如何使用vscode的launch.json来debug调试

1、创建一个launch.json文件

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选择Python Debugger，再选择Python文件，创建处理如下
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默认有下面五个参数

    "name": "Python Debugger: Current File","type": "debugpy","request": "launch","program": "${file}","console": "integratedTerminal"

修改“program”路径：使用“workspaceFolder”
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开启调试：

调试结果：

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一些复杂的调试可能会如下：

{"version": "0.2.0","configurations": [{"name": "Python Debugger: Experiment Runner",//"type": "debugpy","type": "python","request": "launch",//"program": "${file}","program": "${workspaceFolder}/driving/configs/_base_/models/B_efficientnetlite_H_roadclsdecoder.py","console": "integratedTerminal",// new"cwd":"${workspaceFolder}",// 如果是false的话就会进到别的子程序里面，为了调试的直观，// 设置true比较好, true就是调试的范围都是你写的代码"justMyCode":true,  // 环境"env":{"CUDA_VISILBE_DEVICES":"0",// 开启断言assert"TORCH_USE_CUDA_DSA":"ON"},// 训练参数细节"args": ["--task_name", "CoLA", "--do_train", "true","--do_eval", "true","--data_dir", "glue_data/CoLA","--vocab_file", "uncased_L-2_H-128_A-2/vocab.txt","--bert_config_file", "uncased_L-2_H-128_A-2/bert_config.json", "--init_checkpoint", "uncased_L-2_H-128_A-2/bert_model.ckpt", "--max_seq_length", "128" ,"--train_batch_size", "32","--learning_rate", "2e-5" ,"--num_train_epochs", "3.0" ,"--output_dir", "tmp/CoLA_output"]      }]
}