#!/bin/bash
export CUDA_DEVICE_MAX_CONNECTIONS=1
source "tests_extend/system_tests/env_npu.sh"
export STREAMS_PER_DEVICE=32
NPUS_PER_NODE=8
MASTER_ADDR=localhost
MASTER_PORT=6001
NNODES=1
NODE_RANK=0
WORLD_SIZE=$(($NPUS_PER_NODE*$NNODES))
CKPT_DIR=./ckpt_llama
DATA_PATH="/home/dataset/llama2/alpaca_text_document"
TOKENIZER_MODEL="/home/dataset/model/llama-2-7b-hf/tokenizer.model"
TP=2
PP=2
CP=1
EP=1
DISTRIBUTED_ARGS="
--nproc_per_node $NPUS_PER_NODE \
--nnodes $NNODES \
--node_rank $NODE_RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT
"
RECOMPUTE_ARGS="
--recompute-granularity full \
--recompute-method block \
--recompute-num-layers 1 \
--enable-recompute-layers-per-pp-rank \
--recompute-activation-function \
--recompute-activation-function-num-layers 1 \
--recompute-in-advance \
"
GPT_ARGS="
--tensor-model-parallel-size ${TP} \
--pipeline-model-parallel-size ${PP} \
--num-layers-per-virtual-pipeline-stage 1 \
--context-parallel-size ${CP} \
--context-parallel-algo ulysses_cp_algo \
--reuse-fp32-param \
--sequence-parallel \
--use-fused-rotary-pos-emb \
--use-fused-rmsnorm \
--use-flash-attn \
--num-layers 4 \
--hidden-size 8192 \
--ffn-hidden-size 28672 \
--num-attention-heads 64 \
--tokenizer-type Llama2Tokenizer \
--tokenizer-model ${TOKENIZER_MODEL} \
--seq-length 32768 \
--max-position-embeddings 32768 \
--micro-batch-size 1 \
--global-batch-size 4 \
--make-vocab-size-divisible-by 1 \
--lr 1.0e-6 \
--train-iters 1000 \
--lr-decay-style cosine \
--untie-embeddings-and-output-weights \
--attention-dropout 0.0 \
--init-method-std 0.01 \
--hidden-dropout 0.0 \
--position-embedding-type rope \
--normalization RMSNorm \
--swiglu \
--no-masked-softmax-fusion \
--attention-softmax-in-fp32 \
--min-lr 1.0e-7 \
--weight-decay 0.1 \
--clip-grad 1.0 \
--adam-beta1 0.9 \
--initial-loss-scale 4096.0 \
--adam-beta2 0.95 \
--adam-eps 1e-5 \
--disable-bias-linear \
--group-query-attention \
--num-query-groups 8 \
--lr-warmup-fraction 0.01 \
--bf16 \
--use-ascend-coc \
--coc-parallel-num 2 \
--npu-deterministic \
--transformer-impl local \
"
DATA_ARGS="
--data-path $DATA_PATH \
--split 949,50,1
"
OUTPUT_ARGS="
--log-throughput \
--log-interval 1 \
--save-interval 10000 \
--eval-interval 50 \
--eval-iters 10 \
"
torchrun $DISTRIBUTED_ARGS pretrain_gpt.py \
$GPT_ARGS \
$RECOMPUTE_ARGS \
$DATA_ARGS \
$OUTPUT_ARGS \
--exit-interval 50 \
--save $CKPT_DIR \
--ckpt-format torch \
torchrun $DISTRIBUTED_ARGS pretrain_gpt.py \
$GPT_ARGS \
$RECOMPUTE_ARGS \
$DATA_ARGS \
$OUTPUT_ARGS \
--load $CKPT_DIR
set +x