The full-stage+kv dump (1.7GB/file, synchronous in-forward) hung/crashed a scheduler child. Trim to the residual-stream trajectory (attn_in/attn_out per layer) + q_all + final_hidden (~tens of MB/forward) — enough to localize the first divergent layer (Stage 1). Drop dense-space kv_cache/topk (not comparable anyway) and the MoE substages. Dumps go to local NVMe (/ssd) to avoid beegfs stall. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Code Structure
eval: The evaluation utilities.lang: The frontend language.multimodal_gen: Inference framework for accelerated image/video generation.srt: The backend engine for running local models. (SRT = SGLang Runtime).test: The test utilities.api.py: The public APIs.bench_offline_throughput.py: Benchmark the performance in the offline mode.bench_one_batch.py: Benchmark the latency of running a single static batch without a server.bench_one_batch_server.py: Benchmark the latency of running a single batch with a server.bench_serving.py: Benchmark online serving with dynamic requests.check_env.py: Check the environment variables and dependencies.global_config.py: The global configs and constants.launch_server.py: The entry point for launching a local server.profiler.py: The profiling entry point to send profile requests.utils.py: Common utilities.version.py: Version info.