add pwgan tipc, test=doc

tests/test_tipc/common_func.sh

@@ -0,0 +1,65 @@
+#!/bin/bash
+
+function func_parser_key(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[0]}
+    echo ${tmp}
+}
+
+function func_parser_value(){
+    strs=$1
+    IFS=":"
+    array=(${strs})
+    tmp=${array[1]}
+    echo ${tmp}
+}
+
+function func_set_params(){
+    key=$1
+    value=$2
+    if [ ${key}x = "null"x ];then
+        echo " "
+    elif [[ ${value} = "null" ]] || [[ ${value} = " " ]] || [ ${#value} -le 0 ];then
+        echo " "
+    else 
+        echo "${key}=${value}"
+    fi
+}
+
+function func_parser_params(){
+    strs=$1
+    MODE=$2
+    IFS=":"
+    array=(${strs})
+    key=${array[0]}
+    tmp=${array[1]}
+    IFS="|"
+    res=""
+    for _params in ${tmp[*]}; do
+        IFS="="
+        array=(${_params})
+        mode=${array[0]}
+        value=${array[1]}
+        if [[ ${mode} = ${MODE} ]]; then
+            IFS="|"
+            #echo $(func_set_params "${mode}" "${value}")
+            echo $value
+            break
+        fi
+        IFS="|"
+    done
+    echo ${res}
+}
+
+function status_check(){
+    last_status=$1   # the exit code
+    run_command=$2
+    run_log=$3
+    if [ $last_status -eq 0 ]; then
+        echo -e "\033[33m Run successfully with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+    else
+        echo -e "\033[33m Run failed with command - ${run_command}!  \033[0m" | tee -a ${run_log}
+    fi
+}

tests/test_tipc/configs/conformer/train_benchmark.txt

@@ -54,4 +54,4 @@ batch_size:16|30
 fp_items:fp32
 iteration:50
 --profiler-options:"batch_range=[10,35];state=GPU;tracer_option=Default;profile_path=model.profile"
-flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096"
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096

tests/test_tipc/configs/pwgan/train_benchmark.txt

@@ -0,0 +1,57 @@
+===========================train_params===========================
+model_name:pwgan
+python:python3.7
+gpu_list:0|0,1
+null:null
+null:null
+--max-iter:100
+null:null
+--batch-size:6
+null:null
+null:null
+null:null
+null:null
+##
+trainer:norm_train
+norm_train: ../paddlespeech/t2s/exps/gan_vocoder/parallelwave_gan/train.py --ngpu=1 --train-metadata=dump/train/norm/metadata.jsonl --dev-metadata=dump/dev/norm/metadata.jsonl --config=../examples/csmsc/voc1/conf/default.yaml --output-dir=exp/default --run-benchmark=true --max-iter 10
+pact_train:null
+fpgm_train:null
+distill_train:null
+null:null
+null:null
+##
+===========================eval_params===========================
+eval:null
+null:null
+##
+===========================infer_params===========================
+null:null
+null:null
+norm_export: null
+quant_export:null
+fpgm_export:null
+distill_export:null
+export1:null
+export2:null
+null:null
+infer_model:null
+infer_export:null
+infer_quant:null
+inference:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+null:null
+===========================train_benchmark_params==========================
+batch_size:6|16
+fp_items:fp32
+iteration:50
+--profiler_options:"batch_range=[10,35];state=GPU;tracer_option=Default;profile_path=model.profile"
+flags:FLAGS_eager_delete_tensor_gb=0.0;FLAGS_fraction_of_gpu_memory_to_use=0.98;FLAGS_conv_workspace_size_limit=4096

tests/test_tipc/prepare.sh

@@ -58,4 +58,19 @@ if [ ${MODE} = "benchmark_train" ];then
         sed -i "s#data/#test_tipc/conformer/benchmark_train/data/#g" ${curPath}/conformer/benchmark_train/conf/preprocess.yaml
 
