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#Configuration
Introduction
This document introduces the configuration(filed in config/*.yaml
) of PaddleClas.
- Note: Some parameters do not appear in the yaml file (because they are not used for this file). During training or validation, you can use the command
-o
to update or add the specified parameters. For the example-o checkpoints=./ckp_path/ppcls
, it means that the parametercheckpoints
will be updated or added using the value./ckp_path/ppcls
.
Basic
name | detail | default value | optional value |
---|---|---|---|
mode | mode | "train" | ["train"," valid"] |
checkpoints | checkpoint model path for resuming training process | "" | Str |
last_epoch | last epoch for the training,used with checkpoints | -1 | int |
pretrained_model | pretrained model path | "" | Str |
load_static_weights | whether the pretrained model is saved in static mode | False | bool |
model_save_dir | model stored path | "" | Str |
classes_num | class number | 1000 | int |
total_images | total images | 1281167 | int |
save_interval | save interval | 1 | int |
validate | whether to validate when training | TRUE | bool |
valid_interval | valid interval | 1 | int |
epochs | epoch | int | |
topk | K value | 5 | int |
image_shape | image size | [3,224,224] | list, shape: (3,) |
use_mix | whether to use mixup | False | ['True', 'False'] |
ls_epsilon | label_smoothing epsilon value | 0 | float |
use_distillation | whether to use SSLD distillation training | False | bool |
ARCHITECTURE
name | detail | default value | optional value |
---|---|---|---|
name | model name | "ResNet50_vd" | one of 23 architectures |
params | model parameters | {} | extra dictionary for the model structure, parameters such as padding_type in EfficientNet can be set here |
LEARNING_RATE
name | detail | default value | Optional value |
---|---|---|---|
function | decay type | "Linear" | ["Linear", "Cosine", "Piecewise", "CosineWarmup"] |
params.lr | initial learning rate | 0.1 | float |
params.decay_epochs | milestone in piecewisedecay | list | |
params.gamma | gamma in piecewisedecay | 0.1 | float |
params.warmup_epoch | warmup epoch | 5 | int |
parmas.steps | decay steps in lineardecay | 100 | int |
params.end_lr | end lr in lineardecay | 0 | float |
OPTIMIZER
name | detail | default value | optional value |
---|---|---|---|
function | optimizer name | "Momentum" | ["Momentum", "RmsProp"] |
params.momentum | momentum value | 0.9 | float |
regularizer.function | regularizer method name | "L2" | ["L1", "L2"] |
regularizer.factor | regularizer factor | 0.0001 | float |
reader
name | detail |
---|---|
batch_size | batch size |
num_workers | worker number |
file_list | train list path |
data_dir | train dataset path |
shuffle_seed | seed |
processing
function name | attribute name | detail |
---|---|---|
DecodeImage | to_rgb | decode to RGB |
to_np | to numpy | |
channel_first | Channel first | |
RandCropImage | size | random crop |
RandFlipImage | random flip | |
NormalizeImage | scale | normalize image |
mean | mean | |
std | std | |
order | order | |
ToCHWImage | to CHW | |
CropImage | size | crop size |
ResizeImage | resize_short | resize according to short size |
mix preprocessing
name | detail |
---|---|
MixupOperator.alpha | alpha value in mixup |