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fix ResNeXt101_wsl bugs
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5 files changed

+524
-4
lines changed

5 files changed

+524
-4
lines changed

‎ppcls/arch/backbone/model_zoo/resnext101_wsl.py

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -460,17 +460,17 @@ def ResNeXt101_32x8d_wsl(pretrained=False, use_ssld=False, **kwargs):
460460
return model
461461

462462

463-
def ResNeXt101_32x16d_wsl(**args):
463+
def ResNeXt101_32x16d_wsl(pretrained=False, use_ssld=False, **kwargs):
464464
model = ResNeXt101WSL(cardinality=32, width=16, **kwargs)
465465
_load_pretrained(
466466
pretrained,
467467
model,
468-
MODEL_URLS["ResNeXt101_32x16d_ws"],
468+
MODEL_URLS["ResNeXt101_32x16d_wsl"],
469469
use_ssld=use_ssld)
470470
return model
471471

472472

473-
def ResNeXt101_32x32d_wsl(**args):
473+
def ResNeXt101_32x32d_wsl(pretrained=False, use_ssld=False, **kwargs):
474474
model = ResNeXt101WSL(cardinality=32, width=32, **kwargs)
475475
_load_pretrained(
476476
pretrained,
@@ -480,7 +480,7 @@ def ResNeXt101_32x32d_wsl(**args):
480480
return model
481481

482482

483-
def ResNeXt101_32x48d_wsl(**args):
483+
def ResNeXt101_32x48d_wsl(pretrained=False, use_ssld=False, **kwargs):
484484
model = ResNeXt101WSL(cardinality=32, width=48, **kwargs)
485485
_load_pretrained(
486486
pretrained,

‎ppcls/configs/ImageNet/ResNeXt101_wsl/ResNeXt101_32x16d_wsl.yaml

Lines changed: 130 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,130 @@
1+
# global configs
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Global:
3+
checkpoints: null
4+
pretrained_model: null
5+
output_dir: ./output/
6+
device: gpu
7+
save_interval: 1
8+
eval_during_train: True
9+
eval_interval: 1
10+
epochs: 120
11+
print_batch_step: 10
12+
use_visualdl: False
13+
# used for static mode and model export
14+
image_shape: [3, 224, 224]
15+
save_inference_dir: ./inference
16+
17+
# model architecture
18+
Arch:
19+
name: ResNeXt101_32x16d_wsl
20+
class_num: 1000
21+
22+
# loss function config for traing/eval process
23+
Loss:
24+
Train:
25+
- CELoss:
26+
weight: 1.0
27+
Eval:
28+
- CELoss:
29+
weight: 1.0
30+
31+
32+
Optimizer:
33+
name: Momentum
34+
momentum: 0.9
35+
lr:
36+
name: Piecewise
37+
learning_rate: 0.1
38+
decay_epochs: [30, 60, 90]
39+
values: [0.1, 0.01, 0.001, 0.0001]
40+
regularizer:
41+
name: 'L2'
42+
coeff: 0.0001
43+
44+
45+
# data loader for train and eval
46+
DataLoader:
47+
Train:
48+
dataset:
49+
name: ImageNetDataset
50+
image_root: ./dataset/ILSVRC2012/
51+
cls_label_path: ./dataset/ILSVRC2012/train_list.txt
52+
transform_ops:
53+
- DecodeImage:
54+
to_rgb: True
55+
channel_first: False
56+
- RandCropImage:
57+
size: 224
58+
- RandFlipImage:
59+
flip_code: 1
60+
- NormalizeImage:
61+
scale: 1.0/255.0
62+
mean: [0.485, 0.456, 0.406]
63+
std: [0.229, 0.224, 0.225]
64+
order: ''
65+
66+
sampler:
67+
name: DistributedBatchSampler
68+
batch_size: 64
69+
drop_last: False
70+
shuffle: True
71+
loader:
72+
num_workers: 4
73+
use_shared_memory: True
74+
75+
Eval:
76+
dataset:
77+
name: ImageNetDataset
78+
image_root: ./dataset/ILSVRC2012/
79+
cls_label_path: ./dataset/ILSVRC2012/val_list.txt
80+
transform_ops:
81+
- DecodeImage:
82+
to_rgb: True
83+
channel_first: False
84+
- ResizeImage:
85+
resize_short: 256
86+
- CropImage:
87+
size: 224
88+
- NormalizeImage:
89+
scale: 1.0/255.0
90+
mean: [0.485, 0.456, 0.406]
91+
std: [0.229, 0.224, 0.225]
92+
order: ''
93+
sampler:
94+
name: DistributedBatchSampler
95+
batch_size: 64
96+
drop_last: False
97+
shuffle: False
98+
loader:
99+
num_workers: 4
100+
use_shared_memory: True
101+
102+
Infer:
103+
infer_imgs: docs/images/whl/demo.jpg
104+
batch_size: 10
105+
transforms:
106+
- DecodeImage:
107+
to_rgb: True
108+
channel_first: False
109+
- ResizeImage:
110+
resize_short: 256
111+
- CropImage:
112+
size: 224
113+
- NormalizeImage:
114+
scale: 1.0/255.0
115+
mean: [0.485, 0.456, 0.406]
116+
std: [0.229, 0.224, 0.225]
117+
order: ''
118+
- ToCHWImage:
119+
PostProcess:
120+
name: Topk
121+
topk: 5
122+
class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
123+
124+
Metric:
125+
Train:
126+
- TopkAcc:
127+
topk: [1, 5]
128+
Eval:
129+
- TopkAcc:
130+
topk: [1, 5]