     fi
-fi
+
+    if [ ${model_name} == "pwgan" ]; then
+        # 下载 csmsc 数据集并解压缩
+        wget -nc https://weixinxcxdb.oss-cn-beijing.aliyuncs.com/gwYinPinKu/BZNSYP.rar
+        mkdir -p BZNSYP
+        unrar x BZNSYP.rar BZNSYP
+        wget -nc https://paddlespeech.bj.bcebos.com/Parakeet/benchmark/durations.txt
+        # 数据预处理
+        python ../paddlespeech/t2s/exps/gan_vocoder/preprocess.py --rootdir=BZNSYP/ --dumpdir=dump --num-cpu=20 --cut-sil=True --dur-file=durations.txt --config=../examples/csmsc/voc1/conf/default.yaml
+        python ../utils/compute_statistics.py --metadata=dump/train/raw/metadata.jsonl --field-name="feats"
+        python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/train/raw/metadata.jsonl --dumpdir=dump/train/norm --stats=dump/train/feats_stats.npy
+        python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/dev/raw/metadata.jsonl --dumpdir=dump/dev/norm --stats=dump/train/feats_stats.npy
+        python ../paddlespeech/t2s/exps/gan_vocoder/normalize.py --metadata=dump/test/raw/metadata.jsonl --dumpdir=dump/test/norm --stats=dump/train/feats_stats.npy
+    fi
+
+fi

tests/test_tipc/test_train_inference_python.sh

@@ -20,10 +20,10 @@ train_use_gpu_value=$(func_parser_value "${lines[4]}")
 autocast_list=$(func_parser_value "${lines[5]}")
 autocast_key=$(func_parser_key "${lines[5]}")
 epoch_key=$(func_parser_key "${lines[6]}")
-epoch_num=$(func_parser_params "${lines[6]}")
+epoch_num=$(func_parser_params "${lines[6]}" "${MODE}")
 save_model_key=$(func_parser_key "${lines[7]}")
 train_batch_key=$(func_parser_key "${lines[8]}")
-train_batch_value=$(func_parser_params "${lines[8]}")
+train_batch_value=$(func_parser_params "${lines[8]}" "${MODE}")
 pretrain_model_key=$(func_parser_key "${lines[9]}")
 pretrain_model_value=$(func_parser_value "${lines[9]}")
 train_model_name=$(func_parser_value "${lines[10]}")
@@ -50,7 +50,6 @@ eval_key1=$(func_parser_key "${lines[24]}")
 eval_value1=$(func_parser_value "${lines[24]}")
 
 save_infer_key=$(func_parser_key "${lines[27]}")
-save_infer_value=$(func_parser_value "${lines[27]}")
 export_weight=$(func_parser_key "${lines[28]}")
 norm_export=$(func_parser_value "${lines[29]}")
 pact_export=$(func_parser_value "${lines[30]}")
@@ -62,11 +61,11 @@ export_key2=$(func_parser_key "${lines[34]}")
 export_value2=$(func_parser_value "${lines[34]}")
 inference_dir=$(func_parser_value "${lines[35]}")
 
-# parser inference model
+# parser inference model 
 infer_model_dir_list=$(func_parser_value "${lines[36]}")
 infer_export_list=$(func_parser_value "${lines[37]}")
 infer_is_quant=$(func_parser_value "${lines[38]}")
-# parser inference
+# parser inference 
 inference_py=$(func_parser_value "${lines[39]}")
 use_gpu_key=$(func_parser_key "${lines[40]}")
 use_gpu_list=$(func_parser_value "${lines[40]}")
@@ -91,44 +90,42 @@ infer_value1=$(func_parser_value "${lines[50]}")
 
