提交 958727f3 编写于 作者: C cuicheng01

update resnet condigs

上级 91665f56
......@@ -30,10 +30,10 @@ Loss:
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Piecewise
name: "Piecewise"
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
......@@ -46,80 +46,80 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,80 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -30,10 +30,10 @@ Loss:
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Piecewise
name: "Piecewise"
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
......@@ -46,80 +46,80 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,80 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -30,10 +30,10 @@ Loss:
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Piecewise
name: "Piecewise"
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
......@@ -46,80 +46,80 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,80 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,80 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -30,10 +30,10 @@ Loss:
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Piecewise
name: "Piecewise"
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
......@@ -46,80 +46,80 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,80 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
......@@ -30,10 +30,10 @@ Loss:
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Piecewise
name: "Piecewise"
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
......@@ -46,80 +46,80 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Eval:
- TopkAcc:
topk: [1, 5]
# global configs
Global:
checkpoints: null
pretrained_model: null
output_dir: "./output/"
device: "gpu"
class_num: 1000
save_interval: 1
eval_during_train: True
eval_interval: 1
epochs: 120
print_batch_step: 10
use_visualdl: False
image_shape: [3, 224, 224]
infer_imgs:
# model architecture
Arch:
name: "RecModel"
Backbone:
name: "ResNet50"
Stoplayer:
name: "flatten_0"
output_dim: 2048
embedding_size: 512
Head:
name: "ArcMargin"
margin: 0.5
scale: 80
# 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: Piecewise
learning_rate: 0.1
decay_epochs: [30, 60, 90]
values: [0.1, 0.01, 0.001, 0.0001]
regularizer:
name: 'L2'
coeff: 0.0001
# data loader for train and eval
DataLoader:
Train:
# Dataset:
# Sampler:
# Loader:
batch_size: 256
num_workers: 4
file_list: "./dataset/ILSVRC2012/train_list.txt"
data_dir: "./dataset/ILSVRC2012/"
shuffle_seed: 0
transforms:
- DecodeImage:
to_rgb: True
channel_first: False
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 1./255.
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
- ToCHWImage:
Eval:
# TOTO: modify to the latest trainer
# Dataset:
# Sampler:
# Loader:
batch_size: 128
num_workers: 4
file_list: "./dataset/ILSVRC2012/val_list.txt"
data_dir: "./dataset/ILSVRC2012/"
shuffle_seed: 0
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:
Metric:
Train:
- Topk:
k: [1, 5]
Eval:
- Topk:
k: [1, 5]
......@@ -24,16 +24,17 @@ Loss:
Train:
- CELoss:
weight: 1.0
epsilon: 0.1
Eval:
- CELoss:
weight: 1.0
Optimizer:
name: Momentum
name: "Momentum"
momentum: 0.9
lr:
name: Cosine
name: "Cosine"
learning_rate: 0.1
regularizer:
name: 'L2'
......@@ -44,81 +45,81 @@ Optimizer:
DataLoader:
Train:
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- RandCropImage:
size: 224
- RandFlipImage:
flip_code: 1
- NormalizeImage:
scale: 0.00392157
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
order: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/train_list.txt"
transform_ops:
- 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: ''
batch_transform_ops:
- MixupOperator:
alpha: 0.2
sampler:
name: DistributedBatchSampler
batch_size: 64
drop_last: False
shuffle: True
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: True
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
use_shared_memory: True
Eval:
# TOTO: modify to the latest trainer
dataset:
name: ImageNetDataset
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
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: ''
name: "ImageNetDataset"
image_root: "./dataset/ILSVRC2012/"
cls_label_path: "./dataset/ILSVRC2012/val_list.txt"
transform_ops:
- 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
name: "DistributedBatchSampler"
batch_size: 64
drop_last: False
shuffle: False
loader:
num_workers: 6
use_shared_memory: True
num_workers: 6
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:
- 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
name: "Topk"
topk: 5
class_id_map_file: "ppcls/utils/imagenet1k_label_list.txt"
Metric:
Train:
- TopkAcc:
topk: [1, 5]
Eval:
Train:
Eval:
- TopkAcc:
topk: [1, 5]
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