‎ppcls/configs/ImageNet/ResNeXt101_wsl/ResNeXt101_32x32d_wsl.yaml

Lines changed: 130 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,130 @@
1+
# global configs
2+
Global:
3+
checkpoints: null
4+
pretrained_model: null
5+
output_dir: ./output/
6+
device: gpu
7+
save_interval: 1
8+
eval_during_train: True
9+
eval_interval: 1
10+
epochs: 120
11+
print_batch_step: 10
12+
use_visualdl: False
13+
# used for static mode and model export
14+
image_shape: [3, 224, 224]
15+
save_inference_dir: ./inference
16+
17+
# model architecture
18+
Arch:
19+
name: ResNeXt101_32x32d_wsl
20+
class_num: 1000
21+
22+
# loss function config for traing/eval process
23+
Loss:
24+
Train:
25+
- CELoss:
26+
weight: 1.0
27+
Eval:
28+
- CELoss:
29+
weight: 1.0
30+
31+
32+
Optimizer:
33+
name: Momentum
34+
momentum: 0.9
35+
lr:
36+
name: Piecewise
37+
learning_rate: 0.1
38+
decay_epochs: [30, 60, 90]
39+
values: [0.1, 0.01, 0.001, 0.0001]
40+
regularizer:
41+
name: 'L2'
42+
coeff: 0.0001
43+
44+
45+
# data loader for train and eval
46+
DataLoader:
47+
Train:
48+
dataset:
49+
name: ImageNetDataset
50+
image_root: ./dataset/ILSVRC2012/
51+
cls_label_path: ./dataset/ILSVRC2012/train_list.txt
52+
transform_ops:
53+
- DecodeImage:
54+
to_rgb: True
55+
channel_first: False
56+
- RandCropImage:
57+
size: 224
58+
- RandFlipImage:
59+
flip_code: 1
60+
- NormalizeImage:
61+
scale: 1.0/255.0
62+
mean: [0.485, 0.456, 0.406]
63+
std: [0.229, 0.224, 0.225]
64+
order: ''
65+
66+
sampler:
67+
name: DistributedBatchSampler
68+
batch_size: 64
69+
drop_last: False
70+
shuffle: True
71+
loader:
72+
num_workers: 4
73+
use_shared_memory: True
74+
75+
Eval:
76+
dataset:
77+
name: ImageNetDataset
78+
image_root: ./dataset/ILSVRC2012/
79+
cls_label_path: ./dataset/ILSVRC2012/val_list.txt
80+
transform_ops:
81+
- DecodeImage:
82+
to_rgb: True
83+
channel_first: False
84+
- ResizeImage:
85+
resize_short: 256
86+
- CropImage:
87+
size: 224
88+
- NormalizeImage:
89+
scale: 1.0/255.0
90+
mean: [0.485, 0.456, 0.406]
91+
std: [0.229, 0.224, 0.225]
92+
order: ''
93+
sampler:
94+
name: DistributedBatchSampler
95+
batch_size: 64
96+
drop_last: False
97+
shuffle: False
98+
loader:
99+
num_workers: 4
100+
use_shared_memory: True
101+
102+
Infer:
103+
infer_imgs: docs/images/whl/demo.jpg
104+
batch_size: 10
105+
transforms:
106+
- DecodeImage:
107+
to_rgb: True
108+
channel_first: False
109+
- ResizeImage:
110+
resize_short: 256
111+
- CropImage:
112+
size: 224
113+
- NormalizeImage:
114+
scale: 1.0/255.0
115+
mean: [0.485, 0.456, 0.406]
116+
std: [0.229, 0.224, 0.225]
117+
order: ''
118+
- ToCHWImage:
119+
PostProcess:
120+
name: Topk
121+
topk: 5
122+
class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
123+
124+
Metric:
125+
Train:
126+
- TopkAcc:
127+
topk: [1, 5]
128+
Eval:
129+
- TopkAcc:
130+
topk: [1, 5]

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