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961fdd2c
编写于
6月 13, 2022
作者:
W
Wei Shengyu
提交者:
GitHub
6月 13, 2022
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差异文件
Merge pull request #2026 from weisy11/update_car_doc
Update car doc
上级
f70c566b
41a3a676
变更
11
展开全部
隐藏空白更改
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并排
Showing
11 changed file
with
1304 addition
and
0 deletion
+1304
-0
deploy/configs/PULC/car_exists/inference_car_exists.yaml
deploy/configs/PULC/car_exists/inference_car_exists.yaml
+36
-0
deploy/images/PULC/car_exists/objects365_00001507.jpeg
deploy/images/PULC/car_exists/objects365_00001507.jpeg
+0
-0
deploy/images/PULC/car_exists/objects365_00001521.jpeg
deploy/images/PULC/car_exists/objects365_00001521.jpeg
+0
-0
docs/images/PULC/docs/car_exists_data_demo.jpeg
docs/images/PULC/docs/car_exists_data_demo.jpeg
+0
-0
docs/zh_CN/PULC/PULC_car_exists.md
docs/zh_CN/PULC/PULC_car_exists.md
+447
-0
ppcls/configs/PULC/car_exists/MobileNetV3_small_x0_35.yaml
ppcls/configs/PULC/car_exists/MobileNetV3_small_x0_35.yaml
+139
-0
ppcls/configs/PULC/car_exists/PPLCNet_x1_0.yaml
ppcls/configs/PULC/car_exists/PPLCNet_x1_0.yaml
+152
-0
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_distillation.yaml
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_distillation.yaml
+169
-0
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_search.yaml
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_search.yaml
+152
-0
ppcls/configs/PULC/car_exists/SwinTransformer_tiny_patch4_window7_224.yaml
...C/car_exists/SwinTransformer_tiny_patch4_window7_224.yaml
+169
-0
ppcls/configs/PULC/car_exists/search.yaml
ppcls/configs/PULC/car_exists/search.yaml
+40
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未找到文件。
deploy/configs/PULC/car_exists/inference_car_exists.yaml
0 → 100644
浏览文件 @
961fdd2c
Global
:
infer_imgs
:
"
./images/PULC/car_exists/objects365_00001507.jpeg"
inference_model_dir
:
"
./models/car_exists_infer"
batch_size
:
1
use_gpu
:
True
enable_mkldnn
:
False
cpu_num_threads
:
10
enable_benchmark
:
True
use_fp16
:
False
ir_optim
:
True
use_tensorrt
:
False
gpu_mem
:
8000
enable_profile
:
False
PreProcess
:
transform_ops
:
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
0.00392157
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
channel_num
:
3
-
ToCHWImage
:
PostProcess
:
main_indicator
:
ThreshOutput
ThreshOutput
:
threshold
:
0.5
label_0
:
nocar
label_1
:
contains_car
SavePreLabel
:
save_dir
:
./pre_label/
deploy/images/PULC/car_exists/objects365_00001507.jpeg
0 → 100644
浏览文件 @
961fdd2c
157.1 KB
deploy/images/PULC/car_exists/objects365_00001521.jpeg
0 → 100644
浏览文件 @
961fdd2c
178.0 KB
docs/images/PULC/docs/car_exists_data_demo.jpeg
0 → 100644
浏览文件 @
961fdd2c
157.1 KB
docs/zh_CN/PULC/PULC_car_exists.md
0 → 100644
浏览文件 @
961fdd2c
此差异已折叠。
点击以展开。
ppcls/configs/PULC/car_exists/MobileNetV3_small_x0_35.yaml
0 → 100644
浏览文件 @
961fdd2c
# global configs
Global
:
checkpoints
:
null
pretrained_model
:
null
output_dir
:
./output/
device
:
gpu
save_interval
:
1
eval_during_train
:
True
eval_interval
:
1
start_eval_epoch
:
10
epochs
:
20
print_batch_step
:
10
use_visualdl
:
False
# used for static mode and model export
image_shape
:
[
3
,
224
,
224
]
save_inference_dir
:
./inference
# training model under @to_static
to_static
:
False
use_dali
:
False
# model architecture
Arch
:
name
:
MobileNetV3_small_x0_35
class_num
:
2
pretrained
:
True
use_sync_bn
:
True
# loss function config for traing/eval process
Loss
:
Train
:
-
CELoss
:
weight
:
1.0
epsilon
:
0.1
Eval
:
-
CELoss
:
weight
:
1.0
Optimizer
:
name
:
Momentum
momentum
:
0.9
lr
:
name
:
Cosine
learning_rate
:
0.05
warmup_epoch
:
5
regularizer
:
name
:
'
L2'
coeff
:
0.00001
# data loader for train and eval
DataLoader
:
Train
