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update tipc log #3333

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merged 3 commits into from
Sep 21, 2022
Merged

update tipc log #3333

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5d05434
update tipc
zhengya01 Sep 21, 2022
ffcee1b
update tipc
zhengya01 Sep 21, 2022
b59fca0
code style
zhengya01 Sep 21, 2022
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23 changes: 19 additions & 4 deletions tests/test_tipc/common_func.sh
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Original file line number Diff line number Diff line change
@@ -1,5 +1,19 @@
#!/bin/bash

# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

function func_parser_key(){
strs=$1
IFS=":"
Expand Down Expand Up @@ -53,13 +67,14 @@ function func_parser_params(){
}

function status_check(){
last_status=$1 # the exit code
last_status=$1 # the exit code.
run_command=$2
run_log=$3
model_name=$4
log_path=$5
if [ $last_status -eq 0 ]; then
echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log}
echo -e "\033[33m Run successfully with command - ${model_name} - ${run_command} - ${log_path} \033[0m" | tee -a ${run_log}
else
echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log}
echo -e "\033[33m Run failed with command - ${model_name} - ${run_command} - ${log_path} \033[0m" | tee -a ${run_log}
fi
}

34 changes: 21 additions & 13 deletions tests/test_tipc/test_train_inference_python.sh
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -140,7 +140,8 @@ if [ ${MODE} = "klquant_whole_infer" ]; then
infer_value1=$(func_parser_value "${lines[19]}")
fi

LOG_PATH="./test_tipc/output/${model_name}"
WORK_PATH=$(pwd)
LOG_PATH="$(pwd)/test_tipc/output/${model_name}/${MODE}"
mkdir -p ${LOG_PATH}
status_log="${LOG_PATH}/results_python.log"

Expand All @@ -153,6 +154,7 @@ function func_inference(){
_log_path=$4
_img_dir=$5
_flag_quant=$6
_gpu=$7
# inference
for use_gpu in ${use_gpu_list[*]}; do
if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
Expand All @@ -171,7 +173,7 @@ function func_inference(){
fi # skip when quant model inference but precision is not int8
set_precision=$(func_set_params "${precision_key}" "${precision}")

_save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/python_infer_cpu_gpus_${_gpu}_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
Expand All @@ -184,7 +186,7 @@ function func_inference(){
eval $command
last_status=${PIPESTATUS[0]}
eval "cat ${_save_log_path}"
status_check $last_status "${command}" "${status_log}"
status_check $last_status "${command}" "${status_log}" "${model_name}" "${_save_log_path}"
done
done
done
Expand All @@ -202,7 +204,7 @@ function func_inference(){
continue
fi
for batch_size in ${batch_size_list[*]}; do
_save_log_path="${_log_path}/python_infer_gpu_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
_save_log_path="${_log_path}/python_infer_gpu_gpus_${_gpu}_usetrt_${use_trt}_precision_${precision}_batchsize_${batch_size}.log"
set_infer_data=$(func_set_params "${image_dir_key}" "${_img_dir}")
set_benchmark=$(func_set_params "${benchmark_key}" "${benchmark_value}")
set_batchsize=$(func_set_params "${batch_size_key}" "${batch_size}")
Expand All @@ -215,7 +217,7 @@ function func_inference(){
eval $command
last_status=${PIPESTATUS[0]}
eval "cat ${_save_log_path}"
status_check $last_status "${command}" "${status_log}"
status_check $last_status "${command}" "${status_log}" "${model_name}" "${_save_log_path}"

done
done
Expand Down Expand Up @@ -335,8 +337,8 @@ else
set_train_params1=$(func_set_params "${train_param_key1}" "${train_param_value1}")
set_use_gpu=$(func_set_params "${train_use_gpu_key}" "${train_use_gpu}")
if [ ${#ips} -le 26 ];then
save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}"
nodes=1
save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}"
else
IFS=","
ips_array=(${ips})
Expand All @@ -346,37 +348,43 @@ else
fi


_train_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}.log"
set_save_model=$(func_set_params "${save_model_key}" "${save_log}")
if [ ${#gpu} -le 2 ];then # train with cpu or single gpu
cmd="${python} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} "
cmd="${python} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config} >${_train_log} 2>&1"
elif [ ${#ips} -le 26 ];then # train with multi-gpu
cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}"
else # train with multi-machine
cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train} ${set_use_gpu} ${set_save_model} ${set_pretrain} ${set_epoch} ${set_autocast} ${set_batchsize} ${set_train_params1} ${set_amp_config}"
fi
# run train
eval $cmd
status_check $? "${cmd}" "${status_log}"
if [ ${#gpu} -ge 2 ];then
cat ${WORK_PATH}/log/workerlog.0 > ${_train_log}
fi
status_check $? "${cmd}" "${status_log}" "${model_name}" "${_train_log}"

set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}")

# run eval
if [ ${eval_py} != "null" ]; then
eval ${env}
_eval_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}_eval.log"
set_eval_params1=$(func_set_params "${eval_key1}" "${eval_value1}")
eval_cmd="${python} ${eval_py} ${set_eval_pretrain} ${set_use_gpu} ${set_eval_params1}"
eval_cmd="${python} ${eval_py} ${set_eval_pretrain} ${set_use_gpu} ${set_eval_params1} >${_eval_log} 2>&1"
eval $eval_cmd
status_check $? "${eval_cmd}" "${status_log}"
status_check $? "${eval_cmd}" "${status_log}" "${model_name}" "${_eval_log}"
fi
# run export model
if [ ${run_export} != "null" ]; then
# run export model
save_infer_path="${save_log}"
set_export_weight=$(func_set_params "${export_weight}" "${save_log}/${train_model_name}")
set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_path}")
export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key}"
_export_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}_export.log"
export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key} >${_export_log} 2>&1"
eval $export_cmd
status_check $? "${export_cmd}" "${status_log}"
status_check $? "${export_cmd}" "${status_log}" "${model_name}" "${_export_log}"

#run inference
eval $env
Expand All @@ -386,7 +394,7 @@ else
else
infer_model_dir=${save_infer_path}
fi
func_inference "${python}" "${inference_py}" "${infer_model_dir}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}"
func_inference "${python}" "${inference_py}" "${infer_model_dir}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}" "${gpu}"

eval "unset CUDA_VISIBLE_DEVICES"
fi
Expand Down