From fb47744a2dccf391850ad081fa01cadcdcc1e521 Mon Sep 17 00:00:00 2001 From: mmglove Date: Tue, 16 Nov 2021 17:31:51 +0800 Subject: [PATCH 1/5] update benchmark case --- tests/benchmark/conformer/README.md | 10 - tests/benchmark/conformer/analysis.py | 345 --------------------- tests/benchmark/conformer/prepare.sh | 1 - tests/benchmark/conformer/run.sh | 30 +- tests/benchmark/conformer/run_benchmark.sh | 28 +- 5 files changed, 39 insertions(+), 375 deletions(-) delete mode 100644 tests/benchmark/conformer/analysis.py diff --git a/tests/benchmark/conformer/README.md b/tests/benchmark/conformer/README.md index 71d5f91b..22e0009d 100644 --- a/tests/benchmark/conformer/README.md +++ b/tests/benchmark/conformer/README.md @@ -43,16 +43,6 @@ bash prepare.sh bash run.sh ``` -### Analyse the sp -``` -bash run_analysis_sp.sh -``` - -### Analyse the mp -``` -bash run_analysis_mp.sh -``` - ### The log ``` {"log_file": "recoder_sp_bs16_fp32_ngpu1.txt", diff --git a/tests/benchmark/conformer/analysis.py b/tests/benchmark/conformer/analysis.py deleted file mode 100644 index 610791c8..00000000 --- a/tests/benchmark/conformer/analysis.py +++ /dev/null @@ -1,345 +0,0 @@ -# copyright (c) 2019 PaddlePaddle Authors. All Rights Reserve. -# -# 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. -from __future__ import print_function - -import argparse -import json -import re -import traceback - - -def parse_args(): - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument( - "--filename", type=str, help="The name of log which need to analysis.") - parser.add_argument( - "--log_with_profiler", - type=str, - help="The path of train log with profiler") - parser.add_argument( - "--profiler_path", type=str, help="The path of profiler timeline log.") - parser.add_argument( - "--keyword", type=str, help="Keyword to specify analysis data") - parser.add_argument( - "--separator", - type=str, - default=None, - help="Separator of different field in log") - parser.add_argument( - '--position', type=int, default=None, help='The position of data field') - parser.add_argument( - '--range', - type=str, - default="", - help='The range of data field to intercept') - parser.add_argument( - '--base_batch_size', type=int, help='base_batch size on gpu') - parser.add_argument( - '--skip_steps', - type=int, - default=0, - help='The number of steps to be skipped') - parser.add_argument( - '--model_mode', - type=int, - default=-1, - help='Analysis mode, default value is -1') - parser.add_argument('--ips_unit', type=str, default=None, help='IPS unit') - parser.add_argument( - '--model_name', - type=str, - default=0, - help='training model_name, transformer_base') - parser.add_argument( - '--mission_name', type=str, default=0, help='training mission name') - parser.add_argument( - '--direction_id', type=int, default=0, help='training direction_id') - parser.add_argument( - '--run_mode', - type=str, - default="sp", - help='multi process or single process') - parser.add_argument( - '--index', - type=int, - default=1, - help='{1: speed, 2:mem, 3:profiler, 6:max_batch_size}') - parser.add_argument( - '--gpu_num', type=int, default=1, help='nums of training gpus') - parser.add_argument( - '--use_num', type=int, default=1, help='nums of used recoders') - args = parser.parse_args() - args.separator = None if args.separator == "None" else args.separator - return args - - -def _is_number(num): - pattern = re.compile(r'^[-+]?