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cortex/crates/neuron/src/harness/tp/rpc.rs
rob thijssen fa013505d1
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fix(neuron): chunked TP-vision prefill + pre-flight VRAM guard
agent-0 sent a ~13k-token prompt + image; the TP vision prefill was
single-shot, so it tried to materialise activations for all 12,960
positions at once and OOM'd rank 1 mid-forward. Rank 1 died before
issuing its row-parallel AllReduce, stranding rank 0 on the collective
(it hung holding the pool lock). The text path survives the same size
because it chunks the prefill.

Chunk the vision prefill the same way:

- TpQwen3_5ForCausalLM::prefill_with_images_chunked encodes the image(s)
  once, then walks the pre-expanded prompt in prefill_chunk_tokens()
  windows, splicing the patch-embedding rows into whichever chunk(s)
  carry <|image_pad|> positions (pure-text chunks take the plain
  forward). Activation is bounded by the chunk, not the prompt.
- Every rank runs the identical chunk sequence (chunk_size threaded
  through GenerateStepWithImages / TpForwardLogitsWithImages /
  generate_step_with_images), so the per-chunk AllReduces stay paired
  across ranks with no extra sync — the KV cache accumulates via the
  growing offset, only the last chunk's logits are kept.

Pre-flight guard (validate_vision_prefill): even chunked, a long
prompt's KV cache can exhaust VRAM mid-forward, and on TP that hangs
the collective. Reject up front with a clean InsufficientVram when the
estimated footprint exceeds free VRAM, so a doomed request fails fast
instead of hanging the daemon. Heuristic + tunable
(NEURON_VISION_PREFILL_MB_PER_1K_TOKENS / _BASE_MB); default permissive
so the now-working 12,960-token case still passes. Applied to every
vision path (single-GPU + TP); single-GPU vision stays single-shot for
now, so the guard is its protection until it's chunked too.

Tests: pre-flight guard behaviour; RPC round-trip carries chunk_size.
The chunked forward is cuda-gated — CI CUDA type-check validates it.

Refs #16 / TP-vision. Operational note: a TP rank OOM still hangs the
daemon (needs restart); making a worker failure abort the leader's
collective is separate, broader TP hardening.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-04 17:21:36 +03:00

