#!/bin/bash
export HCCL_CONNECT_TIMEOUT=1200
export CUDA_DEVICE_MAX_CONNECTIONS=1
MASTER_ADDR=localhost
MASTER_PORT=6000
NNODES=1
NODE_RANK=0
NPUS_PER_NODE=8
TP=8
PP=1
CHECKPOINT="Your ckpt file path"
TOKENIZER_PATH="Your vocab file path"
DATA_PATH="Your data path (such as ./mmlu/test/)"
TASK="mmlu"
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} \
--task $TASK \
--task-data-path $DATA_PATH \
--max-new-tokens 1 \
--num-layers 32 \
--hidden-size 4096 \
--ffn-hidden-size 14336 \
--num-attention-heads 32 \
--group-query-attention \
--num-query-groups 8 \
--tokenizer-type PretrainedFromHF \
--tokenizer-name-or-path ${TOKENIZER_PATH} \
--seq-length 4096 \
--max-position-embeddings 32768 \
--micro-batch-size 1 \
--make-vocab-size-divisible-by 1 \
--untie-embeddings-and-output-weights \
--disable-bias-linear \
--position-embedding-type rope \
--normalization RMSNorm \
--use-fused-rmsnorm \
--swiglu \
--no-gradient-accumulation-fusion \
--no-masked-softmax-fusion \
--attention-softmax-in-fp32 \
--load ${CHECKPOINT} \
--no-load-optim \
--no-load-rng \
--bf16 \
--seed 42 \
--rotary-base 1000000 \
--use-mcore-models \
--transformer-impl local
"
torchrun $DISTRIBUTED_ARGS evaluation.py \
$GPT_ARGS \
--distributed-backend nccl
| tee logs/evaluation_mcore_mistral_${TASK}.log