forked from mindspore-Ecosystem/mindspore
74 lines
1.8 KiB
YAML
74 lines
1.8 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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data_url: ""
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train_url: ""
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checkpoint_url: ""
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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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# ==============================================================================
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dataset_path: "/cache/data"
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ckpt_path: '/cache/data/'
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checkpoint: './inceptionv3/inceptionv3-rank3_1-247_1251.ckpt'
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ckpt_file: '/cache/data/inceptionv3/inceptionv3-rank3_1-247_1251.ckpt'
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resume: ''
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is_distributed: False
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device_id: 0
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platform: 'CPU'
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file_name: 'inceptionv3'
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file_format: 'AIR'
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width: 299
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height: 299
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modelarts_dataset_unzip_name: 'ImageNet_Original'
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need_modelarts_dataset_unzip: True
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ckpt_save_dir: './ckpt/'
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result_path: '' # "result file path"
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label_file": '' # "label file"
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# Training options
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random_seed: 1
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work_nums: 8
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decay_method: 'cosine'
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loss_scale: 1024
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batch_size: 128
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epoch_size: 120
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num_classes: 10
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ds_type: 'cifar10'
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ds_sink_mode: False
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smooth_factor: 0.1
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aux_factor: 0.2
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lr_init: 0.00004
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lr_max: 0.1
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lr_end: 0.000004
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warmup_epochs: 1
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weight_decay: 0.00004
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momentum: 0.9
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opt_eps: 1.0
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keep_checkpoint_max: 10
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is_save_on_master: 0
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dropout_keep_prob: 0.8
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has_bias: False
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amp_level: 'O0'
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---
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# Config description for each option
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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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data_path: 'Dataset path for local'
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output_path: 'Training output path for local'
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device_target: 'Target device type'
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enable_profiling: 'Whether enable profiling while training, default: False'
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file_name: 'inceptionv3 output air name.'
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file_format: 'file format'
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---
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device_target: ['Ascend', 'GPU', 'CPU']
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file_format: ['AIR', 'ONNX', 'MINDIR']
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