Phi-3/compile/compile.sh

#!/bin/bash
set -ex
models=""
mode=int4
folder="tmp"
num_device=1
mode_args=""
device_args=""
addr_args=""
quantize_args=""
name="phi3-4b"
num_layers=
hidden_size=
out_model=$name.bmodel

while [[ $# -gt 0 ]]; do
 key="$1"

 case $key in
 --mode)
 mode="$2"
 shift 2
 ;;
 --num_device)
 num_device="$2"
 shift 2
 ;;
 --name)
 name="$2"
 shift 2
 ;;
 --addr_mode)
 addr_mode="$2"
 shift 2
 ;;
 --seq_length)
 seq_length="$2"
 shift 2
 ;;
 *)
 echo "Invalid option: $key" >&2
 exit 1
 ;;
 :)
 echo "Option -$OPTARG requires an argument." >&2
 exit 1
 ;;
 esac
done

if [ "$name" = "phi3-4b" ]; then
 num_layers=31
 hidden_size=3072
 echo "Compile Phi3-4B"
else
 >&2 echo -e "Error: Invalid name $name, the input name must be \033[31mphi3-4b\033[0m"
 exit 1
fi

if [ x$mode == x"int8" ]; then
 quantize_args="--quantize W8F16"
elif [ x$mode == x"f16" ]; then
 quantize_args="--quantize F16"
elif [ x$mode == x"int4" ]; then
 quantize_args="--quantize W4F16 --q_group_size 64"
else
 echo "Error, unknown quantize mode"
 exit 1
fi

if [ x$num_device != x1 ]; then
 device_args="--num_device $num_device"
 out_model=$name'_'$mode'_'$num_device'dev.bmodel'
else
 out_model=$name'_'$mode'_1dev.bmodel'
fi

if [ x$addr_mode == x"io_alone" ]; then
 addr_args="--addr_mode io_alone"
fi

outdir=${folder}/embedding
mkdir -p $outdir
pushd $outdir

model_transform.py \
 --model_name embedding \
 --model_def ../../onnx/embedding.onnx \
 --mlir embedding.mlir

model_deploy.py \
 --mlir embedding.mlir \
 --quantize F16 \
 --quant_input \
 --quant_output \
 --chip bm1684x \
 $device_args \
 --model embedding.bmodel

model_transform.py \
 --model_name embedding_cache \
 --model_def ../../onnx/embedding.onnx \
 --input_shapes [[1,1]] \
 --mlir embedding_cache.mlir

model_deploy.py \
 --mlir embedding_cache.mlir \
 --quantize F16 \
 --quant_input \
 --quant_output \
 --chip bm1684x \
 $device_args \
 --model embedding_cache.bmodel

rm *.npz

models=$models' '$outdir'/embedding.bmodel '$outdir'/embedding_cache.bmodel '

popd

echo $models

outdir=${folder}/$mode"_"$num_device"dev"/lm_head
mkdir -p $outdir
pushd $outdir

model_transform.py \
 --model_name lm_head \
 --model_def ../../onnx/lm_head.onnx \
 --input_shapes [[1,${hidden_size}]] \
 --mlir lm_head.mlir

model_deploy.py \
 --mlir lm_head.mlir \
 $quantize_args \
 --quant_input \
 --chip bm1684x \
 $device_args \
 --model lm_head.bmodel


model_transform.py \
 --model_name greedy_head \
 --model_def ../../onnx/greedy_head.onnx \
 --mlir greedy_head.mlir

model_deploy.py \
 --mlir greedy_head.mlir \
 --chip bm1684x \
 --model greedy_head.bmodel


model_transform.py \
 --model_name penalty_sample_head \
 --model_def ../../onnx/penalty_sample_head.onnx \
 --mlir penalty_sample_head.mlir

model_deploy.py \
 --mlir penalty_sample_head.mlir \
 --chip bm1684x \
 --model penalty_sample_head.bmodel

rm *.npz

models=${models}${outdir}'/lm_head.bmodel '$outdir'/greedy_head.bmodel '$outdir'/penalty_sample_head.bmodel '
popd

echo $models

outdir=${folder}/$mode"_"$num_device"dev"/block
mkdir -p $outdir

pushd $outdir
mkdir -p $outdir

for ((i=0; i<=$num_layers; i++)); do
 model_transform.py \
 --model_name block_$i \
 --model_def ../../onnx/block_$i.onnx \
 --mlir block_$i.mlir

 model_deploy.py \
 --mlir block_$i.mlir \
 $quantize_args \
 --quant_input \
 --quant_output \
 --chip bm1684x \
 $device_args \
 --model block_$i.bmodel

 model_transform.py \
 --model_name block_cache_$i \
 --model_def ../../onnx/block_cache_$i.onnx \
 --mlir block_cache_$i.mlir

 model_deploy.py \
 --mlir block_cache_$i.mlir \
 $quantize_args \
 --quant_input \
 --quant_output \
 --chip bm1684x \
 $device_args \
 $addr_args \
 --model block_cache_$i.bmodel

 rm *.npz

 models=${models}${outdir}'/block_'$i'.bmodel '$outdir'/block_cache_'$i'.bmodel '

done
popd
echo $models

model_tool --combine $models -o $out_model