[-0-9]\d*\.\d*|[-+]?\.?[0-9]\d*$') - result = pattern.match(num) - if result: - return True - else: - return False - - -class TimeAnalyzer(object): - def __init__(self, - filename, - keyword=None, - separator=None, - position=None, - range="-1"): - if filename is None: - raise Exception("Please specify the filename!") - - if keyword is None: - raise Exception("Please specify the keyword!") - - self.filename = filename - self.keyword = keyword - self.separator = separator - self.position = position - self.range = range - self.records = None - self._distil() - - def _distil(self): - self.records = [] - with open(self.filename, "r") as f_object: - lines = f_object.readlines() - for line in lines: - if self.keyword not in line: - continue - try: - result = None - - # Distil the string from a line. - line = line.strip() - line_words = line.split( - self.separator) if self.separator else line.split() - print("line_words", line_words) - if args.position: - result = line_words[self.position] - else: - # Distil the string following the keyword. - for i in range(len(line_words) - 1): - if line_words[i] == self.keyword: - result = line_words[i + 1] - break - - # Distil the result from the picked string. - if not self.range: - result = result[0:] - elif _is_number(self.range): - result = result[0:int(self.range)] - else: - result = result[int(self.range.split(":")[0]):int( - self.range.split(":")[1])] - self.records.append(float(result)) - except Exception as exc: - pass - #print("line is: {}; separator={}; position={}".format(line, self.separator, self.position)) - self.records.sort() - self.records = self.records[:args.use_num] - print("records", self.records) - print("Extract {} records: separator={}; position={}".format( - len(self.records), self.separator, self.position)) - - def _get_fps(self, - mode, - batch_size, - gpu_num, - avg_of_records, - run_mode, - unit=None): - if mode == -1 and run_mode == 'sp': - assert unit, "Please set the unit when mode is -1." - fps = gpu_num * avg_of_records - elif mode == -1 and run_mode == 'mp': - assert unit, "Please set the unit when mode is -1." - fps = gpu_num * avg_of_records #temporarily, not used now - print("------------this is mp") - elif mode == 0: - # s/step -> samples/s - fps = (batch_size * gpu_num) / avg_of_records - unit = "samples/s" - elif mode == 1: - # steps/s -> steps/s - fps = avg_of_records - unit = "steps/s" - elif mode == 2: - # s/step -> steps/s - fps = 1 / avg_of_records - unit = "steps/s" - elif mode == 3: - # steps/s -> samples/s - fps = batch_size * gpu_num * avg_of_records - unit = "samples/s" - elif mode == 4: - # s/epoch -> s/epoch - fps = avg_of_records - unit = "s/epoch" - else: - ValueError("Unsupported analysis mode.") - - return fps, unit - - def analysis(self, - batch_size, - gpu_num=1, - skip_steps=0, - mode=-1, - run_mode='sp', - unit=None): - if batch_size <= 0: - print("base_batch_size should larger than 0.") - return 0, '' - - if len( - self.records - ) <= skip_steps: # to address the condition which item of log equals to skip_steps - print("no records") - return 0, '' - - sum_of_records = 0 - sum_of_records_skipped = 0 - skip_min = self.records[skip_steps] - skip_max = self.records[skip_steps] - - count = len(self.records) - for i in range(count): - sum_of_records += self.records[i] - if