 # parser klquant_infer
 if [ ${MODE} = "klquant_whole_infer" ]; then
-    dataline=$(awk 'NR==1 NR==17{print}'  $FILENAME)
+    dataline=$(awk 'NR==1, NR==17{print}'  $FILENAME)
     lines=(${dataline})
     model_name=$(func_parser_value "${lines[1]}")
     python=$(func_parser_value "${lines[2]}")
-    # parser inference model
+    export_weight=$(func_parser_key "${lines[3]}")
-    infer_model_dir_list=$(func_parser_value "${lines[3]}")
+    save_infer_key=$(func_parser_key "${lines[4]}")
-    infer_export_list=$(func_parser_value "${lines[4]}")
+    # parser inference model 
-    infer_is_quant=$(func_parser_value "${lines[5]}")
+    infer_model_dir_list=$(func_parser_value "${lines[5]}")
-    # parser inference
+    infer_export_list=$(func_parser_value "${lines[6]}")
-    inference_py=$(func_parser_value "${lines[6]}")
+    infer_is_quant=$(func_parser_value "${lines[7]}")
-    use_gpu_key=$(func_parser_key "${lines[7]}")
+    # parser inference 
-    use_gpu_list=$(func_parser_value "${lines[7]}")
+    inference_py=$(func_parser_value "${lines[8]}")
-    use_mkldnn_key=$(func_parser_key "${lines[8]}")
+    use_gpu_key=$(func_parser_key "${lines[9]}")
-    use_mkldnn_list=$(func_parser_value "${lines[8]}")
+    use_gpu_list=$(func_parser_value "${lines[9]}")
-    cpu_threads_key=$(func_parser_key "${lines[9]}")
+    use_mkldnn_key=$(func_parser_key "${lines[10]}")
-    cpu_threads_list=$(func_parser_value "${lines[9]}")
+    use_mkldnn_list=$(func_parser_value "${lines[10]}")
-    batch_size_key=$(func_parser_key "${lines[10]}")
+    cpu_threads_key=$(func_parser_key "${lines[11]}")
-    batch_size_list=$(func_parser_value "${lines[10]}")
+    cpu_threads_list=$(func_parser_value "${lines[11]}")
-    use_trt_key=$(func_parser_key "${lines[11]}")
+    batch_size_key=$(func_parser_key "${lines[12]}")
-    use_trt_list=$(func_parser_value "${lines[11]}")
+    batch_size_list=$(func_parser_value "${lines[12]}")
-    precision_key=$(func_parser_key "${lines[12]}")
+    use_trt_key=$(func_parser_key "${lines[13]}")
-    precision_list=$(func_parser_value "${lines[12]}")
+    use_trt_list=$(func_parser_value "${lines[13]}")
-    infer_model_key=$(func_parser_key "${lines[13]}")
+    precision_key=$(func_parser_key "${lines[14]}")
-    image_dir_key=$(func_parser_key "${lines[14]}")
+    precision_list=$(func_parser_value "${lines[14]}")
-    infer_img_dir=$(func_parser_value "${lines[14]}")
+    infer_model_key=$(func_parser_key "${lines[15]}")
-    save_log_key=$(func_parser_key "${lines[15]}")
+    image_dir_key=$(func_parser_key "${lines[16]}")
-    benchmark_key=$(func_parser_key "${lines[16]}")
+    infer_img_dir=$(func_parser_value "${lines[16]}")
-    benchmark_value=$(func_parser_value "${lines[16]}")
+    save_log_key=$(func_parser_key "${lines[17]}")
-    infer_key1=$(func_parser_key "${lines[17]}")
+    save_log_value=$(func_parser_value "${lines[17]}")
-    infer_value1=$(func_parser_value "${lines[17]}")
+    benchmark_key=$(func_parser_key "${lines[18]}")
+    benchmark_value=$(func_parser_value "${lines[18]}")
+    infer_key1=$(func_parser_key "${lines[19]}")
+    infer_value1=$(func_parser_value "${lines[19]}")
 fi
 
-save_model_value=$(func_parser_value "${lines[7]}")
+LOG_PATH="./test_tipc/output"
-if [[ ${save_model_value} = " " ]] || [[ ${save_model_value} = "null" ]] || [[ ${save_model_value} = "" ]];then
-    LOG_PATH="./test_tipc/output"
-else
-    LOG_PATH=${save_model_value}
-fi
 mkdir -p ${LOG_PATH}
 status_log="${LOG_PATH}/results_python.log"
 
