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Tighten and trim code comments

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This commit is contained in:
Daniel Han 2026-06-12 08:25:40 +00:00
commit b50eb8bc71
10 changed files with 125 additions and 133 deletions
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30
studio/scripts/provision_llama_cuda.sh
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@ -1,8 +1,8 @@
#!/usr/bin/env bash
# Build CUDA llama.cpp for Studio GGUF *inference* into ~/.unsloth/llama.cpp
# (resolver checks <dir>/build/bin/llama-server). Idempotent, best-effort, always
# exits 0. Exists because no aarch64+CUDA prebuilt covers NVIDIA ARM hosts
# (DGX Spark / GB10, N1X "RTX" laptops). Platform gotchas handled:
# (resolver checks <dir>/build/bin/llama-server). Idempotent, best-effort, exits
# 0. Exists because no aarch64+CUDA prebuilt covers NVIDIA ARM hosts (DGX Spark /
# GB10, N1X "RTX" laptops). Platform gotchas handled:
# * nvcc rejects gcc-15 -> force gcc-14 / g++-14 host compiler
# * glibc >= 2.41 vs CUDA < 13.3 -> install CUDA 13.3 (rsqrt header clash)
# * sm_121 (Blackwell) -> derive arch from the GPU's compute_cap
@ -13,7 +13,7 @@ LLAMA_DIR="${UNSLOTH_LLAMA_CPP_PATH:-$HOME/.unsloth/llama.cpp}"
SERVER="$LLAMA_DIR/build/bin/llama-server"
log() { printf ' - %s\n' "$*"; }
# CUDA shows up two ways: monolithic (libggml-cuda in ldd) or split (dlopen-ed
# Detect CUDA two ways: monolithic (libggml-cuda in ldd) or split (dlopen-ed
# libggml-cuda.so* beside the binary, missed by ldd). CPU-only builds ship no
# libggml-cuda.so, so its presence is the reliable signal.
is_cuda_server() {
@ -39,12 +39,12 @@ SUDO=""; [ "$(id -u)" -ne 0 ] && SUDO="sudo"
HAVE_APT=0; command -v apt-get >/dev/null 2>&1 && HAVE_APT=1
# 2. Base toolchain first, then gcc-14 (nvcc rejects gcc-15) in a SEPARATE apt
# transaction: gcc-14 is absent from default Ubuntu 22.04 / Debian 12 sources,
# which would abort a combined transaction and lose the base build tools too.
# transaction: gcc-14 is absent from default Ubuntu 22.04 / Debian 12 sources, so
# a combined transaction would abort and lose the base build tools too.
if [ "$HAVE_APT" -eq 1 ]; then
$SUDO apt-get update -y >/dev/null 2>&1 || true
# libcurl4-openssl-dev: -DLLAMA_CURL=ON needs it, and on the WSL deferred path
# setup.sh's GGUF dep install (which covers libcurl) was skipped.
# libcurl4-openssl-dev: -DLLAMA_CURL=ON needs it, and the WSL deferred path
# skips setup.sh's GGUF dep install that would otherwise provide libcurl.
$SUDO apt-get install -y --no-install-recommends \
build-essential cmake git curl ca-certificates libcurl4-openssl-dev >/dev/null 2>&1 || true
$SUDO apt-get install -y --no-install-recommends gcc-14 g++-14 >/dev/null 2>&1 || true
@ -89,7 +89,7 @@ fi
CUDA_HOME="$(dirname "$(dirname "$NVCC")")"
# CUDA + Linux dirs FIRST so the build uses Linux cmake/gcc/git, not Windows tools
# leaked in via WSL interop (/mnt/c); original PATH kept so nvidia-smi resolves.
# leaked in via WSL interop (/mnt/c). Keep original PATH so nvidia-smi resolves.
export PATH="$CUDA_HOME/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:$PATH"
export CUDAToolkit_ROOT="$CUDA_HOME"
@ -158,7 +158,7 @@ _cmake_configure() {
-DLLAMA_CURL=ON >/dev/null 2>&1
}
# A pre-existing build/ may carry a stale CMake cache (relocated dir: bad absolute
# paths + GGML_CUDA=OFF). Reuse it first (fast incremental); wipe only on failure.
# paths + GGML_CUDA=OFF). Reuse first (fast incremental); wipe only on failure.
if ! _cmake_configure; then
log "stale/incompatible CMake cache detected; wiping build dir for a clean CUDA configure"
rm -rf build
@ -166,10 +166,10 @@ if ! _cmake_configure; then
fi
# Also builds the targets unsloth-zoo's GGUF exporter needs (llama-mtmd-cli,
# llama-gguf-split). Jobs default to ~half the cores (full -j(nproc) CUDA builds
# trip thermal shutdowns on NVIDIA-ARM laptops like the N1X "RTX Spark") and are
# RAM-capped (~1.5 GB/nvcc job). Tune: UNSLOTH_LLAMA_BUILD_JOBS=N; re-runs resume.
# trip thermal shutdowns on NVIDIA-ARM laptops like the N1X "RTX Spark"), capped
# at ~1.5 GB/nvcc job. Tune: UNSLOTH_LLAMA_BUILD_JOBS=N; re-runs resume.
_ncpu="$(nproc 2>/dev/null || echo 4)"
# Honor a valid positive-int override; ignore junk/0 (cmake reads -j0 as "all cores").
# Honor a valid positive-int override; ignore junk/0 (cmake treats -j0 as all cores).
if [ -n "${UNSLOTH_LLAMA_BUILD_JOBS:-}" ] && [ "${UNSLOTH_LLAMA_BUILD_JOBS}" -ge 1 ] 2>/dev/null; then
JOBS="$UNSLOTH_LLAMA_BUILD_JOBS"
else
@ -188,7 +188,7 @@ command -v nice >/dev/null 2>&1 && _NICE="nice -n 19"
command -v ionice >/dev/null 2>&1 && _NICE="$_NICE ionice -c 3"
_cmake_build() {
# Only llama-server is REQUIRED: an old UNSLOTH_LLAMA_TAG pin may predate the
# helper targets, and those missing must not fail the whole provision.
# helper targets, whose absence must not fail the whole provision.
$_NICE cmake --build build -j"$JOBS" --target llama-server >/dev/null 2>&1
}
_cmake_build_extras() {
@ -200,7 +200,7 @@ _cmake_build_extras() {
if ! _cmake_build; then
# An interrupted build (thermal/power shutdown, common on this machine class)
# can leave a half-linked libggml-cuda.so that breaks the resume link
# (undefined ggml_cuda_op_* refs); wipe and rebuild clean once.
# (undefined ggml_cuda_op_* refs); wipe and rebuild clean.
log "build failed (likely interrupted/partial); wiping build dir and rebuilding clean"
rm -rf build
_cmake_configure || { log "cmake configure failed"; cd /; _restore_prev; exit 0; }