i >= skip_steps: - sum_of_records_skipped += self.records[i] - if self.records[i] < skip_min: - skip_min = self.records[i] - if self.records[i] > skip_max: - skip_max = self.records[i] - - avg_of_records = sum_of_records / float(count) - avg_of_records_skipped = sum_of_records_skipped / float(count - - skip_steps) - - fps, fps_unit = self._get_fps(mode, batch_size, gpu_num, avg_of_records, - run_mode, unit) - fps_skipped, _ = self._get_fps(mode, batch_size, gpu_num, - avg_of_records_skipped, run_mode, unit) - if mode == -1: - print("average ips of %d steps, skip 0 step:" % count) - print("\tAvg: %.3f %s" % (avg_of_records, fps_unit)) - print("\tFPS: %.3f %s" % (fps, fps_unit)) - if skip_steps > 0: - print("average ips of %d steps, skip %d steps:" % - (count, skip_steps)) - print("\tAvg: %.3f %s" % (avg_of_records_skipped, fps_unit)) - print("\tMin: %.3f %s" % (skip_min, fps_unit)) - print("\tMax: %.3f %s" % (skip_max, fps_unit)) - print("\tFPS: %.3f %s" % (fps_skipped, fps_unit)) - elif mode == 1 or mode == 3: - print("average latency of %d steps, skip 0 step:" % count) - print("\tAvg: %.3f steps/s" % avg_of_records) - print("\tFPS: %.3f %s" % (fps, fps_unit)) - if skip_steps > 0: - print("average latency of %d steps, skip %d steps:" % - (count, skip_steps)) - print("\tAvg: %.3f steps/s" % avg_of_records_skipped) - print("\tMin: %.3f steps/s" % skip_min) - print("\tMax: %.3f steps/s" % skip_max) - print("\tFPS: %.3f %s" % (fps_skipped, fps_unit)) - elif mode == 0 or mode == 2: - print("average latency of %d steps, skip 0 step:" % count) - print("\tAvg: %.3f s/step" % avg_of_records) - print("\tFPS: %.3f %s" % (fps, fps_unit)) - if skip_steps > 0: - print("average latency of %d steps, skip %d steps:" % - (count, skip_steps)) - print("\tAvg: %.3f s/step" % avg_of_records_skipped) - print("\tMin: %.3f s/step" % skip_min) - print("\tMax: %.3f s/step" % skip_max) - print("\tFPS: %.3f %s" % (fps_skipped, fps_unit)) - - return round(fps_skipped, 3), fps_unit - - -if __name__ == "__main__": - args = parse_args() - run_info = dict() - run_info["log_file"] = args.filename - run_info["model_name"] = args.model_name - run_info["mission_name"] = args.mission_name - run_info["direction_id"] = args.direction_id - run_info["run_mode"] = args.run_mode - run_info["index"] = args.index - run_info["gpu_num"] = args.gpu_num - run_info["FINAL_RESULT"] = 0 - run_info["JOB_FAIL_FLAG"] = 0 - - try: - if args.index == 1: - if args.gpu_num == 1: - run_info["log_with_profiler"] = args.log_with_profiler - run_info["profiler_path"] = args.profiler_path - analyzer = TimeAnalyzer(args.filename, args.keyword, args.separator, - args.position, args.range) - run_info["FINAL_RESULT"], run_info["UNIT"] = analyzer.analysis( - batch_size=args.base_batch_size, - gpu_num=args.gpu_num, - skip_steps=args.skip_steps, - mode=args.model_mode, - run_mode=args.run_mode, - unit=args.ips_unit) - # if int(os.getenv('job_fail_flag')) == 1 or int(run_info["FINAL_RESULT"]) == 0: - # run_info["JOB_FAIL_FLAG"] = 1 - elif args.index == 3: - run_info["FINAL_RESULT"] = {} - records_fo_total = TimeAnalyzer(args.filename, 'Framework overhead', - None, 3, '').records - records_fo_ratio = TimeAnalyzer(args.filename, 'Framework overhead', - None, 5).records - records_ct_total = TimeAnalyzer(args.filename, 'Computation time', - None, 3, '').records - records_gm_total = TimeAnalyzer(args.filename, - 'GpuMemcpy Calls', - None, 4, '').records - records_gm_ratio = TimeAnalyzer(args.filename, - 'GpuMemcpy Calls', - None, 6).records - records_gmas_total = TimeAnalyzer(args.filename, - 'GpuMemcpyAsync Calls', - None, 4, '').records - records_gms_total = TimeAnalyzer(args.filename, - 'GpuMemcpySync Calls', - None, 4, '').records - run_info["FINAL_RESULT"]["Framework_Total"] = records_fo_total[ - 0] if records_fo_total else 0 - run_info["FINAL_RESULT"]["Framework_Ratio"] = records_fo_ratio[ - 0] if records_fo_ratio else 0 - run_info["FINAL_RESULT"][ - "ComputationTime_Total"] = records_ct_total[ - 0] if records_ct_total else 0 - run_info["FINAL_RESULT"]["GpuMemcpy_Total"] = records_gm_total[ - 0] if records_gm_total else 0 - run_info["FINAL_RESULT"]["GpuMemcpy_Ratio"] = records_gm_ratio[ - 0] if records_gm_ratio else 0 - run_info["FINAL_RESULT"][ - "GpuMemcpyAsync_Total"] = records_gmas_total[ - 0] if records_gmas_total else 0 - run_info["FINAL_RESULT"]["GpuMemcpySync_Total"] = records_gms_total[ - 0] if records_gms_total else 0 - else: - print("Not support!") - except Exception: - traceback.print_exc() - print("{}".format(json.dumps(run_info)) - ) # it's required, for the log file path insert to the database diff --git a/tests/benchmark/conformer/prepare.sh b/tests/benchmark/conformer/prepare.sh index 8f03fd1b..29719074 100644 --- a/tests/benchmark/conformer/prepare.sh +++ b/tests/benchmark/conformer/prepare.sh @@ -1,4 +1,3 @@ -source ../../../tools/venv/bin/activate #Enter the example dir pushd ../../../examples/aishell/s1 diff --git a/tests/benchmark/conformer/run.sh b/tests/benchmark/conformer/run.sh index c09bbf09..0ae2c8e2 100644 --- a/tests/benchmark/conformer/run.sh +++ b/tests/benchmark/conformer/run.sh @@ -1,8 +1,13 @@ # 提供可稳定复现性能的脚本，默认在标准docker环境内py37执行： paddlepaddle/paddle:latest-gpu-cuda10.1-cudnn7 paddle=2.1.2 py=37 # 执行目录：需说明 -CUR_DIR=${PWD} -source ../../../tools/venv/bin/activate +CUR_DIR=${PWD} # PaddleSpeech/tests/benchmark/conformer +cd ../../../ +pip install -e . # 安装pdspeech +log_path=${LOG_PATH_INDEX_DIR:-$(pwd)} # benchmark系统指定该参数,不需要跑profile时,log_path指向存speed的目录 +cd ${CUR_DIR} +sed -i '/set\ -xe/d' run_benchmark.sh + #cd ** pushd ../../../examples/aishell/s1 # 1 安装该模型需要的依赖 (如需开启优化策略请注明) @@ -11,26 +16,33 @@ pushd ../../../examples/aishell/s1 source path.sh source ${MAIN_ROOT}/utils/parse_options.sh || exit 1; - +mkdir -p conf/benchmark +#yq e ".training.accum_grad=1" conf/conformer.yaml > conf/benchmark/conformer.yaml +cp conf/conformer.yaml conf/benchmark/conformer.yaml +sed -i fp_item_list=(fp32) bs_item=(16 30) -config_path=conf/conformer.yaml +config_path=conf/benchmark/conformer.yaml seed=0 output=exp/conformer profiler_options=None +model_item=conformer for fp_item in ${fp_item_list[@]}; do - for batch_size in ${bs_item[@]} + for bs_item in ${bs_item[@]} do rm exp -rf + log_name=speech_${model_item}_bs${bs_item}_${fp_item} # 如:clas_MobileNetv1_mp_bs32_fp32_8 echo "index is speed, 8gpus, run_mode is multi_process, begin, conformer" run_mode=mp ngpu=8 - CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash ${CUR_DIR}/run_benchmark.sh ${run_mode} ${config_path} ${output} ${seed} ${ngpu} ${profiler_options} ${batch_size} ${fp_item} ${CUR_DIR} - rm exp -rf - echo "index is speed, 1gpus, begin, conformer" + CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash ${CUR_DIR}/run_benchmark.sh ${run_mode} ${config_path} ${output} ${seed} ${ngpu} ${profiler_options} ${bs_item} ${fp_item} ${model_item} | tee ${log_path}/${log_name}_speed_8gpus8p 2>&1 + sleep 60 + log_name=speech_${model_item}_bs${bs_item}_${fp_item} # 如:clas_MobileNetv1_mp_bs32_fp32_8 + echo "index is speed, 1gpus, begin, ${log_name}" run_mode=sp ngpu=1 - CUDA_VISIBLE_DEVICES=0 bash ${CUR_DIR}/run_benchmark.sh ${run_mode} ${config_path} ${output} ${seed} ${ngpu} ${profiler_options} ${batch_size} ${fp_item} ${CUR_DIR} + CUDA_VISIBLE_DEVICES=0 bash ${CUR_DIR}/run_benchmark.sh ${run_mode} ${config_path} ${output} ${seed} ${ngpu} ${profiler_options} ${bs_item} ${fp_item} ${model_item} | tee ${log_path}/${log_name}_speed_1gpus 2>&1 # (5min) + sleep 60 done done diff --git a/tests/benchmark/conformer/run_benchmark.sh b/tests/benchmark/conformer/run_benchmark.sh index c03a08f3..a6503117 100644 --- a/tests/benchmark/conformer/run_benchmark.sh +++ b/tests/benchmark/conformer/run_benchmark.sh @@ -9,20 +9,27 @@ function _set_params(){ output=${3:-"exp/conformer"} seed=${4:-"0"} ngpu=${5:-"1"} - profiler_options=${6:-"None"} + profiler_options=${6:-"1"} batch_size=${7:-"32"} fp_item=${8:-"fp32"} - TRAIN_LOG_DIR=${9:-$(pwd)} - + model_item=${9:-"conformer"} benchmark_max_step=0 - run_log_path=${TRAIN_LOG_DIR:-$(pwd)} # TRAIN_LOG_DIR 后续QA设置该参数 +# 添加日志解析需要的参数 + base_batch_size=${batch_size} + mission_name="语音合成" + direction_id="1" + ips_unit="sequences/sec" + skip_steps=10 # 解析日志，有些模型前几个step耗时长，需要跳过 (必填) + keyword="ips:" # 解析日志，筛选出数据所在行的关键字 (必填) + index="1" + model_name=${model_item}_bs${batch_size}_${fp_item} # 以下不用修改 device=${CUDA_VISIBLE_DEVICES//,/ } arr=(${device}) num_gpu_devices=${#arr[*]} - log_file=${run_log_path}/recoder_${run_mode}_bs${batch_size}_${fp_item}_ngpu${ngpu}.txt + log_file=${run_log_path}/recoder_${model_item}_${run_mode}_bs${batch_size}_${fp_item}_ngpu${ngpu} } function _train(){ @@ -36,11 +43,9 @@ function _train(){ --benchmark-batch-size ${batch_size} --benchmark-max-step ${benchmark_max_step} " - echo "run_mode "${run_mode} - case ${run_mode} in - sp) train_cmd="python3 -u ${BIN_DIR}/train.py "${train_cmd} ;; - mp) train_cmd="python3 -u ${BIN_DIR}/train.py "${train_cmd} ;; + sp) train_cmd="python -u ${BIN_DIR}/train.py "${train_cmd} ;; + mp) train_cmd="python -u ${BIN_DIR}/train.py "${train_cmd} ;; *) echo "choose run_mode(sp or mp)"; exit 1; esac echo ${train_cmd} @@ -61,5 +66,8 @@ function _train(){ fi } +source ${BENCHMARK_ROOT}/scripts/run_model.sh # 在该脚本中会对符合benchmark规范的log使用analysis.py 脚本进行性能数据解析;该脚本在连调时可从benchmark repo中下载https://github.com/PaddlePaddle/benchmark/blob/master/scripts/run_model.sh;如果不联调只想要产出训练log可以注掉本行,提交时需打开 _set_params $@ -_train +# _train # 如果只想产出训练log,不解析,可取消注释 +_run # 该函数在run_model.sh中,执行时会调用_train; 如果不联调只想要产出训练log可以注掉本行,提交时需打开 + From bd0a8aeeaa1356599bdfa2a1fb6ae92f0ce2064b Mon Sep 17 00:00:00 2001 From: mmglove Date: Tue, 16 Nov 2021 17:43:14 +0800 Subject: [PATCH 2/5] update benchmark case --- tests/benchmark/conformer/run.