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/train_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
RandCropImage
:
size
:
224
-
RandFlipImage
:
flip_code
:
1
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
512
drop_last
:
False
shuffle
:
True
loader
:
num_workers
:
8
use_shared_memory
:
True
Eval
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/val_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
False
loader
:
num_workers
:
4
use_shared_memory
:
True
Infer
:
infer_imgs
:
deploy/images/PULC/car_exists/objects365_00001507.jpeg
batch_size
:
10
transforms
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
ToCHWImage
:
PostProcess
:
name
:
ThreshOutput
threshold
:
0.5
label_0
:
nobody
label_1
:
someone
Metric
:
Train
:
-
TopkAcc
:
topk
:
[
1
,
2
]
Eval
:
-
TprAtFpr
:
max_fpr
:
0.01
-
TopkAcc
:
topk
:
[
1
,
2
]
ppcls/configs/PULC/car_exists/PPLCNet_x1_0.yaml
0 → 100644
浏览文件 @
961fdd2c
# global configs
Global
:
checkpoints
:
null
pretrained_model
:
null
output_dir
:
./output/
device
:
gpu
save_interval
:
1
eval_during_train
:
True
eval_interval
:
1
start_eval_epoch
:
10
epochs
:
20
print_batch_step
:
10
use_visualdl
:
False
# used for static mode and model export
image_shape
:
[
3
,
224
,
224
]
save_inference_dir
:
./inference
# training model under @to_static
to_static
:
False
use_dali
:
False
# model architecture
Arch
:
name
:
PPLCNet_x1_0
class_num
:
2
pretrained
:
True
use_ssld
:
True
use_sync_bn
:
True
# loss function config for traing/eval process
Loss
:
Train
:
-
CELoss
:
weight
:
1.0
Eval
:
-
CELoss
:
weight
:
1.0
Optimizer
:
name
:
Momentum
momentum
:
0.9
lr
:
name
:
Cosine
learning_rate
:
0.0125
warmup_epoch
:
5
regularizer
:
name
:
'
L2'
coeff
:
0.00004
# data loader for train and eval
DataLoader
:
Train
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/train_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
RandCropImage
:
size
:
192
-
RandFlipImage
:
flip_code
:
1
-
TimmAutoAugment
:
prob
:
0.5
config_str
:
rand-m9-mstd0.5-inc1
interpolation
:
bicubic
img_size
:
192
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
RandomErasing
:
EPSILON
:
0.5
sl
:
0.02
sh
:
1.0/3.0
r1
:
0.3
attempt
:
10
use_log_aspect
:
True
mode
:
pixel
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
True
loader
:
num_workers
:
8
use_shared_memory
:
True
Eval
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists
cls_label_path
:
./dataset/car_exists/val_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
False
loader
:
num_workers
:
4
use_shared_memory
:
True
Infer
:
infer_imgs
:
deploy/images/PULC/car_exists/objects365_00001507.jpeg
batch_size
:
10
transforms
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
ToCHWImage
:
PostProcess
:
name
:
ThreshOutput
threshold
:
0.9
label_0
:
nobody
label_1
:
someone
Metric
:
Train
:
-
TopkAcc
:
topk
:
[
1
,
2
]
Eval
:
-
TprAtFpr
:
max_fpr
:
0.01
-
TopkAcc
:
topk
:
[
1
,
2
]
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_distillation.yaml
0 → 100644
浏览文件 @
961fdd2c
# global configs
Global
:
checkpoints
:
null
pretrained_model
:
null
output_dir
:
./output
device
:
gpu
save_interval
:
1
eval_during_train
:
True
start_eval_epoch
:
1
eval_interval
:
1
epochs
:
20
print_batch_step
:
10
use_visualdl
:
False
# used for static mode and model export
image_shape
:
[
3
,
224
,
224
]
save_inference_dir
:
./inference
# training model under @to_static
to_static
:
False
use_dali
:
False
# model architecture
Arch
:
name
:
"
DistillationModel"
class_num
:
&class_num
2
# if not null, its lengths should be same as models
pretrained_list
:
# if not null, its lengths should be same as models
freeze_params_list
:
-
True
-
False
use_sync_bn
:
True
models
:
-
Teacher
:
name
:
ResNet101_vd
class_num
:
*class_num
-
Student
:
name
:
PPLCNet_x1_0
class_num
:
*class_num
pretrained
:
True
use_ssld
:
True
infer_model_name
:
"
Student"
