half for NFloat

Consistent with how the tutorial already uses these types:

• The explanatory note at line 83: "Note that we are using half type, which is 16-bit floating-point type for better throughput and to reduce memory usage".
• MLVec<N> stores half data[N] and toArray() returns NFloat[N] directly from data (only valid if NFloat = half).
• Optimizer::learningRate = 0.01h — the h suffix is a half-precision literal.
• The companion atomic helper is named InterlockedAddF16Emulated.
• The "complete code" the tutorial links to (neural-shading-s25/.../mlp-training) targets half-precision MLPs.

Test plan

• Render section 3 of the tutorial mentally: the new subsection appears just after the "## 3. Forward Pass Architecture Design" heading, before "### 3.1 Top-Level Network Definition", so subsequent uses of NFloat and InterlockedAddF16Emulated have a definition the reader can trace back to without leaving the page.
• Sphinx build via CI (markdown-only change, no syntax-sensitive constructs).

Fixes #196

[jhelferty-nv]

@nv-slang-bot Can you please update this branch from the main one? Also, is this PR still consistent with the current state of things, or has the documentation and/or samples being referenced been updated since?

[nv-slang-bot]

@jhelferty-nv Done — both parts below.

1. Branch updated from main ✅

I merged the latest main into fix/issue-196-clarify-nfloat-helpers (the branch was 31 commits behind). Clean merge, no conflicts — the doc file is untouched on main, so the merge only pulled in unrelated site changes. New head is b1104a89; main is now fully an ancestor of the branch. The net change vs main is still exactly the original +16 / −0 in docs/auto-diff-tutorial-2.md. CI should re-run on the updated head.

2. Consistency re-verify — still consistent for the doc; one caveat on the linked sample

The doc change itself is still correct and correctly placed:

• docs/auto-diff-tutorial-2.md has not changed on main since this PR branched — main never added these declarations, so the PR is neither redundant nor stale.
• The new "Conventions Used in the Code Listings" subsection still slots correctly under ## 3. Forward Pass Architecture Design, immediately before ### 3.1 Top-Level Network Definition.
• NFloat and InterlockedAddF16Emulated still appear where the PR expects them (the section-3 listings), and the InterlockedAddF16Emulated stub signature still matches the two call sites in the tutorial (the biasesGrad + i, dResult.data[i], originalValue calls). NFloat = half is consistent with the tutorial's own prose ("we are using half type … for better throughput"), half data[N] in MLVec, and the 0.01h half literal.

Caveat worth flagging (pre-existing, non-blocking): the PR justifies NFloat = half partly via the linked companion repo shader-slang/neural-shading-s25 → hardware-acceleration/mlp-training. That repo/path still exists, but its current code does not match the tutorial's stubs:

• mlp-training/common.slang declares public typealias NFloat = float; (not half), and the sample does its atomic accumulation with Atomic<NFloat>* + .add(), not a helper named InterlockedAddF16Emulated.
• InterlockedAddF16Emulated does not appear anywhere in neural-shading-s25 (repo-wide code search: 0 hits).
• A sibling directory, hardware-acceleration/mlp-training-coopvec/, does use typealias NFloat = half; — but it also has no InterlockedAddF16Emulated.
• This is not a "changed since the PR" situation: mlp-training/common.slang was last modified 2025-08-08, which predates this PR (2026-05-27), so the sample and the tutorial never matched on these two specifics.

Since the doc's new stubs are self-contained and explicitly say to "treat them as if declared once at file scope," the PR still stands on its own as a readability fix for #196. The only thing I'd surface for your call: the sentence claims the identifiers' "full implementations live in the companion example repository," and for InterlockedAddF16Emulated (and for half specifically) that's not literally true of the linked mlp-training path today. If you'd like, I can soften that wording (e.g. point at mlp-training-coopvec for the half variant, or drop the "full implementations live in" phrasing for the emulated-atomic helper). Left as-is for now since it doesn't block the clarification.

I have not marked this ready-for-review or merged — that stays with you.

_{🤖 Generated by an automated Slang coworker — may be inaccurate. A human maintainer should verify.}

[jhelferty-nv]

@nv-slang-bot Would the sample code in this documentation still compile. or has the API changed sufficiently that it no longer would with, e.g., slangpy 0.43.1?

[jhelferty-nv]

@nv-slang-bot see my earlier reply

[nv-slang-bot]

@jhelferty-nv Good question — I checked this concretely rather than by eye. Short answer: yes, it still compiles; no relevant API/language drift affecting this tutorial.

First, a framing note: every code listing in this tutorial is Slang shader code (hlsl fences) — there is no SlangPy Python host code in the tutorial, so compatibility of the shown code comes down to whether the bundled Slang compiler accepts it. slangpy 0.43.1 (released 2026-07-16, the current latest) bundles Slang release v2026.12, so I tested against that.

What I verified (with slangc 2026.12, the compiler in 0.43.1):

1. The complete, runnable sample — the linked neural-shading-s25/hardware-acceleration/mlp-training — compiles unchanged. Both compute entry points (learnGradient, adjustParameters) build to valid SPIR-V and pass SPIR-V validation. The only diagnostic is a benign __SLANG_APPLE__-undefined preprocessor warning on the non-Apple path (it gates a Metal-only [require]), not an error.

2. Every language construct the tutorial's listings exercise is accepted by 2026.12: the autodiff surface ([Differentiable], [BackwardDerivativeOf(...)], DifferentialPair<T>, no_diff, bwd_diff, IDifferentiable), raw pointer parameters (NFloat*), Atomic<T> with .add, generics, and the compute-shader attributes ([shader("compute")], [numthreads]). I confirmed the tutorial's specific [BackwardDerivativeOf(fn)] spelling (the reverse-reference form placed on the derivative) compiles to SPIR-V on 2026.12 with a targeted repro.

One honest caveat about the listings themselves: the in-page snippets are elided teaching excerpts — several bodies are shown as { ... } or // construct ..., and matMulAdd / matMulTransposed / outerProductAccumulate are forward-declared with their bodies left to the companion repo. So the snippets aren't meant to be copy-pasted as a standalone compilable program; the complete compilable form is the linked sample.

Bottom line: the complete linked sample compiles unchanged with slangpy 0.43.1 / Slang 2026.12, and the exact Slang constructs shown in the tutorial remain accepted — I hit no identifier or signature incompatibility in either the full sample or the targeted reproducer. No API change affects this tutorial.

_{🤖 Generated by an automated Slang coworker — may be inaccurate. A human maintainer should verify.}