95 lines
3.4 KiB
Markdown
95 lines
3.4 KiB
Markdown
# Configuration
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---
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## Introduction
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This document introduces the configuration(filed in `config/*.yaml`) of PaddleClas.
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* 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 parameter `checkpoints` will be updated or added using the value `./ckp_path/ppcls`.
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### Basic
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| name | detail | default value | optional value |
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|:---:|:---:|:---:|:---:|
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| mode | mode | "train" | ["train"," valid"] |
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| checkpoints | checkpoint model path for resuming training process | "" | Str |
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| last_epoch | last epoch for the training，used with checkpoints | -1 | int |
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| pretrained_model | pretrained model path | "" | Str |
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| load_static_weights | whether the pretrained model is saved in static mode | False | bool |
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| model_save_dir | model stored path | "" | Str |
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| classes_num | class number | 1000 | int |
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| total_images | total images | 1281167 | int |
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| save_interval | save interval | 1 | int |
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| validate | whether to validate when training | TRUE | bool |
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| valid_interval | valid interval | 1 | int |
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| epochs | epoch | | int |
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| topk | K value | 5 | int |
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| image_shape | image size | [3，224，224] | list, shape: (3,) |
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| use_mix | whether to use mixup | False | ['True', 'False'] |
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| ls_epsilon | label_smoothing epsilon value| 0 | float |
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| use_distillation | whether to use SSLD distillation training | False | bool |
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## ARCHITECTURE
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| name | detail | default value | optional value |
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|:---:|:---:|:---:|:---:|
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| name | model name | "ResNet50_vd" | one of 23 architectures |
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| params | model parameters | {} | extra dictionary for the model structure, parameters such as `padding_type` in EfficientNet can be set here |
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### LEARNING_RATE
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| name | detail | default value |Optional value |
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|:---:|:---:|:---:|:---:|
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| function | decay type | "Linear" | ["Linear", "Cosine", <br> "Piecewise", "CosineWarmup"] |
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| params.lr | initial learning rate | 0.1 | float |
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| params.decay_epochs | milestone in piecewisedecay | | list |
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| params.gamma | gamma in piecewisedecay | 0.1 | float |
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| params.warmup_epoch | warmup epoch | 5 | int |
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| parmas.steps | decay steps in lineardecay | 100 | int |
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| params.end_lr | end lr in lineardecay | 0 | float |
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### OPTIMIZER
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| name | detail | default value | optional value |
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|:---:|:---:|:---:|:---:|
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| function | optimizer name | "Momentum" | ["Momentum", "RmsProp"] |
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| params.momentum | momentum value | 0.9 | float |
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| regularizer.function | regularizer method name | "L2" | ["L1", "L2"] |
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| regularizer.factor | regularizer factor | 0.0001 | float |
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### reader
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| name | detail |
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|:---:|:---:|
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| batch_size | batch size |
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| num_workers | worker number |
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| file_list | train list path |
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| data_dir | train dataset path |
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| shuffle_seed | seed |
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processing
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| function name | attribute name | detail |
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|:---:|:---:|:---:|
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| DecodeImage | to_rgb | decode to RGB |
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| | to_np | to numpy |
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| | channel_first | Channel first |
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| RandCropImage | size | random crop |
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| RandFlipImage | | random flip |
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| NormalizeImage | scale | normalize image |
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| | mean | mean |
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| | std | std |
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| | order | order |
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| ToCHWImage | | to CHW |
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| CropImage | size | crop size |
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| ResizeImage | resize_short | resize according to short size |
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mix preprocessing
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| name| detail|
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|:---:|:---:|
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| MixupOperator.alpha | alpha value in mixup|
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