DeepInfer/tests/neuron/run_all.sh
whn09 9c8c85d83d Neuron: per-layer region graphs + vllm-neuron#71 NKI kernels (issues #10, #11, #13, #25)
- Decode runs eagerly and compiles per-layer regions (attention half, MoE) with stage boundaries
  (neuron_ops/regions.py, DEEPINFER_NEURON_GRAPH_MODE=regions); layer KV views are sliced from the
  roots inside the graph (_LazyKVCache).
- vllm-neuron#71 NKI kernels (Apache-2.0, vendored under neuron_ops/nki/ with attribution), called via
  torch_neuronx.nki_hop.wrap_nki: blockquant (fp8/fp4 GEMMs incl. grouped einsum, MoE and shared
  expert on bf16 activations), sparse_attn / index_score / compress_pool (nki_attention.py),
  hc_mixes / hc_expand / hc_collapse / hc_attn_out / rmsnorm / swiglu (nki_hc.py, nki_norm.py).
- Compile-safe formulations: row-major scales, no dtype bitcasts of graph inputs (uint8 weight
  tensors), whole-row KV stores, byte assembly in int32 narrowed once at the store, arithmetic int16
  scale packing, plain fma/rsqrt and bf16 F.linear under compile; default backend deepinfer_neuron
  (torch fp8 carried as uint8, avoiding NCC_EOCP001 with the kernels' OCP fp8).
- Host: tiny model 9/9 vs golden on all prompts; device: kernel tests pass (13 attention, 88 hc/norm);
  region decode graph compiles except the attention projection stage (being reduced).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-22 17:36:54 +08:00

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#!/bin/bash
# Neuron port test suite. Run after tests/neuron/setup_trn2.sh.
#
# bash tests/neuron/run_all.sh cpu # host-only: kernel unit tests + end-to-end vs golden (~1 h)
# CORES=0-7 bash tests/neuron/run_all.sh device # NeuronCore tests on the given logical cores
# CORES=0-7 bash tests/neuron/run_all.sh all
# bash tests/neuron/run_all.sh cpu deep_gemm flash_mla # only selected stages
#
# Device stages use the first core of CORES for single-core runs and CORES for multi-rank deep_ep
# (world sizes 2/4/8 limited by the core count). They refuse to start if those cores are in use.
# Logs: $WORK/test_logs/<timestamp>/<stage>.log; a PASS/FAIL table is printed at the end.
set -uo pipefail
REPO="$(cd "$(dirname "${BASH_SOURCE[0]}")/../.." && pwd)"
WORK="${WORK:-$HOME/di}"
MODE="${1:-cpu}"; shift || true
ONLY=("$@")
CORES="${CORES:-0-7}"
LOGDIR="$WORK/test_logs/$(date +%Y%m%d-%H%M%S)"
mkdir -p "$LOGDIR"
# shellcheck disable=SC1091
source "$WORK/venv/bin/activate"
cd "$REPO" || exit 1
VENDOR="$REPO/deepinfer/neuron_ops/vendor"
T="$REPO/tests/neuron"
export DEEPINFER_ACCELERATOR=neuron
# Kernel unit tests compare bit-for-bit against references quantizing to the e4m3fn range (448); the end-to-end
# stages run the default trn2 e4m3 range (224, deepinfer/neuron_ops/fp8.py) and compare against the golden.
UNIT_FP8_MAX="${UNIT_FP8_MAX:-448}"
declare -a SUMMARY=()
first_core() { echo "${CORES%%[-,]*}"; }
core_count() { python3 - "$CORES" <<'EOF'
import sys
n = 0
for part in sys.argv[1].split(","):
a, _, b = part.partition("-")
n += (int(b) - int(a) + 1) if b else 1
print(n)
EOF
}
selected() { [ ${#ONLY[@]} -eq 0 ] && return 0; for s in "${ONLY[@]}"; do [ "$s" = "$1" ] && return 0; done; return 1; }
run() { # run <stage> <command...>
local stage="$1"; shift
selected "$stage" || return 0
echo "=== $stage"
local t0=$SECONDS
local fp8_max="$UNIT_FP8_MAX"
case "$stage" in e2e_*|device_diff) fp8_max="${DEEPINFER_NEURON_FP8_MAX:-224}" ;; esac
if DEEPINFER_NEURON_FP8_MAX="$fp8_max" "$@" > "$LOGDIR/$stage.log" 2>&1; then r=PASS; else r=FAIL; fi
SUMMARY+=("$(printf '%-6s %-28s %5ss %s' "$r" "$stage" $((SECONDS - t0)) "$LOGDIR/$stage.log")")
echo " $r ($((SECONDS - t0))s)"
[ "$r" = FAIL ] && tail -5 "$LOGDIR/$stage.log" | sed 's/^/ | /'
}
