forked from mindspore-Ecosystem/mindspore
85 lines
2.6 KiB
YAML
85 lines
2.6 KiB
YAML
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# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unlesee you know exactly what you are doing)
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enable_modelarts: False
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# url for modelarts
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data_url: ""
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train_url: ""
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checkpoint_url: ""
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# path for local
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data_path: "/cache/data"
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output_path: "/cache/train"
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load_path: "/cache/checkpoint_path"
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device_target: "GPU"
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enable_profiling: False
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checkpoint_path: "./checkpoint/"
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checkpoint_file: "./checkpoint/.ckpt"
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# ======================================================================================
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# common options
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crop_size: 512
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image_mean: [103.53, 116.28, 123.675]
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image_std: [57.375, 57.120, 58.395]
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ignore_label: 255
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num_classes: 21
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model: "FCN8s"
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# ======================================================================================
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# Training options
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train_batch_size: 8
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min_scale: 0.5
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max_scale: 2.0
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data_file: "./vocaug_local_mindrecords/vocaug_local_mindrecords.mindrecords" # change to your own path of train data
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# optimizer
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train_epochs: 500
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base_lr: 0.005
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loss_scale: 1024
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# model
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ckpt_vgg16: "./vgg16_predtrain.ckpt" # change to your own path of backbone pretrain
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ckpt_pre_trained: ""
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save_steps: 330
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keep_checkpoint_max: 5
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ckpt_dir: "./ckpt"
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# ======================================================================================
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# Eval options
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eval_batch_size: 16
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data_root: "./VOCdevkit/VOC2012" # change to your own path of val data
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data_lst: "./VOCdevkit/VOC2012/ImageSets/Segmentation/val.txt" # change to your own path of val data list
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scales: [1.0]
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flip: False
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freeze_bn: False
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ckpt_file: "./FCN8s_1-500_220.ckpt" # change to your own path of evaluate model
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---
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# Help description for each configuration
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enable_modelarts: "Whether training on modelarts default: False"
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data_url: "Url for modelarts"
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train_url: "Url for modelarts"
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data_path: "The location of input data"
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output_pah: "The location of the output file"
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device_target: "device id of GPU or Ascend. (Default: None)"
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enable_profiling: "Whether enable profiling while training default: False"
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crop_size: "crop_size"
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image_mean: "image_mean"
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image_std: "image std"
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ignore_label: "ignore label"
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num_classes: "number of classes"
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model: "select model"
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data_file: "path of train data"
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train_batch_size: "train_batch_size"
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min_scale: "min scales of train"
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max_scale: "max scales of train"
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train_epochs: "train epoch"
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base_lr: "base lr"
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loss_scale: "loss scales"
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ckpt_vgg16: "backbone pretrain"
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ckpt_pre_trained: "model pretrain"
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data_root: "root path of val data"
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eval_batch_size: "eval batch size"
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data_lst: "list of val data"
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scales: "scales of evaluation"
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flip: "freeze bn"
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ckpt_file: "model to evaluate"
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