Support stage1-2 MoE resume on g0050

This commit is contained in:
yi_lu
2026-07-16 09:23:10 +08:00
parent 07e108388d
commit 1329bb9506
2 changed files with 159 additions and 2 deletions

View File

@@ -0,0 +1,119 @@
#!/usr/bin/env bash
set -euo pipefail
# Host path layout on g0050 after /ssd was replaced by /data.
HOST_WORKSPACE="${HOST_WORKSPACE:-/data/workspace/yi}"
CONTAINER_WORKSPACE="${CONTAINER_WORKSPACE:-/ssd/workspace/yi}"
REPO_ROOT="${REPO_ROOT:-${CONTAINER_WORKSPACE}/laoyao_2b_moe}"
HOST_REPO_ROOT="${HOST_REPO_ROOT:-${HOST_WORKSPACE}/laoyao_2b_moe}"
IMAGE="${IMAGE:-laoyao/nemo-megatron:26.06-flashattn4}"
RUN_NAME="${RUN_NAME:-stage1_2_8192_8gpu_dp8_mbs14_full_recompute_general55_code15_math15_science15}"
RUN_DIR="${RUN_DIR:-${REPO_ROOT}/runs/${RUN_NAME}}"
CKPT_DIR="${CKPT_DIR:-${RUN_DIR}/checkpoints}"
TENSORBOARD_DIR="${TENSORBOARD_DIR:-${RUN_DIR}/tensorboard}"
LOAD_DIR="${LOAD_DIR:-${CKPT_DIR}}"
DATA_MANIFEST="${DATA_MANIFEST:-${CONTAINER_WORKSPACE}/laoyao_2b_moe_pretraining_dataset/megatron_bridge/stage2_8192_by_category_general55_code15_math15_science15_100b_v1/stage1_2_weighted_manifest.json}"
VALIDATION_PREFIX="${VALIDATION_PREFIX:-${REPO_ROOT}/dataset/val/megatron_8192_glm52/heldout_2p8k_text_document}"
TRAIN_ITERS="${TRAIN_ITERS:-281245}"
SEQ_LENGTH="${SEQ_LENGTH:-8192}"
MICRO_BATCH_SIZE="${MICRO_BATCH_SIZE:-14}"
GLOBAL_BATCH_SIZE="${GLOBAL_BATCH_SIZE:-112}"
SAVE_INTERVAL="${SAVE_INTERVAL:-2500}"
EVAL_INTERVAL="${EVAL_INTERVAL:-15000}"
EVAL_ITERS="${EVAL_ITERS:-10}"
DATASET_WORKERS="${DATASET_WORKERS:-4}"
LR="${LR:-3.0e-4}"
MIN_LR="${MIN_LR:-5.0e-6}"
WARMUP_FRACTION="${WARMUP_FRACTION:-0.01}"
LOG_FILE="${LOG_FILE:-/tmp/laoyao_stage1_2_8192_8gpu_mbs14.log}"
CONTAINER_NAME="${CONTAINER_NAME:-laoyao_stage1_2_pretrain}"
HOST_DATA_MANIFEST="${DATA_MANIFEST/${CONTAINER_WORKSPACE}/${HOST_WORKSPACE}}"
HOST_LOAD_DIR="${LOAD_DIR/${CONTAINER_WORKSPACE}/${HOST_WORKSPACE}}"
HOST_VALIDATION_PREFIX="${VALIDATION_PREFIX/${CONTAINER_WORKSPACE}/${HOST_WORKSPACE}}"
HOST_CKPT_DIR="${CKPT_DIR/${CONTAINER_WORKSPACE}/${HOST_WORKSPACE}}"
HOST_TENSORBOARD_DIR="${TENSORBOARD_DIR/${CONTAINER_WORKSPACE}/${HOST_WORKSPACE}}"
if [[ ! -d "${HOST_REPO_ROOT}" ]]; then
echo "ERROR: host repo dir not found: ${HOST_REPO_ROOT}" >&2
exit 1
fi
if [[ ! -f "${HOST_DATA_MANIFEST}" ]]; then
echo "ERROR: host data manifest not found: ${HOST_DATA_MANIFEST}" >&2
exit 1
fi
if [[ ! -d "${HOST_LOAD_DIR}" ]]; then
echo "ERROR: host load checkpoint dir not found: ${HOST_LOAD_DIR}" >&2
exit 1
fi
if [[ ! -f "${HOST_VALIDATION_PREFIX}.idx" ]]; then
echo "WARNING: host validation prefix not found: ${HOST_VALIDATION_PREFIX}" >&2
fi
if docker ps --format '{{.Names}}' | grep -Fxq "${CONTAINER_NAME}"; then
echo "ERROR: container already running: ${CONTAINER_NAME}" >&2
exit 1
fi
mkdir -p "${HOST_CKPT_DIR}" "${HOST_TENSORBOARD_DIR}"
echo "Starting Laoyao 2B MoE stage1-2 pretraining"
echo "host_workspace: ${HOST_WORKSPACE}"
echo "container_workspace: ${CONTAINER_WORKSPACE}"
echo "repo: ${REPO_ROOT}"
echo "data_manifest: ${DATA_MANIFEST}"
echo "save_checkpoint_dir: ${CKPT_DIR}"
echo "load_checkpoint_dir: ${LOAD_DIR}"
echo "load_checkpoint_iteration: $(cat "${HOST_LOAD_DIR}/latest_checkpointed_iteration.txt" 2>/dev/null || echo unknown)"
echo "train_iters: ${TRAIN_ITERS}"
echo "log_file: ${LOG_FILE}"
cd "${HOST_REPO_ROOT}"
nohup docker run --rm --name "${CONTAINER_NAME}" \
--gpus all \
--ipc=host \
--network=host \
--ulimit memlock=-1 \
--ulimit stack=67108864 \
-e CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 \
-v "${HOST_WORKSPACE}:${CONTAINER_WORKSPACE}" \
-w "${REPO_ROOT}" \
"${IMAGE}" \
bash -lc "torchrun --nproc_per_node=8 \
training/megatron_bridge/laoyao_2b_moe_pretrain.py \
--data-manifest '${DATA_MANIFEST}' \
--validation-prefix '${VALIDATION_PREFIX}' \
--seq-length '${SEQ_LENGTH}' \
--train-iters '${TRAIN_ITERS}' \
--micro-batch-size '${MICRO_BATCH_SIZE}' \
--global-batch-size '${GLOBAL_BATCH_SIZE}' \
--tensor-parallel 1 \
--pipeline-parallel 1 \
--expert-parallel 1 \
--context-parallel 1 \
--split 999,1,0 \
--dataset-workers '${DATASET_WORKERS}' \
--lr '${LR}' \
--min-lr '${MIN_LR}' \
--warmup-fraction '${WARMUP_FRACTION}' \
--save-dir '${CKPT_DIR}' \
--load-dir '${LOAD_DIR}' \
--tensorboard-dir '${TENSORBOARD_DIR}' \
--save-interval '${SAVE_INTERVAL}' \
--keep-last-checkpoints 10 \
--log-interval 10 \
--eval-interval '${EVAL_INTERVAL}' \
--eval-iters '${EVAL_ITERS}' \
--use-distributed-optimizer \
--overlap-grad-reduce \
--overlap-param-gather \
--recompute-granularity full \
--recompute-method uniform \
--recompute-num-layers 1" \
> "${LOG_FILE}" 2>&1 &
echo "Launched. Check with:"
echo " tail -f ${LOG_FILE}"
echo " docker ps"