# loss function config for traing/eval process
Loss
:
Train
:
-
DistillationDMLLoss
:
weight
:
1.0
model_name_pairs
:
-
[
"
Student"
,
"
Teacher"
]
Eval
:
-
CELoss
:
weight
:
1.0
Optimizer
:
name
:
Momentum
momentum
:
0.9
lr
:
name
:
Cosine
learning_rate
:
0.01
warmup_epoch
:
5
regularizer
:
name
:
'
L2'
coeff
:
0.00004
# data loader for train and eval
DataLoader
:
Train
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/train_list_for_distill.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
RandCropImage
:
size
:
192
-
RandFlipImage
:
flip_code
:
1
-
TimmAutoAugment
:
prob
:
0.0
config_str
:
rand-m9-mstd0.5-inc1
interpolation
:
bicubic
img_size
:
192
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
RandomErasing
:
EPSILON
:
0.1
sl
:
0.02
sh
:
1.0/3.0
r1
:
0.3
attempt
:
10
use_log_aspect
:
True
mode
:
pixel
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
True
loader
:
num_workers
:
16
use_shared_memory
:
True
Eval
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/val_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
False
loader
:
num_workers
:
4
use_shared_memory
:
True
Infer
:
infer_imgs
:
deploy/images/PULC/car_exists/objects365_00001507.jpeg
batch_size
:
10
transforms
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
ToCHWImage
:
PostProcess
:
name
:
ThreshOutput
threshold
:
0.5
label_0
:
nobody
label_1
:
someone
Metric
:
Train
:
-
DistillationTopkAcc
:
model_key
:
"
Student"
topk
:
[
1
,
2
]
Eval
:
-
TprAtFpr
:
max_fpr
:
0.01
-
TopkAcc
:
topk
:
[
1
,
2
]
ppcls/configs/PULC/car_exists/PPLCNet_x1_0_search.yaml
0 → 100644
浏览文件 @
961fdd2c
# global configs
Global
:
checkpoints
:
null
pretrained_model
:
null
output_dir
:
./output/
device
:
gpu
save_interval
:
1
eval_during_train
:
True
eval_interval
:
1
start_eval_epoch
:
10
epochs
:
20
print_batch_step
:
10
use_visualdl
:
False
# used for static mode and model export
image_shape
:
[
3
,
224
,
224
]
save_inference_dir
:
./inference
# training model under @to_static
to_static
:
False
use_dali
:
False
# model architecture
Arch
:
name
:
PPLCNet_x1_0
class_num
:
2
pretrained
:
True
use_ssld
:
True
use_sync_bn
:
True
# loss function config for traing/eval process
Loss
:
Train
:
-
CELoss
:
weight
:
1.0
Eval
:
-
CELoss
:
weight
:
1.0
Optimizer
:
name
:
Momentum
momentum
:
0.9
lr
:
name
:
Cosine
learning_rate
:
0.01
warmup_epoch
:
5
regularizer
:
name
:
'
L2'
coeff
:
0.00004
# data loader for train and eval
DataLoader
:
Train
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/train_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
RandCropImage
:
size
:
224
-
RandFlipImage
:
flip_code
:
1
-
TimmAutoAugment
:
prob
:
0.0
config_str
:
rand-m9-mstd0.5-inc1
interpolation
:
bicubic
img_size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
RandomErasing
:
EPSILON
:
0.0
sl
:
0.02
sh
:
1.0/3.0
r1
:
0.3
attempt
:
10
use_log_aspect
:
True
mode
:
pixel
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
True
loader
:
num_workers
:
8
use_shared_memory
:
True
Eval
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/val_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
False
loader
:
num_workers
:
4
use_shared_memory
:
True
Infer
:
infer_imgs
:
deploy/images/PULC/car_exists/objects365_00001507.jpeg
batch_size
:
10
transforms
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
ToCHWImage
:
PostProcess
:
name
:
ThreshOutput
threshold
:
0.5
label_0
:
nobody
label_1
:
someone
Metric
:
Train
:
-
TopkAcc
:
topk
:
[
1
,
2
]
Eval
:
-
TprAtFpr
:
max_fpr
:
0.01
-
TopkAcc
:
topk
:
[
1
,
2
]
ppcls/configs/PULC/car_exists/SwinTransformer_tiny_patch4_window7_224.yaml
0 → 100644
浏览文件 @
961fdd2c
# global configs
Global
:
checkpoints
:
null
pretrained_model
:
null
output_dir
:
./output/
device
:
gpu
save_interval
:
1
eval_during_train
:
True
eval_interval
:
1
start_eval_epoch
:
10
epochs
:
20
print_batch_step
