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compile.sh
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compile.sh
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#!/bin/bash
set -ex
models=
mode="int8"
folder="tmp"
num_device=1
device_args=""
quantize_args="--quantize W8F16"
addr_args=""
name=""
num_layers=
out_model=$name.bmodel
seq_length=
hidden_size=
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 [[ -z "$seq_length" ]]; then
echo "Error: --seq_length is required." >&2
exit 1
fi
if [ "$name" = "qwen-1_8b" ]; then
num_layers=24
hidden_size=2048
echo "Compile Qwen-1_8B"
elif [ "$name" = "qwen-7b" ]; then
num_layers=32
hidden_size=4096
echo "Compile Qwen-7B"
elif [ "$name" = "qwen-14b" ]; then
num_layers=40
hidden_size=5120
echo "Compile Qwen-14B"
elif [ "$name" = "qwen-72b" ]; then
num_layers=80
hidden_size=8192
echo "Compile Qwen-72B"
else
>&2 echo -e "Error: Invalid name $name, the input name must be \033[31mqwen-1_8b|qwen-7b|qwen-14b\033[0m"
exit 1
fi
if [ x$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}_${mode}_seq${seq_length}_${num_device}dev.bmodel
else
out_model=${name}_${mode}_seq${seq_length}_1dev.bmodel
fi
if [ x$addr_mode == x"io_alone" ]; then
addr_args="--addr_mode io_alone"
fi
outdir=${folder}/$mode"_"$num_device"dev"/embedding
mkdir -p $outdir
pushd $outdir
model_transform.py \
--model_name embedding \
--model_def ../../onnx/embedding.pt \
--input_shapes [[1,${seq_length}]] \
--input_types "int32" \
--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.pt \
--input_shapes [[1,1]] \
--input_types "int32" \
--mlir embedding_cache.mlir
model_deploy.py \
--mlir embedding_cache.mlir \
--quantize F16 \
--quant_input \
--quant_output \
--chip bm1684x \
$device_args \
--model embedding_cache.bmodel
models=$models' '$outdir'/embedding.bmodel '$outdir'/embedding_cache.bmodel '
rm *.npz *.onnx -f
popd
echo $models
outdir=${folder}/$mode"_"$num_device"dev"/lm_head
mkdir -p $outdir
pushd $outdir
if [[ $num_device -gt 1 ]]; then
model_transform.py \
--model_name lm_head \
--model_def ../../onnx/lm_head_with_topk.pt \
--input_shapes [[1,1,${hidden_size}]] \
--mlir lm_head.mlir
model_deploy.py \
--mlir lm_head.mlir \
${quantize_args} \
--quant_input \
--chip bm1684x \
$device_args \
--model lm_head.bmodel
models=${models}${outdir}'/lm_head.bmodel '
else
model_transform.py \
--model_name lm_head \
--model_def ../../onnx/lm_head.pt \
--input_shapes [[1,${hidden_size}]] \
--mlir lm_head.mlir
model_deploy.py \
--mlir lm_head.mlir \
$quantize_args \
--quant_input \
--chip bm1684x \
$device_args \
--model lm_head.bmodel
model_transform.py \
--model_name greedy_head \
--model_def ../../onnx/greedy_head.onnx \
--mlir greedy_head.mlir
model_deploy.py \
--mlir greedy_head.mlir \
--chip bm1684x \
--model greedy_head.bmodel
model_transform.py \
--model_name penalty_sample_head \
--model_def ../../onnx/penalty_sample_head.onnx \
--mlir penalty_sample_head.mlir
model_deploy.py \
--mlir penalty_sample_head.mlir \
--chip bm1684x \
--model penalty_sample_head.bmodel
models=${models}${outdir}'/lm_head.bmodel '$outdir'/greedy_head.bmodel '$outdir'/penalty_sample_head.bmodel '
fi
rm *.npz *.onnx -f
popd
echo $models
outdir=${folder}/$mode"_"$num_device"dev"/block
mkdir -p $outdir
pushd $outdir
for ((i=0; i<$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
model_transform.py \
--model_name block_prompt_cache_$i \
--model_def ../../onnx/block_prompt_cache_$i.onnx \
--mlir block_prompt_cache_$i.mlir
model_deploy.py \
--mlir block_prompt_cache_$i.mlir \
${quantize_args} \
--quant_input \
--quant_output \
--chip bm1684x \
$device_args \
--model block_prompt_cache_$i.bmodel
rm *.npz *.onnx -f
models=${models}${outdir}'/block_'$i'.bmodel '$outdir'/block_cache_'$i'.bmodel '$outdir'/block_prompt_cache_'$i'.bmodel '
done
popd
echo $models
model_tool --combine $models -o $out_model