cores_free() { # are the NeuronCores in $CORES free? (other cores may be busy)
python3 - "$CORES" <<'EOF'
import json, subprocess, sys
want = set()
for part in sys.argv[1].split(","):
a, _, b = part.partition("-")
want.update(range(int(a), int(b) + 1) if b else [int(a)])
busy = [d["neuron_device"] for d in json.loads(subprocess.check_output(["neuron-ls", "-j"]))
if d.get("neuron_processes") and want & set(d["neuroncore_ids"])]
if busy:
print(f"NeuronCores in {sys.argv[1]} are in use (devices {busy}); not starting device stages")
sys.exit(1 if busy else 0)
EOF
}
cpu_stages() {
export DEEPINFER_NEURON_DEVICE=cpu
run deep_gemm env PYTHONPATH="$VENDOR" python "$T/deep_gemm/test_deep_gemm_neuron.py"
run deep_gemm_tk env PYTHONPATH="$VENDOR" python "$T/deep_gemm/test_interop_tile_kernels.py"
run flash_mla bash -c "cd $T/flash_mla && PYTHONPATH=$VENDOR python test_flash_mla.py"
run deep_select bash -c "cd $T/flash_mla && PYTHONPATH=$VENDOR python test_deep_select.py"
run tilelang_stub bash -c "cd $T/flash_mla && PYTHONPATH=$VENDOR python test_tilelang.py"
run tile_kernels python -m pytest -q -p no:cacheprovider "$T/tile_kernels/test_tile_kernels.py"
for ws in 1 2 4; do
run "deep_ep_ws$ws" python "$T/deep_ep/test_ep.py" --num-processes $ws --port $((29531 + ws))
run "engram_ws$ws" python "$T/deep_ep/test_engram.py" --num-processes $ws --port $((29541 + ws))
run "bucket_ws$ws" python "$T/deep_ep/test_bucket.py" --num-processes $ws --port $((29551 + ws))
done
run sampling_kat env PYTHONPATH="$REPO" python "$T/sampling/kat.py"
run sampling_check env PYTHONPATH="$REPO" python "$T/sampling/check2.py"
# Upstream interface tests of tilelang_ops (compare the Neuron backend against the *_ref implementations).
for m in norm store_kv_cache load_paged_kv_cache fused_transform compress state_cache get_kv_index kv_index_cat \
swa_index candidate_blocks flash_mla_utils gather prepare_v4_decode_metadata random_sampling fused_sample \
sampler sum_smaller_probs structure_output; do
run "tl_$m" env PYTHONPATH="$T" python -m pytest -q -p no:cacheprovider --noconftest -p nie_skip \
"deepinfer/model_executor/layers/tilelang_ops/$m.py" -k "not benchmark and not 129280-4096"
done
run e2e_cpu python examples/neuron/run_deepinfer_tiny.py --device cpu --threads 32 --num-kv-blocks 32 \
--out "$WORK/e2e_cpu" --golden-dir "$WORK/golden" --hf-ckpt "$WORK/tiny_ckpt" --compare
}
device_stages() {
cores_free || return 0
local c0 n
c0="$(first_core)"; n="$(core_count)"
export DEEPINFER_NEURON_DEVICE=neuron
run device_primitives env NEURON_RT_VISIBLE_CORES="$c0" python "$T/device/test_device_primitives.py"
run nki_hc env NEURON_RT_VISIBLE_CORES="$c0" python -m pytest -q -p no:cacheprovider "$T/compile/test_nki_hc.py"
for ws in 2 4 8 16; do
[ "$ws" -le "$n" ] || continue
for t in ep engram bucket; do
run "${t}_neuron_ws$ws" env DEEP_EP_TEST_DEVICE=neuron DEEP_EP_TEST_CORE_BASE="$c0" \
python "$T/deep_ep/test_$t.py" --num-processes $ws --port $((29600 + 10 * ws + ${#t}))
done
done
run e2e_neuron env NEURON_RT_VISIBLE_CORES="$c0" CUDA_VISIBLE_DEVICES="$c0" MASTER_PORT=29733 \
python examples/neuron/run_deepinfer_tiny.py --device neuron --num-kv-blocks 32 \
--out "$WORK/e2e_neuron" --golden-dir "$WORK/golden" --hf-ckpt "$WORK/tiny_ckpt" --compare
run device_diff env NEURON_RT_VISIBLE_CORES="$c0" CUDA_VISIBLE_DEVICES="$c0" MASTER_PORT=29734 \
python examples/neuron/device_diff.py --prompts short --num-kv-blocks 32 \
--out "$WORK/device_diff" --golden-dir "$WORK/golden" --hf-ckpt "$WORK/tiny_ckpt"
}
case "$MODE" in
cpu) cpu_stages ;;
device) device_stages ;;
all) cpu_stages; device_stages ;;
*) echo "usage: $0 cpu|device|all [stage...]"; exit 2 ;;
esac
echo; echo "===== summary ($LOGDIR)"
printf '%s\n' "${SUMMARY[@]}"
! printf '%s\n' "${SUMMARY[@]}" | grep -q '^FAIL'