/
modelcard.sh
222 lines (184 loc) · 18.5 KB
/
modelcard.sh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
function get_env() {
conda_env="vmamba"
nvcc -V
conda create -n ${conda_env} --clone base
conda init bash && source ~/.bashrc && conda activate vmamba
python -VV
pip -V
pip install torch==1.13.0 torchvision==0.14.0 torchaudio==0.13.0 --extra-index-url https://download.pytorch.org/whl/cu117
# We use py110 cu117 torch113
pip install packaging
pip install timm==0.4.12
pip install pytest chardet yacs termcolor
pip install submitit tensorboardX
pip install triton==2.0.0
pip install fvcore
pip install seaborn
cd selective_scan && pip install . && pytest
# you can also install packages below as an alternative...
# pip install triton==2.0.0
# pip install causal_conv1d==1.0.0 # causal_conv1d-1.0.0+cu118torch1.13cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
# pip install mamba_ssm==1.0.1 # mamba_ssm-1.0.1+cu118torch1.13cxx11abiFALSE-cp310-cp310-linux_x86_64.whl
}
function get_env_mmdet() {
pip install mmengine==0.10.1
pip install mmcv==2.1.0
pip install opencv-python-headless ftfy
pip install mmdet==3.3.0
pip install mmsegmentation==1.2.2
pip install mmpretrain==1.2.0
}
function dataset_to_memory() {
# README: copy data into memory
tar --use-compress-program=pigz -cvf ImageNet_ILSVRC2012.tar.pz ImageNet_ILSVRC2012/
sudo mount -t tmpfs -o size=150G tmpfs .media/memfs/
tar --use-compress-program=pigz -xvf ImageNet_ILSVRC2012.tar.pz -C /media/memfs/ # 5min
}
function classification() {
# ======================================================
export CODE=classification PYTHON=python
export nnodes=1 nrank=0 nprocs=8 mport=29501 maddr="127.0.0.1"
export pycmds="main.py --cfg configs/vssm/vssm_tiny_224.yaml --batch-size 64 --data-path /dataset/ImageNet2012 --output /tmp"
cd ${CODE}; ${PYTHON} -m torch.distributed.launch --nnodes ${nnodes} --node_rank ${nrank} --nproc_per_node ${nprocs} --master_addr ${maddr} --master_port ${mport} ${pycmds}
# ======================================================
export CODE=classification PYTHON=python
export nnodes=1 nrank=0 nprocs=8 mport=29501 maddr="127.0.0.1"
export pycmds="main.py --cfg configs/vssm/vssm_small_224.yaml --batch-size 64 --data-path /dataset/ImageNet2012 --output /tmp"
cd ${CODE}; ${PYTHON} -m torch.distributed.launch --nnodes ${nnodes} --node_rank ${nrank} --nproc_per_node ${nprocs} --master_addr ${maddr} --master_port ${mport} ${pycmds}
# ======================================================
export CODE=classification PYTHON=python
export nnodes=1 nrank=0 nprocs=8 mport=29501 maddr="127.0.0.1"
export pycmds="main.py --cfg configs/vssm/vssm_base_224.yaml --batch-size 64 --data-path /dataset/ImageNet2012 --output /tmp"
cd ${CODE}; ${PYTHON} -m torch.distributed.launch --nnodes ${nnodes} --node_rank ${nrank} --nproc_per_node ${nprocs} --master_addr ${maddr} --master_port ${mport} ${pycmds}
}
function detection() {
mkdir -p detection/data
ln -s /media/Disk1/Dataset/MSCOCO2017 detection/data/coco
# ======================================================
export CODE=detection PYTHON=python
export CONFIG=configs/vssm/mask_rcnn_vssm_fpn_coco_tiny.py
export CKPT=../../ckpts/classification/vssm/vssmbase/ckpt_epoch_260.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=detection PYTHON=python
export CONFIG=configs/vssm/mask_rcnn_vssm_fpn_coco_small.py
export CKPT=../../ckpts/classification/vssm/vssmsmall/ckpt_epoch_238.pth # TODO: use ema_ckpt_epoch_238.pth !!!
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=detection PYTHON=python
export CONFIG=configs/vssm/mask_rcnn_vssm_fpn_coco_base.py
export CKPT=../../ckpts/classification/vssm/vssmtiny/ckpt_epoch_292.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=detection PYTHON=python
export CONFIG=configs/vssm/mask_rcnn_vssm_fpn_coco_tiny_ms_3x.py
export CKPT=../../ckpts/classification/vssm/vssmtiny/ckpt_epoch_292.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=detection PYTHON=python
export CONFIG=configs/vssm/mask_rcnn_vssm_fpn_coco_small_ms_3x.py
export CKPT=../../ckpts/classification/vssm/vssmsmall/ckpt_epoch_238.pth # TODO: use ema_ckpt_epoch_238.pth !!!