@@ -141,7 +138,7 @@ function func_inference(){
     _log_path=$4
     _img_dir=$5
     _flag_quant=$6
-    # inference
+    # inference 
     for use_gpu in ${use_gpu_list[*]}; do
         if [ ${use_gpu} = "False" ] || [ ${use_gpu} = "cpu" ]; then
             for use_mkldnn in ${use_mkldnn_list[*]}; do
@@ -158,15 +155,17 @@ function func_inference(){
                                 continue
                             fi # skip when quant model inference but precision is not int8
                             set_precision=$(func_set_params "${precision_key}" "${precision}")
-
+                            
                             _save_log_path="${_log_path}/python_infer_cpu_usemkldnn_${use_mkldnn}_threads_${threads}_precision_${precision}_batchsize_${batch_size}.log"
                             set_infer_data=$(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}")
+                            set_mkldnn=$(func_set_params "${use_mkldnn_key}" "${use_mkldnn}")
                             set_cpu_threads=$(func_set_params "${cpu_threads_key}" "${threads}")
                             set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
+                            set_infer_params0=$(func_set_params "${save_log_key}" "${save_log_value}")
                             set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}")
-                            command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${use_mkldnn_key}=${use_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_precision} ${set_infer_params1} > ${_save_log_path} 2>&1 "
+                            command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_mkldnn} ${set_cpu_threads} ${set_model_dir} ${set_batchsize} ${set_infer_params0} ${set_infer_data} ${set_benchmark} ${set_precision} ${set_infer_params1} > ${_save_log_path} 2>&1 "
                             eval $command
                             last_status=${PIPESTATUS[0]}
                             eval "cat ${_save_log_path}"
@@ -180,11 +179,11 @@ function func_inference(){
                 for precision in ${precision_list[*]}; do
                     if [[ ${_flag_quant} = "False" ]] && [[ ${precision} =~ "int8" ]]; then
                         continue
-                    fi
+                    fi 
                     if [[ ${precision} =~ "fp16" || ${precision} =~ "int8" ]] && [ ${use_trt} = "False" ]; then
                         continue
                     fi
-                    if [[ ${use_trt} = "False" || ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then
+                    if [[ ${use_trt} = "False" && ${precision} =~ "int8" ]] && [ ${_flag_quant} = "True" ]; then
                         continue
                     fi
                     for batch_size in ${batch_size_list[*]}; do
@@ -195,13 +194,14 @@ function func_inference(){
                         set_tensorrt=$(func_set_params "${use_trt_key}" "${use_trt}")
                         set_precision=$(func_set_params "${precision_key}" "${precision}")
                         set_model_dir=$(func_set_params "${infer_model_key}" "${_model_dir}")
+                        set_infer_params0=$(func_set_params "${save_log_key}" "${save_log_value}")
                         set_infer_params1=$(func_set_params "${infer_key1}" "${infer_value1}")
-                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_tensorrt} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_infer_params1} > ${_save_log_path} 2>&1 "
+                        command="${_python} ${_script} ${use_gpu_key}=${use_gpu} ${set_tensorrt} ${set_precision} ${set_model_dir} ${set_batchsize} ${set_infer_data} ${set_benchmark} ${set_infer_params1} ${set_infer_params0} > ${_save_log_path} 2>&1 "
                         eval $command
                         last_status=${PIPESTATUS[0]}
                         eval "cat ${_save_log_path}"
                         status_check $last_status "${command}" "${status_log}"
-
+                        
                     done
                 done
             done
@@ -227,14 +227,17 @@ if [ ${MODE} = "whole_infer" ] || [ ${MODE} = "klquant_whole_infer" ]; then
     for infer_model in ${infer_model_dir_list[*]}; do
         # run export
         if [ ${infer_run_exports[Count]} != "null" ];then
-            save_infer_dir=$(dirname $infer_model)
+            if [ ${MODE} = "klquant_whole_infer" ]; then
+                save_infer_dir="${infer_model}_klquant"
+            fi
+            if [ ${MODE} = "whole_infer" ]; then
+                save_infer_dir="${infer_model}"
+            fi
             set_export_weight=$(func_set_params "${export_weight}" "${infer_model}")
             set_save_infer_key=$(func_set_params "${save_infer_key}" "${save_infer_dir}")
-            # For lac which needs the `data_dir` args
+            export_cmd="${python} ${infer_run_exports[Count]} ${set_export_weight} ${set_save_infer_key}"
-            set_export1_key=$(func_set_params "${export_key1}" "${export_value1}")
+            echo ${infer_run_exports[Count]} 
-            export_cmd="${python} ${infer_run_exports[Count]} ${set_export_weight} ${set_save_infer_key} ${set_export1_key}"
+            echo $export_cmd
-            echo ${infer_run_exports[Count]}
-            echo  $export_cmd
             eval $export_cmd
             status_export=$?
             status_check $status_export "${export_cmd}" "${status_log}"
@@ -243,7 +246,7 @@ if [ ${MODE} = "whole_infer" ] || [ ${MODE} = "klquant_whole_infer" ]; then
         fi
         #run inference
         is_quant=${infer_quant_flag[Count]}
-        if [ ${MODE} = "klquant_infer" ]; then
+        if [ ${MODE} = "klquant_whole_infer" ]; then
             is_quant="True"
         fi
         func_inference "${python}" "${inference_py}" "${save_infer_dir}" "${LOG_PATH}" "${infer_img_dir}" ${is_quant}
@@ -261,7 +264,6 @@ else
             env=""
         elif [ ${#gpu} -le 1 ];then
             env="export CUDA_VISIBLE_DEVICES=${gpu}"
-            eval ${env}
         elif [ ${#gpu} -le 15 ];then
             IFS=","
             array=(${gpu})
@@ -275,13 +277,13 @@ else
             IFS="|"
             env=" "
         fi
-        for autocast in ${autocast_list[*]}; do
+        for autocast in ${autocast_list[*]}; do 
             if [ ${autocast} = "amp" ]; then
                 set_amp_config="Global.use_amp=True Global.scale_loss=1024.0 Global.use_dynamic_loss_scaling=True"
             else
                 set_amp_config=" "
-            fi
+            fi          
-            for trainer in ${trainer_list[*]}; do
+            for trainer in ${trainer_list[*]}; do 
                 flag_quant=False
                 if [ ${trainer} = ${pact_key} ]; then
                     run_train=${pact_trainer}
@@ -324,10 +326,6 @@ else
                     save_log="${LOG_PATH}/${trainer}_gpus_${gpu}_autocast_${autocast}_nodes_${nodes}"
                 fi
 
