#!/bin/bash
export HCCL_CONNECT_TIMEOUT=1800
export CUDA_DEVICE_MAX_CONNECTIONS=1
export NPU_ASD_ENABLE=0
NPUS_PER_NODE=8
MASTER_ADDR=localhost
MASTER_PORT=6000
NNODES=1
NODE_RANK=0
WORLD_SIZE=$(($NPUS_PER_NODE*$NNODES))
CKPT_SAVE_DIR="your model save ckpt path"
DATA_PATH="your data path"
TOKENIZER_PATH="your tokenizer path"
CKPT_LOAD_DIR="your model ckpt path"
TP=1
PP=1
CP=1
MBS=1
GBS=64
SEQ_LENGTH=4096
TRAIN_ITERS=2000
CP_TYPE='ulysses_cp_algo'
ROUTER_BALANCING_TYPE='softmax_topk'
DISTRIBUTED_ARGS="
--local_worker_num $NPUS_PER_NODE \
--worker_num $WORLD_SIZE \
--node_rank $NODE_RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT \
--log_dir="msrun_log" \
--join=True
"
OPTIMIZE_ARGS="
--use-flash-attn \
--use-fused-rotary-pos-emb \
--use-rotary-position-embeddings \
--use-fused-swiglu \
--use-fused-rmsnorm \
--no-masked-softmax-fusion \
--use-distributed-optimizer
"
TRAIN_ARGS="
--micro-batch-size ${MBS} \
--global-batch-size ${GBS} \
--lr 1.25e-6 \
--lr-decay-style cosine \
--min-lr 1.25e-7 \
--weight-decay 1e-1 \
--lr-warmup-fraction 0.01 \
--attention-dropout 0.0 \
--init-method-std 0.01 \
--hidden-dropout 0.0 \
--clip-grad 1.0 \
--adam-beta1 0.9 \
--adam-beta2 0.95 \
--initial-loss-scale 4096 \
--seed 42 \
--bf16 \
--train-iters ${TRAIN_ITERS} \
--seq-length ${SEQ_LENGTH} \
--no-shared-storage
"
MODEL_PARALLEL_ARGS="
--tensor-model-parallel-size ${TP} \
--pipeline-model-parallel-size ${PP} \
--context-parallel-size ${CP} \
--context-parallel-algo ${CP_TYPE} \
"
GPT_ARGS="
--use-mcore-models \
--spec mindspeed_llm.tasks.models.spec.qwen3_spec layer_spec \
--qk-layernorm \
--kv-channels 128 \
--tokenizer-name-or-path ${TOKENIZER_PATH} \
--max-position-embeddings ${SEQ_LENGTH} \
--num-layers 36 \
--hidden-size 2560 \
--ffn-hidden-size 9728 \
--num-attention-heads 32 \
--tokenizer-type PretrainedFromHF \
--make-vocab-size-divisible-by 1 \
--padded-vocab-size 151936 \
--rotary-base 1000000 \
--disable-bias-linear \
--position-embedding-type rope \
--normalization RMSNorm \
--swiglu \
--attention-softmax-in-fp32 \
--no-gradient-accumulation-fusion \
--group-query-attention \
--num-query-groups 8
"
DATA_ARGS="
--data-path $DATA_PATH \
--split 100,0,0
"
OUTPUT_ARGS="
--log-interval 1 \
--save-interval ${TRAIN_ITERS} \
--eval-interval ${TRAIN_ITERS} \
--eval-iters 0 \
--no-load-optim \
--no-load-rng
"
msrun $DISTRIBUTED_ARGS pretrain_gpt.py \
$GPT_ARGS \
$DATA_ARGS \
$MOE_ARGS \
$OUTPUT_ARGS \
$OPTIMIZE_ARGS \
$TRAIN_ARGS \
$MODEL_PARALLEL_ARGS \
--load ${CKPT_LOAD_DIR} \
--save ${CKPT_SAVE_DIR} \
--distributed-backend nccl \
--ai-framework mindspore \
| tee logs/train_mcore_qwen3_4b.log