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
}
function segmentation() {
mkdir -p segmentation/data/ade
ln -s /media/Disk1/Dataset/ADEChallengeData2016 segmentation/data/ade
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_tiny.py
export CKPT=../../ckpts/classification/vssm/vssmtiny/ckpt_epoch_292.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_small.py
export CKPT=../../ckpts/classification/vssm/vssmsmall/ema_ckpt_epoch_238.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_base.py
export CKPT=../../ckpts/classification/vssm/vssmbase/ckpt_epoch_260.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-640x640_small.py
export CKPT=../../ckpts/classification/vssm/vssmsmall/ema_ckpt_epoch_238.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-896x896_small.py
export CKPT=../../ckpts/classification/vssm/vssmsmall/ema_ckpt_epoch_238.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch --cfg-options model.backbone.pretrained=$CKPT
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_swin_4xb4-160k_ade20k-640x640_small.py
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_swin_4xb4-160k_ade20k-896x896_small.py
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_convnext_4xb4-160k_ade20k-640x640_small.py
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_convnext_4xb4-160k_ade20k-896x896_small.py
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/train.py $CONFIG --launcher pytorch
}
function segmentation_test_tta() {
mkdir -p segmentation/data/ade
ln -s /media/Disk1/Dataset/ADEChallengeData2016 segmentation/data/ade
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_tiny.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_vssm_4xb4-160k_ade20k-512x512_tiny/iter_144000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta --cfg-options model.backbone.pretrained=None
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_small.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_vssm_4xb4-160k_ade20k-512x512_small/iter_160000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta --cfg-options model.backbone.pretrained=None
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-512x512_base.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_vssm_4xb4-160k_ade20k-512x512_base/iter_128000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta --cfg-options model.backbone.pretrained=None
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_vssm_4xb4-160k_ade20k-640x640_small.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_vssm_4xb4-160k_ade20k-640x640_small/iter_112000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta --cfg-options model.backbone.pretrained=None
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_swin_4xb4-160k_ade20k-640x640_small.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_swin_4xb4-160k_ade20k-640x640_small/iter_160000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta
# ======================================================
export CODE=segmentation PYTHON=python
export CONFIG=configs/vssm/upernet_convnext_4xb4-160k_ade20k-640x640_small.py
export CKPT=../../ckpts/segmentation/work_dirs/upernet_convnext_4xb4-160k_ade20k-640x640_small/iter_160000.pth
cd $CODE; export GPUS=8 NNODES=${NNODES:-1} NODE_RANK=${NODE_RANK:-0} PORT=${PORT:-29500} MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}; PYTHONPATH="$PWD":$PYTHONPATH $PYTHON -m torch.distributed.launch --nnodes=$NNODES --node_rank=$NODE_RANK --master_addr=$MASTER_ADDR --nproc_per_node=$GPUS --master_port=$PORT ./tools/test.py $CONFIG $CKPT --launcher pytorch --tta
}
function analyze() {
CUDA_VISIBLE_DEVICES=0 python analyze/get_erf.py > analyze/show/erf/get_erf.log 2>&1
CUDA_VISIBLE_DEVICES=0 python analyze/get_flops.py > analyze/show/flops/flops.log 2>&1
CUDA_VISIBLE_DEVICES=0 python analyze/get_loss.py
# =====================================================
export ACTION=flops SCALENET=vssm; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/flops.log 2>&1
export ACTION=tiny SCALENET=vssm; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/vssmtiny_scale.log 2>&1
export ACTION=tiny SCALENET=swin; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/swintiny_scale.log 2>&1
export ACTION=tiny SCALENET=convnext; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/convnexttiny_scale.log 2>&1
export ACTION=tiny SCALENET=deit; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/deitsmall_scale.log 2>&1
export ACTION=tiny SCALENET=resnet; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/resnet50_scale.log 2>&1
export ACTION=small SCALENET=vssm; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/vssmsmall_scale.log 2>&1
export ACTION=small SCALENET=swin; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/swinsmall_scale.log 2>&1
export ACTION=small SCALENET=convnext; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/convnextsmall_scale.log 2>&1
export ACTION=small SCALENET=resnet; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/resnet101_scale.log 2>&1
export ACTION=base SCALENET=vssm; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/vssmbase_scale.log 2>&1
export ACTION=base SCALENET=swin; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/swinbase_scale.log 2>&1
export ACTION=base SCALENET=convnext; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/convnextbase_scale.log 2>&1
export ACTION=base SCALENET=deit; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/deitbase_scale.log 2>&1
export ACTION=base SCALENET=replknet; CUDA_VISIBLE_DEVICES=0 python analyze/get_scaleup.py >> analyze/show/scaleup.log/replknet31b_scale.log 2>&1
# ============================================
python analyze/scaleup_show.py
}