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add ci for mae and convmae (PaddlePaddle#197)
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39 changes: 39 additions & 0 deletions
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tests/CI/ssl/convmae/convmae_convvit_base_patch16_ft_in1k_1n8c_dp_fp16o1.sh
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# Copyright (c) 2023 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. | ||
|
||
#unset PADDLE_TRAINER_ENDPOINTS | ||
#export PADDLE_NNODES=4 | ||
#export PADDLE_MASTER="10.67.228.16:12538" | ||
#export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | ||
#export PADDLE_JOB_ID=ConvMAE | ||
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# 4 nodes finetune setting | ||
ACCUM_ITER=1 | ||
PRETRAIN_CHKPT='pretrained/convmae/convmae_convvit_base_pretrained_1599ep.pd' | ||
IMAGENET_DIR=./dataset/ILSVRC2012/ | ||
python -m paddle.distributed.launch \ | ||
--nnodes=$PADDLE_NNODES \ | ||
--master=$PADDLE_MASTER \ | ||
--devices=$CUDA_VISIBLE_DEVICES \ | ||
../../task/ssl/mae/main_finetune.py \ | ||
--accum_iter $ACCUM_ITER \ | ||
--print_freq 1 \ | ||
--max_train_step 600 \ | ||
--batch_size 32 \ | ||
--model convvit_base_patch16 \ | ||
--finetune ${PRETRAIN_CHKPT} \ | ||
--epochs 100 \ | ||
--blr 5e-4 --layer_decay 0.65 \ | ||
--weight_decay 0.05 --drop_path 0.1 --reprob 0.25 --mixup 0.8 --cutmix 1.0 \ | ||
--dist_eval --data_path ${IMAGENET_DIR} |
41 changes: 41 additions & 0 deletions
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tests/CI/ssl/convmae/convmae_convvit_base_patch16_lp_in1k_1n8c_dp_fp16o1.sh
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
|
||
#unset PADDLE_TRAINER_ENDPOINTS | ||
#export PADDLE_NNODES=4 | ||
#export PADDLE_MASTER="10.67.228.16:12538" | ||
#export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | ||
#export PADDLE_JOB_ID=ConvMAE | ||
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IMAGENET_DIR=./dataset/ILSVRC2012/ | ||
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# 1 for four node, 4 for single node | ||
ACCUM_ITER=1 | ||
PRETRAIN_CHKPT='pretrained/convmae/convmae_convvit_base_pretrained_1599ep.pd' | ||
python -m paddle.distributed.launch \ | ||
--nnodes=$PADDLE_NNODES \ | ||
--master=$PADDLE_MASTER \ | ||
--devices=$CUDA_VISIBLE_DEVICES \ | ||
../../task/ssl/mae/main_linprobe.py \ | ||
--accum_iter $ACCUM_ITER \ | ||
--print_freq 1 \ | ||
--max_train_step 200 \ | ||
--batch_size 128 \ | ||
--model convvit_base_patch16 \ | ||
--global_pool \ | ||
--finetune ${PRETRAIN_CHKPT} \ | ||
--epochs 90 \ | ||
--blr 0.1 \ | ||
--weight_decay 0.0 \ | ||
--dist_eval --data_path ${IMAGENET_DIR} |
39 changes: 39 additions & 0 deletions
39
tests/CI/ssl/convmae/convmae_convvit_base_patch16_pt_in1k_1n8c_dp_fp16o1.sh
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
|
||
#unset PADDLE_TRAINER_ENDPOINTS | ||
#export PADDLE_NNODES=3 | ||
#export PADDLE_MASTER="10.67.228.16:12538" | ||
#export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | ||
#export PADDLE_JOB_ID=ConvMAE | ||
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# 3 nodes for pretrain | ||
ACCUM_ITER=1 | ||
IMAGENET_DIR=./dataset/ILSVRC2012/ | ||
python -m paddle.distributed.launch \ | ||
--nnodes=$PADDLE_NNODES \ | ||
--master=$PADDLE_MASTER \ | ||
--devices=$CUDA_VISIBLE_DEVICES \ | ||
../../task/ssl/mae/main_pretrain.py \ | ||
--accum_iter $ACCUM_ITER \ | ||
--print_freq 1 \ | ||
--max_train_step 100 \ | ||
--batch_size 128 \ | ||
--model convmae_convvit_base_patch16 \ | ||
--norm_pix_loss \ | ||
--mask_ratio 0.75 \ | ||
--epochs 1600 \ | ||
--warmup_epochs 40 \ | ||
--blr 1.5e-4 --weight_decay 0.05 \ | ||
--data_path ${IMAGENET_DIR} |
43 changes: 43 additions & 0 deletions
43
tests/CI/ssl/mae/mae_vit_base_patch16_ft_in1k_1n8c_dp_fp16o1.sh
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# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
|
||
#unset PADDLE_TRAINER_ENDPOINTS | ||
#export PADDLE_NNODES=4 | ||
#export PADDLE_MASTER="10.67.228.16:12538" | ||
#export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 | ||
#export PADDLE_JOB_ID=MAE | ||
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# for single node finetune | ||
# batch_size 32, ACCUM_ITER=4, effective batch size: 1024 | ||
# batch_size 128, ACCUM_ITER=1, effective batch size: 1024 | ||
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# 4 nodes finetune setting | ||
ACCUM_ITER=1 | ||
PRETRAIN_CHKPT='pretrained/mae/mae_pretrain_vit_base_1599ep.pd' | ||
IMAGENET_DIR=./dataset/ILSVRC2012/ | ||
python -m paddle.distributed.launch \ | ||
--nnodes=$PADDLE_NNODES \ | ||
--master=$PADDLE_MASTER \ | ||
--devices=$CUDA_VISIBLE_DEVICES \ | ||
../../task/ssl/mae/main_finetune.py \ | ||
--accum_iter $ACCUM_ITER \ | ||
--print_freq 1 \ | ||
--max_train_step 600 \ | ||
--batch_size 32 \ | ||
--model vit_base_patch16 \ | ||
--finetune ${PRETRAIN_CHKPT} \ | ||
--epochs 100 \ | ||
--blr 5e-4 --layer_decay 0.65 \ | ||
--weight_decay 0.05 --drop_path 0.1 --reprob 0.25 --mixup 0.8 --cutmix 1.0 \ | ||
--dist_eval --data_path ${IMAGENET_DIR} |
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