#!/bin/bash
set -e
source /usr/local/Ascend/ascend-toolkit/set_env.sh
export ASCEND_SLOG_PRINT_TO_STDOUT=0
export ASCEND_GLOBAL_LOG_LEVEL=3
export TASK_QUEUE_ENABLE=2
export COMBINED_ENABLE=1
export CPU_AFFINITY_CONF=1
export HCCL_CONNECT_TIMEOUT=1200
export CUDA_DEVICE_MAX_CONNECTIONS=1
export ACLNN_CACHE_LIMIT=100000
NPUS_PER_NODE=1
MASTER_ADDR=localhost
MASTER_PORT=6000
NNODES=1
NODE_RANK=0
WORLD_SIZE=$(($NPUS_PER_NODE*$NNODES))
MBS=1
GRAD_ACC_STEP=1
TP=1
PP=1
CP=1
DP=$(($WORLD_SIZE/$TP/$PP/$CP))
GBS=$(($MBS*$GRAD_ACC_STEP*$DP))
BASEPATH=$(cd `dirname $0`; cd ../../../; pwd)
LOCATION=$(pip show mindspeed 2>/dev/null | grep "^Location:" | awk '{print $2}')
echo "LOCATION: $LOCATION"
echo "BASEPATH: $BASEPATH"
cd $BASEPATH
MM_MODEL="$BASEPATH/tests/st/run_configs/inference_internvl2_5/inference_4B.json"
MM_ARGS="
--mm-model ${MM_MODEL} \
"
DISTRIBUTED_ARGS="
--nproc_per_node $NPUS_PER_NODE \
--nnodes $NNODES \
--node_rank $NODE_RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT
"
GPT_ARGS="
--tensor-model-parallel-size ${TP} \
--pipeline-model-parallel-size ${PP} \
--context-parallel-size ${CP} \
--micro-batch-size ${MBS} \
--global-batch-size ${GBS} \
--seq-length 4096 \
--tokenizer-type NullTokenizer \
--vocab-size 151674 \
--position-embedding-type rope \
--rotary-base 1000000 \
--swiglu \
--no-masked-softmax-fusion \
--use-distributed-optimizer \
--bf16 \
--use-flash-attn \
--trust-remote-code \
"
OUTPUT_ARGS="
--log-interval 1 \
--save-interval 5000 \
--eval-interval 5000 \
--eval-iters 5000 \
"
torchrun $DISTRIBUTED_ARGS \
inference_vlm.py \
$GPT_ARGS \
$MM_ARGS \
$OUTPUT_ARGS \
--distributed-backend nccl