312 lines
12 KiB
Rust

//! Wire protocol between the neuron leader process and its
//! `--worker` subprocesses.
//!
//! Every frame is one newline-delimited JSON object on the worker's
//! stdin (request) or stdout (response). Both directions are tagged
//! sum types from the start so new ops in Stage 7b/7c slot in without
//! breaking compatibility — no "14 message types and a version field"
//! drift later. Adding a new variant is the canonical way to evolve
//! the protocol; existing peers that don't recognise an op return
//! `WorkerResponse::Error { kind: "unknown_op", .. }`.
//!
//! The serialised shape uses `tag = "op"` so a request looks like:
//! {"op":"ping"}
//! {"op":"init","comm_id":"a1b2..."}
//! and a response:
//! {"op":"pong","rank":0,"world_size":2,"cuda_device":0}
//! {"op":"error","kind":"nccl_init_failed","message":"..."}
use serde::{Deserialize, Serialize};
/// Leader → worker. Worker handles one at a time; replies with exactly
/// one `WorkerResponse` per request.
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "op", rename_all = "snake_case")]
pub enum WorkerRequest {
/// Liveness probe. Worker replies with `Pong` containing its own
/// identity. Used by the leader to confirm the subprocess is up
/// and ready before kicking off any heavier work.
Ping,
/// One-shot NCCL communicator setup. The leader generates the
/// `comm_id` once (rank 0 of NCCL), broadcasts it to every worker
/// via this message, then every rank (leader included) calls
/// `Comm::from_rank` with the same id — NCCL blocks until all
/// `world_size` ranks check in. The hex-encoded bytes are the
/// canonical `cudarc::nccl::Id::internal()` content.
Init {
/// Hex-encoded NCCL id bytes (128 bytes → 256 hex chars).
comm_id: String,
},
/// Sanity check: after Init, every rank runs an `all_reduce` over
/// a sentinel value (`1u32`). The expected sum is `world_size`.
/// Worker replies with the observed value so the leader can verify
/// the NCCL handshake is genuinely live, not just configured.
NcclSanityCheck,
/// Load this rank's shard of a dense Qwen3 model from mmaped
/// safetensors. The same `safetensors_paths` list is sent to every
/// rank — the ShardedVarBuilder reads only the rank-local slice of
/// each tensor at materialisation time, so the worker's VRAM
/// footprint is `1 / world_size` of the full model (plus replicated
/// embedding/norm/lm_head).
LoadDenseShard {
/// Caller-supplied id for later `GenerateStep` / `UnloadModel`
/// lookups. Typically the HF model id verbatim.
model_id: String,
/// JSON-serialised `candle_transformers::models::qwen3::Config`
/// — the same blob the leader parsed from the HF cache's
/// `config.json`. Threaded through verbatim so the worker uses
/// identical hyperparameters.
config_json: String,
/// Absolute paths the worker should mmap. The same set on every
/// rank; ShardedVarBuilder slices into them per rank.
safetensors_paths: Vec<String>,
/// Optional in-situ quantization dtype (e.g. "q5k", "q8_0",
/// "q6k"). When set, each linear-layer weight is quantized
/// at load time to the named ggml format — saves ~3-5x vs
/// bf16/f16 at the cost of some accuracy. `None` keeps the
/// weights in the on-disk dtype (typically bf16).
#[serde(default)]
quant: Option<String>,
},
/// Run one forward step on this rank's loaded model. The worker
/// reaches into its NCCL Comm for the row-parallel `AllReduce`s
/// inside the model — and so blocks on every other rank issuing the
/// same op. The leader does *not* receive logits back over RPC; it
/// runs its own rank-0 forward in parallel and uses its own logits
/// for sampling.
GenerateStep {
model_id: String,
/// Input token ids for this step. For prefill, the whole prompt;
/// for decode, a single token. Identical on every rank.
tokens: Vec<u32>,
/// KV cache offset (count of tokens already in the cache before
/// this step).
offset: usize,
},
/// Like `GenerateStep` but the prefill carries image content. Every
/// rank preprocesses the same `image_data_uris` through its
/// *replicated* vision tower, splices the resulting patch embeddings
/// at `image_token_id` positions, and runs the forward — the
/// row-parallel `AllReduce`s still synchronise every rank. Because
/// the tower is replicated and `preprocess_data_uri` is
/// deterministic, the spliced hidden state is identical on every
/// rank, so no embedding broadcast is needed. Sent only for the
/// (single-shot) image-bearing prefill; decode steps use plain
/// `GenerateStep`. Worker replies with the same `GenerateStepOk`.
GenerateStepWithImages {
model_id: String,
tokens: Vec<u32>,
offset: usize,
/// `<|image_pad|>` sentinel id (248056 for Qwen3.6); splice
/// target in the expanded token stream.
image_token_id: u32,
/// Source image data URIs (`data:image/...;base64,...`), one per
/// image in prompt order. Each rank decodes + preprocesses these
/// identically; tens of KB each, so cheap over the stdin pipe.
image_data_uris: Vec<String>,
/// Prefill chunk size (tokens). Sent explicitly so every rank
/// walks the prompt in identical windows and the per-chunk
/// row-parallel collectives stay paired across ranks.
chunk_size: usize,
},
/// Reset the KV cache for this model on this rank. Sent at the
/// start of every inference so a fresh request doesn't accidentally