:
10
use_visualdl
:
False
# used for static mode and model export
image_shape
:
[
3
,
224
,
224
]
save_inference_dir
:
./inference
# training model under @to_static
to_static
:
False
use_dali
:
False
# mixed precision training
AMP
:
scale_loss
:
128.0
use_dynamic_loss_scaling
:
True
# O1: mixed fp16
level
:
O1
# model architecture
Arch
:
name
:
SwinTransformer_tiny_patch4_window7_224
class_num
:
2
pretrained
:
True
# loss function config for traing/eval process
Loss
:
Train
:
-
CELoss
:
weight
:
1.0
epsilon
:
0.1
Eval
:
-
CELoss
:
weight
:
1.0
Optimizer
:
name
:
AdamW
beta1
:
0.9
beta2
:
0.999
epsilon
:
1e-8
weight_decay
:
0.05
no_weight_decay_name
:
absolute_pos_embed relative_position_bias_table .bias norm
one_dim_param_no_weight_decay
:
True
lr
:
name
:
Cosine
learning_rate
:
1e-4
eta_min
:
2e-6
warmup_epoch
:
5
warmup_start_lr
:
2e-7
# data loader for train and eval
DataLoader
:
Train
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/train_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
RandCropImage
:
size
:
224
interpolation
:
bicubic
backend
:
pil
-
RandFlipImage
:
flip_code
:
1
-
TimmAutoAugment
:
config_str
:
rand-m9-mstd0.5-inc1
interpolation
:
bicubic
img_size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
RandomErasing
:
EPSILON
:
0.25
sl
:
0.02
sh
:
1.0/3.0
r1
:
0.3
attempt
:
10
use_log_aspect
:
True
mode
:
pixel
batch_transform_ops
:
-
OpSampler
:
MixupOperator
:
alpha
:
0.8
prob
:
0.5
CutmixOperator
:
alpha
:
1.0
prob
:
0.5
sampler
:
name
:
DistributedBatchSampler
batch_size
:
128
drop_last
:
False
shuffle
:
True
loader
:
num_workers
:
8
use_shared_memory
:
True
Eval
:
dataset
:
name
:
ImageNetDataset
image_root
:
./dataset/car_exists/
cls_label_path
:
./dataset/car_exists/val_list.txt
transform_ops
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
sampler
:
name
:
DistributedBatchSampler
batch_size
:
64
drop_last
:
False
shuffle
:
False
loader
:
num_workers
:
8
use_shared_memory
:
True
Infer
:
infer_imgs
:
deploy/images/PULC/car_exists/objects365_00001507.jpeg
batch_size
:
10
transforms
:
-
DecodeImage
:
to_rgb
:
True
channel_first
:
False
-
ResizeImage
:
resize_short
:
256
-
CropImage
:
size
:
224
-
NormalizeImage
:
scale
:
1.0/255.0
mean
:
[
0.485
,
0.456
,
0.406
]
std
:
[
0.229
,
0.224
,
0.225
]
order
:
'
'
-
ToCHWImage
:
PostProcess
:
name
:
ThreshOutput
threshold
:
0.5
label_0
:
nobody
label_1
:
someone
Metric
:
Train
:
-
TopkAcc
:
topk
:
[
1
,
2
]
Eval
:
-
TprAtFpr
:
max_fpr
:
0.01
-
TopkAcc
:
topk
:
[
1
,
2
]
ppcls/configs/PULC/car_exists/search.yaml
0 → 100644
浏览文件 @
961fdd2c
base_config_file
:
ppcls/configs/PULC/person_exists/PPLCNet_x1_0_search.yaml
distill_config_file
:
ppcls/configs/PULC/person_exists/PPLCNet_x1_0_distillation.yaml
gpus
:
0,1,2,3
output_dir
:
output/search_person_cls
search_times
:
1
search_dict
:
-
search_key
:
lrs
replace_config
:
-
Optimizer.lr.learning_rate
search_values
:
[
0.0075
,
0.01
,
0.0125
]
-
search_key
:
resolutions
replace_config
:
-
DataLoader.Train.dataset.transform_ops.1.RandCropImage.size
-
DataLoader.Train.dataset.transform_ops.3.TimmAutoAugment.img_size
search_values
:
[
176
,
192
,
224
]
-
search_key
:
ra_probs
replace_config
:
-
DataLoader.Train.dataset.transform_ops.3.TimmAutoAugment.prob
search_values
:
[
0.0
,
0.1
,
0.5
]
-
search_key
:
re_probs
replace_config
:
-
DataLoader.Train.dataset.transform_ops.5.RandomErasing.EPSILON
search_values
:
[
0.0
,
0.1
,
0.5
]
-
search_key
:
lr_mult_list
replace_config
:
-
Arch.lr_mult_list
search_values
:
-
[
0.0
,
0.2
,
0.4
,
0.6
,
0.8
,
1.0
]
-
[
0.0
,
0.4
,
0.4
,
0.8
,
0.8
,
1.0
]
-
[
1.0
,
1.0
,
1.0
,
1.0
,
1.0
,
1.0
]
teacher
:
rm_keys
:
-
Arch.lr_mult_list
search_values
:
-
ResNet101_vd
-
ResNet50_vd
final_replace
:
Arch.lr_mult_list
:
Arch.models.1.Student.lr_mult_list
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