View File

@@ -44,7 +44,7 @@ def _token_weights_from_manifest(prefix_list: list[str], manifest: dict) -> list
token_by_prefix = {}
for result in manifest.get("results") or []:
output_prefix = result.get("output_prefix")
tokens = result.get("tokens_estimated_from_int32_bin")
tokens = result.get("tokens_estimated_from_int32_bin") or result.get("tokens")
if output_prefix and tokens:
token_by_prefix[str(output_prefix) + "_text_document"] = float(tokens)
@@ -55,6 +55,42 @@ def _token_weights_from_manifest(prefix_list: list[str], manifest: dict) -> list
return _normalize_weights(weights)
def _target_mix_weights_from_manifest(prefix_list: list[str], manifest: dict) -> list[float] | None:
target_mix = manifest.get("target_mix") or {}
if not target_mix:
return None
prefix_to_category = {}
prefix_to_tokens = {}
category_totals = {}
for result in manifest.get("results") or []:
output_prefix = result.get("output_prefix")
category = result.get("mixture_category") or result.get("category")
tokens = result.get("tokens")
if not output_prefix or not category or not tokens:
continue
prefix = str(output_prefix) + "_text_document"
prefix_to_category[prefix] = str(category)
prefix_to_tokens[prefix] = float(tokens)
category_totals[str(category)] = category_totals.get(str(category), 0.0) + float(tokens)
if not prefix_to_category:
return None
raw_weights = []
for prefix in prefix_list:
category = prefix_to_category.get(prefix)
tokens = prefix_to_tokens.get(prefix)
category_total = category_totals.get(category or "", 0.0)
target_ratio = float(target_mix.get(category or "", 0.0))
if not category or not tokens or category_total <= 0 or target_ratio <= 0:
return None
raw_weights.append(target_ratio * (tokens / category_total))
return _normalize_weights(raw_weights)
def _target_mix_weights_from_category_stats(
prefix_list: list[str],
category_stats_path: Path,
@@ -91,7 +127,9 @@ def load_data_blend(args: argparse.Namespace) -> tuple[list[str], list[float] |
raise ValueError(f"{manifest_path} has no ok_prefixes")
prefix_list = [str(prefix) for prefix in prefixes]
category_stats_path = manifest_path.with_name("prefix_category_stats.json")
weights = _target_mix_weights_from_category_stats(prefix_list, category_stats_path)
weights = _target_mix_weights_from_manifest(prefix_list, manifest)
if weights is None:
weights = _target_mix_weights_from_category_stats(prefix_list, category_stats_path)
if weights is None:
weights = _token_weights_from_manifest(prefix_list, manifest)
return (prefix_list, weights)