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Merge pull request #5410 from Intsigstephon/dygraph
add fleet tests for supplementary
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Double_V
GitHub
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@ -47,6 +47,13 @@ bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python_PACT.txt 'lit
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bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python_FPGM.txt 'lite_train_lite_infer'
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```
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多机多卡的运行配置文件分别为 `train_infer_python_fleet.txt`, `train_infer_python_FPGM_fleet.txt` 和 `train_infer_python_PACT_fleet.txt`。
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运行时，需要修改配置文件中的 `gpu_list:xx.xx.xx.xx,yy.yy.yy.yy;0,1`。 将 `xx.xx.xx.xx` 替换为具体的 `ip` 地址，各个`ip`地址之间用`,`分隔。 另外，和单机训练
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不同，启动多机多卡训练需要在多机的每个节点上分别运行命令。以多机多卡量化训练为例，指令如下：
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```
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bash test_tipc/test_train_python.sh ./test_tipc/train_infer_python_PACT_fleet.txt 'lite_train_lite_infer'
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```
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运行相应指令后，在`test_tipc/output`文件夹下自动会保存运行日志。如'lite_train_lite_infer'模式运行后，在test_tipc/extra_output文件夹有以下文件：
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```
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@ -35,7 +35,6 @@ use_share_conv_key=$(func_parser_key "${lines[13]}")
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use_share_conv_list=$(func_parser_value "${lines[13]}")
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run_train_py=$(func_parser_value "${lines[14]}")
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LOG_PATH="./test_tipc/extra_output"
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mkdir -p ${LOG_PATH}
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status_log="${LOG_PATH}/results_python.log"
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@ -98,6 +97,8 @@ if [ ${MODE} = "lite_train_lite_infer" ] || [ ${MODE} = "whole_train_whole_infer
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cmd="${python} ${run_train_py} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_checkpoints} ${set_autocast} ${set_batchsize} ${set_use_custom_op} ${set_model_type} ${set_use_share_conv} ${set_amp_config}"
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elif [ ${#ips} -le 26 ];then # train with multi-gpu
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cmd="${python} -m paddle.distributed.launch --gpus=${gpu} ${run_train_py} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_checkpoints} ${set_autocast} ${set_batchsize} ${set_use_custom_op} ${set_model_type} ${set_use_share_conv} ${set_amp_config}"
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else
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cmd="${python} -m paddle.distributed.launch --ips=${ips} --gpus=${gpu} ${run_train_py} ${set_use_gpu} ${set_save_model} ${set_epoch} ${set_pretrain} ${set_checkpoints} ${set_autocast} ${set_batchsize} ${set_use_custom_op} ${set_model_type} ${set_use_share_conv} ${set_amp_config}"
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fi
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# run train
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@ -4,9 +4,9 @@ python:python3.7
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gpu_list:0|0,1
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use_gpu:True|True
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AMP.use_amp:True|False
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epoch:lite_train_lite_infer=20|whole_train_whole_infer=1000
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epoch:lite_train_lite_infer=2|whole_train_whole_infer=1000
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save_model_dir:./output/
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TRAIN.batch_size:lite_train_lite_infer=2|whole_train_whole_infer=4
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TRAIN.batch_size:lite_train_lite_infer=1280|whole_train_whole_infer=1280
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pretrained_model:null
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checkpoints:null
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use_custom_relu:False|True
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@ -0,0 +1,17 @@
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===========================train_params===========================
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model_name:ch_PPOCRv2_det
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python:python3.7
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gpu_list:xx.xx.xx.xx,yy.yy.yy.yy;0,1
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use_gpu:True
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AMP.use_amp:True|False
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epoch:lite_train_lite_infer=2|whole_train_whole_infer=1000
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save_model_dir:./output/
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TRAIN.batch_size:lite_train_lite_infer=1280|whole_train_whole_infer=1280
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pretrained_model:null
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checkpoints:null
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use_custom_relu:False|True
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model_type:cls|cls_distill|cls_distill_multiopt
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MODEL.siamese:False|True
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norm_train:train.py -c mv3_large_x0_5.yml -o prune_train=True
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quant_train:False
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prune_train:False
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@ -4,9 +4,9 @@ python:python3.7
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gpu_list:0|0,1
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use_gpu:True|True
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AMP.use_amp:True|False
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epoch:lite_train_lite_infer=20|whole_train_whole_infer=1000
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epoch:lite_train_lite_infer=2|whole_train_whole_infer=1000
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save_model_dir:./output/
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TRAIN.batch_size:lite_train_lite_infer=2|whole_train_whole_infer=4
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TRAIN.batch_size:lite_train_lite_infer=1280|whole_train_whole_infer=1280
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pretrained_model:null
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checkpoints:null
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use_custom_relu:False|True
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@ -0,0 +1,17 @@
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===========================train_params===========================
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model_name:ch_PPOCRv2_det
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python:python3.7
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gpu_list:xx.xx.xx.xx,yy.yy.yy.yy;0,1
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use_gpu:True
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AMP.use_amp:True|False
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epoch:lite_train_lite_infer=2|whole_train_whole_infer=1000
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save_model_dir:./output/
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TRAIN.batch_size:lite_train_lite_infer=1280|whole_train_whole_infer=1280
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pretrained_model:null
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checkpoints:null
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use_custom_relu:False|True
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model_type:cls|cls_distill|cls_distill_multiopt
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MODEL.siamese:False|True
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norm_train:train.py -c mv3_large_x0_5.yml -o quant_train=True
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quant_train:False
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prune_train:False
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@ -0,0 +1,17 @@
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===========================train_params===========================
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model_name:ch_PPOCRv2_det
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python:python3.7
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gpu_list:xx.xx.xx.xx,yy.yy.yy.yy;0,1
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use_gpu:True
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AMP.use_amp:True|False
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epoch:lite_train_lite_infer=2|whole_train_whole_infer=1000
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save_model_dir:./output/
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TRAIN.batch_size:lite_train_lite_infer=1280|whole_train_whole_infer=1280
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pretrained_model:null
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checkpoints:null
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use_custom_relu:False|True
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model_type:cls|cls_distill|cls_distill_multiopt
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MODEL.siamese:False|True
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norm_train: train.py -c mv3_large_x0_5.yml -o
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quant_train:False
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prune_train:False
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