CodeCamp #147 [Doc] Add Chinese version of train & test tutorial #2355
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xiexinch
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| # 教程4：使用现有模型进行训练和测试 | |||
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| MMsegmentation 支持在多种设备上训练和测试模型。如下文，具体方式分别为单GPU、分布式、族群式的训练和测试。通过本教程，你将知晓如何用MMsegmentation提供的脚本进行训练和测试。 | |||
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| MMsegmentation 支持在多种设备上训练和测试模型。如下文，具体方式分别为单GPU、分布式、族群式的训练和测试。通过本教程，你将知晓如何用MMsegmentation提供的脚本进行训练和测试。 | |
| MMsegmentation 支持在多种设备上训练和测试模型。如下文，具体方式分别为单GPU、分布式以及计算集群的训练和测试。通过本教程，你将知晓如何用 MMsegmentation 提供的脚本进行训练和测试。 |
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| - `--work-dir ${工作路径}`: 重新指定工作路径 | ||
| - `--amp`: 使用自动混合精度计算 | ||
| - `--resume`: 从工作路径中调用保存的最新的模型权重文件（checkpoint） |
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| - `--resume`: 从工作路径中调用保存的最新的模型权重文件（checkpoint） | |
| - `--resume`: 从工作路径中保存的最新检查点文件（checkpoint）恢复训练 |
| - `--work-dir ${工作路径}`: 重新指定工作路径 | ||
| - `--amp`: 使用自动混合精度计算 | ||
| - `--resume`: 从工作路径中调用保存的最新的模型权重文件（checkpoint） | ||
| - `--cfg-options ${需更新的具体配置}`: 覆盖已载入的配置中的部分设置，并且 以 xxx=yyy 格式的键值对 将被合并到config配置文件中。 |
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| - `--cfg-options ${需更新的具体配置}`: 覆盖已载入的配置中的部分设置，并且 以 xxx=yyy 格式的键值对 将被合并到config配置文件中。 | |
| - `--cfg-options ${需更覆盖的配置}`: 覆盖已载入的配置中的部分设置，并且 以 xxx=yyy 格式的键值对 将被合并到 config 配置文件中。 |
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| 下面是对于多GPU测试的可选参数: | ||
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| - `--launcher`: 用来分布式任务初始化运载器。允许选择的参数值有 `none`, `pytorch`, `slurm`, `mpi`。特别的，如果设置为none，测试将非分布式模式下进行。 |
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| - `--launcher`: 用来分布式任务初始化运载器。允许选择的参数值有 `none`, `pytorch`, `slurm`, `mpi`。特别的，如果设置为none，测试将非分布式模式下进行。 | |
| - `--launcher`: 执行器的启动方式。允许选择的参数值有 `none`, `pytorch`, `slurm`, `mpi`。特别的，如果设置为none，测试将非分布式模式下进行。 |
| - `--launcher`: 用来分布式任务初始化运载器。允许选择的参数值有 `none`, `pytorch`, `slurm`, `mpi`。特别的，如果设置为none，测试将非分布式模式下进行。 | ||
| - `--local_rank`: 分布式中进程的序号。如果没有指定，默认设置为0。 | ||
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| **注意：** 在config配置文件中 `--resume` 和 field `load_from` 的不同之处： |
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| **注意：** 在config配置文件中 `--resume` 和 field `load_from` 的不同之处： | |
| **注意：** 命令行参数 `--resume` 和在配置文件中的参数 `load_from` 的不同之处： |
| 基础用法如下： | ||
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| ```shell | ||
| [GPUS=${GPUS}] sh tools/slurm_test.sh ${划分} ${进程名} ${配置文件} ${检查点文件} [可选参数] |
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| [GPUS=${GPUS}] sh tools/slurm_test.sh ${划分} ${进程名} ${配置文件} ${检查点文件} [可选参数] | |
| [GPUS=${GPUS}] sh tools/slurm_test.sh ${分区} ${进程名} ${配置文件} ${检查点文件} [可选参数] |
| [GPUS=${GPUS}] sh tools/slurm_test.sh ${划分} ${进程名} ${配置文件} ${检查点文件} [可选参数] | ||
| ``` | ||
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| 你可以检查 [the source code](../../../tools/slurm_test.sh) 来查看全部的参数和环境变量。 |
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| 你可以检查 [the source code](../../../tools/slurm_test.sh) 来查看全部的参数和环境变量。 | |
| 你可以通过 [源码](../../../tools/slurm_test.sh) 来查看全部的参数和环境变量。 |
| GPUS=4 GPUS_PER_NODE=4 sh tools/slurm_train.sh ${PARTITION} ${JOB_NAME} config2.py ${工作路径} --cfg-options env_cfg.dist_cfg.port=29501 | ||
| ``` | ||
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| 2. 通过修改config配置文件，设置不同的通讯端口： |
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| 2. 通过修改config配置文件，设置不同的通讯端口： | |
| 2. 通过修改配置文件设置不同的通讯端口： |
| enf_cfg = dict(dist_cfg=dict(backend='nccl', port=29501)) | ||
| ``` | ||
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| 然后你可以通过 config1.py 和 config2.py 同时进行两个任务： |
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| 然后你可以通过 config1.py 和 config2.py 同时进行两个任务： | |
| 然后你可以通过 config1.py 和 config2.py 同时启动两个任务： |
| CUDA_VISIBLE_DEVICES=4,5,6,7 GPUS=4 sh tools/slurm_train.sh ${划分} ${进程名} config2.py ${工作路径} | ||
| ``` | ||
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| 3. 使用环境变量设置命令中的端口 'MASTER_PORT'： |
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| 3. 使用环境变量设置命令中的端口 'MASTER_PORT'： | |
| 3. 在命令行中通过环境变量 `MASTER_PORT` 设置端口 ： |
xiexinch
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xiexinch
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Dec 7, 2022
Co-authored-by: 谢昕辰 <xiexinch@outlook.com>
MeowZheng
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Dec 12, 2022
MeowZheng
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…orial open-mmlab#2355 * doc * modify part of content * changed parts of content * modified * Update docs/zh_cn/user_guides/4_train_test.md Co-authored-by: 谢昕辰 <xiexinch@outlook.com>
aravind-h-v
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…-mmlab#2355) correctly locate 3rd file; also correct misleading docs
wjkim81
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