-                # load pretrain from norm training if current trainer is pact or fpgm trainer
-                if ([ ${trainer} = ${pact_key} ] || [ ${trainer} = ${fpgm_key} ]) && [ ${nodes} -le 1 ]; then
-                    set_pretrain="${load_norm_train_model}"
-                fi
 
                 set_save_model=$(func_set_params "${save_model_key}" "${save_log}")
                 if [ ${#gpu} -le 2 ];then  # train with cpu or single gpu
@@ -338,48 +336,42 @@ else
                     cmd="${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 "unset CUDA_VISIBLE_DEVICES"
                 eval $cmd
                 status_check $? "${cmd}" "${status_log}"
 
                 set_eval_pretrain=$(func_set_params "${pretrain_model_key}" "${save_log}/${train_model_name}")
-                # save norm trained models to set pretrain for pact training and fpgm training
+
-                if [ ${trainer} = ${trainer_norm} ] && [ ${nodes} -le 1 ]; then
+                # run eval 
-                    load_norm_train_model=${set_eval_pretrain}
-                fi
-                # run eval
                 if [ ${eval_py} != "null" ]; then
+                    eval ${env}
                     set_eval_params1=$(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 $eval_cmd
                     status_check $? "${eval_cmd}" "${status_log}"
                 fi
                 # run export model
-                if [ ${run_export} != "null" ]; then
+                if [ ${run_export} != "null" ]; then 
                     # run export model
-                    save_infer_path="${save_infer_value}"
+                    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}")
-                    # For lac which needs the `data_dir` args
+                    export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key}"
-                    set_export1_key=$(func_set_params "${export_key1}" "${export_value1}")
-                    export_cmd="${python} ${run_export} ${set_export_weight} ${set_save_infer_key} ${set_export1_key}"
                     eval $export_cmd
                     status_check $? "${export_cmd}" "${status_log}"
 
                     #run inference
                     eval $env
-                    save_infer_path="${save_infer_value}"
+                    save_infer_path="${save_log}"
-
+                    if [[ ${inference_dir} != "null" ]] && [[ ${inference_dir} != '##' ]]; then
-                    if [ ${inference_dir} != "null" ] && [ ${inference_dir} != '##' ]; then
                         infer_model_dir="${save_infer_path}/${inference_dir}"
                     else
                         infer_model_dir=${save_infer_path}
                     fi
                     func_inference "${python}" "${inference_py}" "${infer_model_dir}" "${LOG_PATH}" "${train_infer_img_dir}" "${flag_quant}"
-
+                    
                     eval "unset CUDA_VISIBLE_DEVICES"
                 fi
-            done  # done with:    for trainer in ${trainer_list[*]}; do
+            done  # done with:    for trainer in ${trainer_list[*]}; do 
-        done      # done with:    for autocast in ${autocast_list[*]}; do
+        done      # done with:    for autocast in ${autocast_list[*]}; do 
     done          # done with:    for gpu in ${gpu_list[*]}; do
-fi  # end if [ ${MODE} = "infer" ]; then
+fi  # end if [ ${MODE} = "infer" ]; then