forked from mindspore-Ecosystem/mindspore
58 lines
1.6 KiB
YAML
58 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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enable_profiling: False
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modelarts_dataset_unzip_name: ''
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# ==============================================================================
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#train-eval-export related
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dataset_name : cifar10
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ckpt_save_dir: checkpoints
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pre_trained: False
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device_id: 0
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num_classes: 10
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lr_init: 0.1
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batch_size: 32
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epoch_size: 120
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momentum: 0.9
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weight_decay: 0.0001
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image_height: 227
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image_width: 227
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train_data_dir: './dataset/imagenet_original/train/'
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val_data_dir: './dataset/imagenet_original/val/'
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keep_checkpoint_max: 1
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checkpoint_path: './scripts/train_parallel4/ckpt_4/train_tinydarknet_imagenet-300_1251.ckpt'
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onnx_filename: 'tinydarknet.onnx'
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air_filename: 'tinydarknet.air'
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# optimizer and lr related
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lr_scheduler: 'exponential'
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lr_epochs: [70, 140, 210, 280]
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lr_gamma: 0.1
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eta_min: 0.0
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T_max: 150
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warmup_epochs: 0
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# loss related
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is_dynamic_loss_scale: False
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loss_scale: 1024
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label_smooth_factor: 0.1
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use_label_smooth: True
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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: "Running platform, choose from Ascend, GPU or CPU, and default is Ascend."
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enable_profiling: 'Whether enable profiling while training, default: False'
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