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/benchmark/conformer/run.sh b/tests/benchmark/conformer/run.sh index 0ae2c8e2..a32fc01e 100644 --- a/tests/benchmark/conformer/run.sh +++ b/tests/benchmark/conformer/run.sh @@ -19,7 +19,7 @@ source ${MAIN_ROOT}/utils/parse_options.sh || exit 1; mkdir -p conf/benchmark #yq e ".training.accum_grad=1" conf/conformer.yaml > conf/benchmark/conformer.yaml cp conf/conformer.yaml conf/benchmark/conformer.yaml -sed -i +sed -i "s/ accum_grad: 2/ accum_grad: 1/g" conf/benchmark/conformer.yaml fp_item_list=(fp32) bs_item=(16 30) config_path=conf/benchmark/conformer.yaml From a6d4d67333542ea67821ea5b69244ed5e7045fc3 Mon Sep 17 00:00:00 2001 From: mmglove Date: Tue, 16 Nov 2021 17:44:46 +0800 Subject: [PATCH 3/5] update benchmark case --- tests/benchmark/conformer/run_benchmark.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/benchmark/conformer/run_benchmark.sh b/tests/benchmark/conformer/run_benchmark.sh index a6503117..78c2b950 100644 --- a/tests/benchmark/conformer/run_benchmark.sh +++ b/tests/benchmark/conformer/run_benchmark.sh @@ -9,7 +9,7 @@ function _set_params(){ output=${3:-"exp/conformer"} seed=${4:-"0"} ngpu=${5:-"1"} - profiler_options=${6:-"1"} + profiler_options=${6:-"None"} batch_size=${7:-"32"} fp_item=${8:-"fp32"} model_item=${9:-"conformer"} From 97878ff43df8c4b01293ee247c2d35f1bbd3cef2 Mon Sep 17 00:00:00 2001 From: mmglove Date: Tue, 16 Nov 2021 18:54:14 +0800 Subject: [PATCH 4/5] update benchmark case --- tests/benchmark/conformer/prepare.sh | 4 +++- tests/benchmark/conformer/run.sh | 1 - tests/benchmark/conformer/run_benchmark.sh | 2 +- 3 files changed, 4 insertions(+), 3 deletions(-) diff --git a/tests/benchmark/conformer/prepare.sh b/tests/benchmark/conformer/prepare.sh index 29719074..c5fae06a 100644 --- a/tests/benchmark/conformer/prepare.sh +++ b/tests/benchmark/conformer/prepare.sh @@ -1,4 +1,6 @@ - +cd ../../../ +pip install -e . # 安装pdspeech +cd - #Enter the example dir pushd ../../../examples/aishell/s1 diff --git a/tests/benchmark/conformer/run.sh b/tests/benchmark/conformer/run.sh index a32fc01e..79beb4e9 100644 --- a/tests/benchmark/conformer/run.sh +++ b/tests/benchmark/conformer/run.sh @@ -3,7 +3,6 @@ # 执行目录：需说明 CUR_DIR=${PWD} # PaddleSpeech/tests/benchmark/conformer cd ../../../ -pip install -e . # 安装pdspeech log_path=${LOG_PATH_INDEX_DIR:-$(pwd)} # benchmark系统指定该参数,不需要跑profile时,log_path指向存speed的目录 cd ${CUR_DIR} sed -i '/set\ -xe/d' run_benchmark.sh diff --git a/tests/benchmark/conformer/run_benchmark.sh b/tests/benchmark/conformer/run_benchmark.sh index 78c2b950..0ea6a2e9 100644 --- a/tests/benchmark/conformer/run_benchmark.sh +++ b/tests/benchmark/conformer/run_benchmark.sh @@ -17,7 +17,7 @@ function _set_params(){ run_log_path=${TRAIN_LOG_DIR:-$(pwd)} # TRAIN_LOG_DIR 后续QA设置该参数 # 添加日志解析需要的参数 base_batch_size=${batch_size} - mission_name="语音合成" + mission_name="语音识别" direction_id="1" ips_unit="sequences/sec" skip_steps=10 # 解析日志，有些模型前几个step耗时长，需要跳过 (必填) From 3ecb8cbfdd820cc52200c95b26978398032b23fe Mon Sep 17 00:00:00 2001 From: mmglove Date: Tue, 16 Nov 2021 19:32:39 +0800 Subject: [PATCH 5/5] update benchmark case --- tests/benchmark/conformer/run_benchmark.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/benchmark/conformer/run_benchmark.sh b/tests/benchmark/conformer/run_benchmark.sh index 0ea6a2e9..56b63e76 100644 --- a/tests/benchmark/conformer/run_benchmark.sh +++ b/tests/benchmark/conformer/run_benchmark.sh @@ -19,7 +19,7 @@ function _set_params(){ base_batch_size=${batch_size} mission_name="语音识别" direction_id="1" - ips_unit="sequences/sec" + ips_unit="sent./sec" skip_steps=10 # 解析日志，有些模型前几个step耗时长，需要跳过 (必填) keyword="ips:" # 解析日志，筛选出数据所在行的关键字 (必填) index="1"