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[doc] update booster tutorials (#3718)
* [booster] update booster tutorials#3717 * [booster] update booster tutorials#3717, fix * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, update setup doc * [booster] update booster tutorials#3717, rename colossalai booster.md * [booster] update booster tutorials#3717, rename colossalai booster.md * [booster] update booster tutorials#3717, rename colossalai booster.md * [booster] update booster tutorials#3717, fix * [booster] update booster tutorials#3717, fix * [booster] update tutorials#3717, update booster api doc * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, modify file * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3717, fix reference link * [booster] update tutorials#3713 * [booster] update tutorials#3713, modify file
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@@ -74,7 +74,7 @@ import colossalai
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args = colossalai.get_default_parser().parse_args()
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# launch distributed environment
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colossalai.launch(config=<CONFIG>,
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colossalai.launch(config=args.config,
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rank=args.rank,
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world_size=args.world_size,
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host=args.host,
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@@ -93,12 +93,21 @@ PyTorch自带的启动器需要在每个节点上都启动命令才能启动多
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首先,我们需要在代码里指定我们的启动方式。由于这个启动器是PyTorch启动器的封装,那么我们自然而然应该使用`colossalai.launch_from_torch`。
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分布式环境所需的参数,如 rank, world size, host 和 port 都是由 PyTorch 启动器设置的,可以直接从环境变量中读取。
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config.py
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```python
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BATCH_SIZE = 512
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LEARNING_RATE = 3e-3
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WEIGHT_DECAY = 0.3
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NUM_EPOCHS = 2
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```
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train.py
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```python
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import colossalai
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colossalai.launch_from_torch(
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config=<CONFIG>,
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config="./config.py",
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)
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...
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```
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接下来,我们可以轻松地在终端使用`colossalai run`来启动训练。下面的命令可以在当前机器上启动一个4卡的训练任务。
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