提交 b1a51f6a 编写于 作者: C cuicheng01

Update mobile model configs

上级 57c4e65f
...@@ -41,7 +41,7 @@ Optimizer: ...@@ -41,7 +41,7 @@ Optimizer:
values: [0.1, 0.01, 0.001, 0.0001] values: [0.1, 0.01, 0.001, 0.0001]
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -39,7 +39,7 @@ Optimizer: ...@@ -39,7 +39,7 @@ Optimizer:
values: [0.1, 0.01, 0.001, 0.0001] values: [0.1, 0.01, 0.001, 0.0001]
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -39,7 +39,7 @@ Optimizer: ...@@ -39,7 +39,7 @@ Optimizer:
values: [0.1, 0.01, 0.001, 0.0001] values: [0.1, 0.01, 0.001, 0.0001]
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -39,7 +39,7 @@ Optimizer: ...@@ -39,7 +39,7 @@ Optimizer:
values: [0.1, 0.01, 0.001, 0.0001] values: [0.1, 0.01, 0.001, 0.0001]
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -39,7 +39,7 @@ Optimizer: ...@@ -39,7 +39,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
...@@ -37,7 +37,7 @@ Optimizer: ...@@ -37,7 +37,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -37,7 +37,7 @@ Optimizer: ...@@ -37,7 +37,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -37,7 +37,7 @@ Optimizer: ...@@ -37,7 +37,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
...@@ -37,7 +37,7 @@ Optimizer: ...@@ -37,7 +37,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
...@@ -37,7 +37,7 @@ Optimizer: ...@@ -37,7 +37,7 @@ Optimizer:
learning_rate: 0.045 learning_rate: 0.045
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: ./output/
device: gpu
save_interval: 1
eval_during_train: True
eval_interval: 1
epochs: 240
print_batch_step: 10
use_visualdl: False
# used for static mode and model export
image_shape: [3, 224, 224]
save_inference_dir: ./inference
# model architecture
Arch:
name: ShuffleNetV2_swish
class_num: 1000
# 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: 0.5
warmup_epoch: 5
regularizer:
name: 'L2'
coeff: 0.00004
# data loader for train and eval
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: ./dataset/ILSVRC2012/
cls_label_path: ./dataset/ILSVRC2012/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: 256
drop_last: False
shuffle: True
loader:
num_workers: 4
use_shared_memory: True
Eval:
dataset:
name: ImageNetDataset
image_root: ./dataset/ILSVRC2012/
cls_label_path: ./dataset/ILSVRC2012/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: docs/images/whl/demo.jpg
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: Topk
topk: 5
class_id_map_file: ppcls/utils/imagenet1k_label_list.txt
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
- TopkAcc:
topk: [1, 5]
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0003 coeff: 0.00003
# data loader for train and eval # data loader for train and eval
......
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
...@@ -38,7 +38,7 @@ Optimizer: ...@@ -38,7 +38,7 @@ Optimizer:
warmup_epoch: 5 warmup_epoch: 5
regularizer: regularizer:
name: 'L2' name: 'L2'
coeff: 0.0004 coeff: 0.00004
# data loader for train and eval # data loader for train and eval
......
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