/// attend over the previous one's tokens.
ClearKvCache { model_id: String },
/// Drop this rank's shard for the given model. Releases the VRAM
/// the shard's weights occupied; subsequent `GenerateStep` calls
/// against the same `model_id` return an `Error`.
UnloadModel { model_id: String },
/// Worker should release resources and exit. Worker replies `Bye`
/// and then closes stdout / exits zero. The leader reaps the
/// child via the `tokio::process::Child` it kept.
Shutdown,
}
/// Worker → leader. Always exactly one of these per `WorkerRequest`.
#[derive(Debug, Clone, Serialize, Deserialize)]
#[serde(tag = "op", rename_all = "snake_case")]
pub enum WorkerResponse {
/// Reply to `Ping`. Carries enough identity for the leader to log
/// what it actually got back.
Pong {
rank: u32,
world_size: u32,
cuda_device: u32,
},
/// Reply to `Init`. Empty payload — success is the absence of
/// `Error`. NCCL's internal blocking handshake means by the time
/// this comes back, every other rank has also reached
/// `Comm::from_rank`.
InitOk,
/// Reply to `NcclSanityCheck`. The observed sum after a single
/// `all_reduce(SUM, 1u32)` across all ranks. The leader checks
/// this matches `world_size`.
NcclSanityResult { observed_sum: u32 },
/// Reply to `LoadDenseShard`. Empty payload — success is the
/// absence of `Error`. By the time this comes back, the rank's
/// `TpQwen3ForCausalLM` is constructed in memory and ready for
/// `GenerateStep`.
LoadDenseShardOk,
/// Reply to `GenerateStep`. Empty payload — workers don't ship
/// logits over the wire. The leader uses its own rank-0 logits;
/// workers only need to confirm the collective completed.
GenerateStepOk,
/// Reply to `ClearKvCache`. Empty payload.
KvCacheCleared,
/// Reply to `UnloadModel`. Empty payload. The named model is no
/// longer present on this rank.
Unloaded,
/// Reply to `Shutdown`. Worker exits immediately after writing this.
Bye,
/// Any request can produce this instead of its dedicated success
/// variant. `kind` is a machine-readable category so the leader
/// can branch on failure mode without string-matching `message`.
Error {
/// Short tag — `nccl_init_failed`, `unknown_op`, etc.
kind: String,
/// Human-readable detail for logs.
message: String,
},
}
#[cfg(test)]
mod tests {
use super::*;
fn roundtrip<T>(value: &T) -> T
where
T: Serialize + for<'de> Deserialize<'de>,
{
serde_json::from_str(&serde_json::to_string(value).expect("serialise"))
.expect("deserialise")
}
#[test]
fn request_ping_round_trip() {
let req = WorkerRequest::Ping;
let wire = serde_json::to_string(&req).unwrap();
assert_eq!(wire, r#"{"op":"ping"}"#);
match roundtrip(&req) {
WorkerRequest::Ping => {}
other => panic!("expected Ping, got {other:?}"),
}
}
#[test]
fn request_init_carries_hex_id() {
let req = WorkerRequest::Init {
comm_id: "deadbeef".into(),
};
let wire = serde_json::to_string(&req).unwrap();
assert_eq!(wire, r#"{"op":"init","comm_id":"deadbeef"}"#);
}
#[test]
fn request_generate_step_with_images_round_trip() {
let req = WorkerRequest::GenerateStepWithImages {
model_id: "Qwen/Qwen3.6-27B".into(),
tokens: vec![1, 2, 248056, 3],
offset: 0,
image_token_id: 248056,
image_data_uris: vec!["data:image/png;base64,AAA=".into()],
chunk_size: 512,
};
let wire = serde_json::to_string(&req).unwrap();
assert!(wire.contains(r#""op":"generate_step_with_images""#));
match roundtrip(&req) {
WorkerRequest::GenerateStepWithImages {
tokens,
image_token_id,
image_data_uris,
..
} => {
assert_eq!(tokens, vec![1, 2, 248056, 3]);
assert_eq!(image_token_id, 248056);
assert_eq!(image_data_uris.len(), 1);
}
other => panic!("expected GenerateStepWithImages, got {other:?}"),
}
}
#[test]
fn request_shutdown_round_trip() {
assert_eq!(
serde_json::to_string(&WorkerRequest::Shutdown).unwrap(),
r#"{"op":"shutdown"}"#
);
}
#[test]
fn response_pong_round_trip() {
let resp = WorkerResponse::Pong {
rank: 1,
world_size: 4,
cuda_device: 1,
};
let wire = serde_json::to_string(&resp).unwrap();
assert!(wire.contains(r#""op":"pong""#));
assert!(wire.contains(r#""rank":1"#));
assert!(wire.contains(r#""world_size":4"#));
match roundtrip(&resp) {
WorkerResponse::Pong {
rank,
world_size,
cuda_device,
} => {
assert_eq!(rank, 1);
assert_eq!(world_size, 4);
assert_eq!(cuda_device, 1);
}
other => panic!("expected Pong, got {other:?}"),
}
}
#[test]
fn response_error_carries_kind_and_message() {
let resp = WorkerResponse::Error {
kind: "nccl_init_failed".into(),
message: "could not bind device".into(),
};
let wire = serde_json::to_string(&resp).unwrap();
assert!(wire.contains(r#""op":"error""#));
assert!(wire.contains(r#""kind":"nccl_init_failed""#));
}
#[test]
fn response_sanity_result_round_trip() {
let resp = WorkerResponse::NcclSanityResult { observed_sum: 4 };
match roundtrip(&resp) {
WorkerResponse::NcclSanityResult { observed_sum } => {
assert_eq!(observed_sum, 4);
}
other => panic!("expected NcclSanityResult, got {other:?}"),
}
}
/// Unknown ops on the wire deserialise to an error rather than
/// silently mis-matching — confirms our `serde(tag = "op")`
/// configuration rejects unknowns instead of doing fuzzy matching.
#[test]
fn unknown_op_fails_to_parse() {
let result: Result<WorkerRequest, _> = serde_json::from_str(r#"{"op":"explode"}"#);
assert!(result.is_err(), "should reject unknown op, got {result:?}");
}
}