forked from mindspore-Ecosystem/mindspore
70 lines
1.6 KiB
YAML
70 lines
1.6 KiB
YAML
# Builtin Configurations(DO NOT CHANGE THESE CONFIGURATIONS unless 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: "Ascend"
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need_modelarts_dataset_unzip: True
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modelarts_dataset_unzip_name: "ImageNet"
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# ==============================================================================
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# default options
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image_size: "224,224"
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num_classes: 1000
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lr: 0.1
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lr_scheduler: "cosine_annealing"
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lr_epochs: "30,60,90,120"
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lr_gamma: 0.1
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eta_min: 0
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T_max: 150
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max_epoch: 150
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warmup_epochs: 5
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weight_decay: 0.0001
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momentum: 0.9
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is_dynamic_loss_scale: 0
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loss_scale: 1024
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label_smooth: 1
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label_smooth_factor: 0.1
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ckpt_interval: 1
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ckpt_save_max: 10
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ckpt_path: "outputs/"
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is_save_on_master: 1
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data_dir: ""
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pretrained: ""
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is_distributed: 1
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per_batch_size: 64
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log_path: "outputs/"
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# export options
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export_batch_size: 1
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ckpt_file: ""
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file_name: "cspdarknet53"
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file_format: "MINDIR"
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width: 224
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height: 224
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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 the input data."
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output_path: "The location of the output file."
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device_target: 'Target device type'
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graph_ckpt: "graph ckpt or feed ckpt"
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# export options
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export_batch_size: "batch size for export"
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ckpt_file: "cspdarknet53 ckpt file"
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file_name: "output air name."
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file_format: "file format, choices in ['AIR', 'ONNX', 'MINDIR']"
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width: "input width"
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height: "input height" |