forked from huawei/mindspore2022
71 lines
1.9 KiB
YAML
71 lines
1.9 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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run_distribute: False
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enable_profiling: False
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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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checkpoint_path: './checkpoint/'
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checkpoint_file_path: ''
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# ==============================================================================
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# Training options
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image_size: [224,224]
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num_classes: 1000
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batch_size: 1
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lr: 0.4
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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: 1
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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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per_batch_size: 128
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ckpt_interval: 5
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ckpt_save_max: 5
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is_save_on_master: 1
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rank_save_ckpt_flag: 0
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outputs_dir: ""
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log_path: './output_log'
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# Export options
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device_id: 0
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width: 224
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height: 224
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file_name: "resnext101"
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file_format: "MINDIR"
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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: 'Dataset url for obs'
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train_url: 'Training output url for obs'
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checkpoint_url: 'The location of checkpoint for obs'
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data_path: 'Dataset path for local'
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output_path: 'Training output path for local'
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load_path: 'The location of checkpoint for obs'
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device_target: 'Target device type, available: [Ascend, GPU, CPU]'
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enable_profiling: 'Whether enable profiling while training, default: False'
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num_classes: 'Class for dataset'
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batch_size: "Batch size for training and evaluation"
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epoch_size: "Total training epochs."
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keep_checkpoint_max: "keep the last keep_checkpoint_max checkpoint"
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checkpoint_path: "The location of the checkpoint file."
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checkpoint_file_path: "The location of the checkpoint file."
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