[doc] add tutorial for booster checkpoint (#3785)

* [doc] add checkpoint related docstr for booster

* [doc] add en checkpoint doc

* [doc] add zh checkpoint doc

* [doc] add booster checkpoint doc in sidebar

* [doc] add cuation about ckpt for plugins

* [doc] add doctest placeholder

* [doc] add doctest placeholder

* [doc] add doctest placeholder
This commit is contained in:
Hongxin Liu
2023-05-19 18:05:08 +08:00
committed by GitHub
parent ad2cf58f50
commit 60e6a154bc
6 changed files with 161 additions and 0 deletions

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@@ -29,6 +29,7 @@
"basics/launch_colossalai",
"basics/booster_api",
"basics/booster_plugins",
"basics/booster_checkpoint",
"basics/define_your_config",
"basics/initialize_features",
"basics/engine_trainer",

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# Booster Checkpoint
Author: [Hongxin Liu](https://github.com/ver217)
**Prerequisite:**
- [Booster API](./booster_api.md)
## Introduction
We've introduced the [Booster API](./booster_api.md) in the previous tutorial. In this tutorial, we will introduce how to save and load checkpoints using booster.
## Model Checkpoint
{{ autodoc:colossalai.booster.Booster.save_model }}
Model must be boosted by `colossalai.booster.Booster` before saving. `checkpoint` is the path to saved checkpoint. It can be a file, if `shard=False`. Otherwise, it should be a directory. If `shard=True`, the checkpoint will be saved in a sharded way. This is useful when the checkpoint is too large to be saved in a single file. Our sharded checkpoint format is compatible with [huggingface/transformers](https://github.com/huggingface/transformers).
{{ autodoc:colossalai.booster.Booster.load_model }}
Model must be boosted by `colossalai.booster.Booster` before loading. It will detect the checkpoint format automatically, and load in corresponding way.
## Optimizer Checkpoint
> ⚠ Saving optimizer checkpoint in a sharded way is not supported yet.
{{ autodoc:colossalai.booster.Booster.save_optimizer }}
Optimizer must be boosted by `colossalai.booster.Booster` before saving.
{{ autodoc:colossalai.booster.Booster.load_optimizer }}
Optimizer must be boosted by `colossalai.booster.Booster` before loading.
## LR Scheduler Checkpoint
{{ autodoc:colossalai.booster.Booster.save_lr_scheduler }}
LR scheduler must be boosted by `colossalai.booster.Booster` before saving. `checkpoint` is the local path to checkpoint file.
{{ autodoc:colossalai.booster.Booster.load_lr_scheduler }}
LR scheduler must be boosted by `colossalai.booster.Booster` before loading. `checkpoint` is the local path to checkpoint file.
## Checkpoint design
More details about checkpoint design can be found in our discussion [A Unified Checkpoint System Design](https://github.com/hpcaitech/ColossalAI/discussions/3339).
<!-- doc-test-command: echo -->

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@@ -43,12 +43,16 @@ We've tested compatibility on some famous models, following models may not be su
Compatibility problems will be fixed in the future.
> ⚠ This plugin can only load optimizer checkpoint saved by itself with the same number of processes now. This will be fixed in the future.
### Gemini Plugin
This plugin implements Zero-3 with chunk-based and heterogeneous memory management. It can train large models without much loss in speed. It also does not support local gradient accumulation. More details can be found in [Gemini Doc](../features/zero_with_chunk.md).
{{ autodoc:colossalai.booster.plugin.GeminiPlugin }}
> ⚠ This plugin can only load optimizer checkpoint saved by itself with the same number of processes now. This will be fixed in the future.
### Torch DDP Plugin
More details can be found in [Pytorch Docs](https://pytorch.org/docs/main/generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel).
@@ -62,3 +66,5 @@ More details can be found in [Pytorch Docs](https://pytorch.org/docs/main/genera
More details can be found in [Pytorch Docs](https://pytorch.org/docs/main/fsdp.html).
{{ autodoc:colossalai.booster.plugin.TorchFSDPPlugin }}
<!-- doc-test-command: echo -->

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# Booster Checkpoint
作者: [Hongxin Liu](https://github.com/ver217)
**前置教程:**
- [Booster API](./booster_api.md)
## 引言
我们在之前的教程中介绍了 [Booster API](./booster_api.md)。在本教程中,我们将介绍如何使用 booster 保存和加载 checkpoint。
## 模型 Checkpoint
{{ autodoc:colossalai.booster.Booster.save_model }}
模型在保存前必须被 `colossalai.booster.Booster` 加速。 `checkpoint` 是要保存的 checkpoint 的路径。 如果 `shard=False`,它就是文件。 否则, 它就是文件夹。如果 `shard=True`checkpoint 将以分片方式保存。当 checkpoint 太大而无法保存在单个文件中时,这很有用。我们的分片 checkpoint 格式与 [huggingface/transformers](https://github.com/huggingface/transformers) 兼容。
{{ autodoc:colossalai.booster.Booster.load_model }}
模型在加载前必须被 `colossalai.booster.Booster` 加速。它会自动检测 checkpoint 格式,并以相应的方式加载。
## 优化器 Checkpoint
> ⚠ 尚不支持以分片方式保存优化器 Checkpoint。
{{ autodoc:colossalai.booster.Booster.save_optimizer }}
优化器在保存前必须被 `colossalai.booster.Booster` 加速。
{{ autodoc:colossalai.booster.Booster.load_optimizer }}
优化器在加载前必须被 `colossalai.booster.Booster` 加速。
## 学习率调度器 Checkpoint
{{ autodoc:colossalai.booster.Booster.save_lr_scheduler }}
学习率调度器在保存前必须被 `colossalai.booster.Booster` 加速。 `checkpoint` 是 checkpoint 文件的本地路径.
{{ autodoc:colossalai.booster.Booster.load_lr_scheduler }}
学习率调度器在加载前必须被 `colossalai.booster.Booster` 加速。 `checkpoint` 是 checkpoint 文件的本地路径.
## Checkpoint 设计
有关 Checkpoint 设计的更多详细信息,请参见我们的讨论 [A Unified Checkpoint System Design](https://github.com/hpcaitech/ColossalAI/discussions/3339).
<!-- doc-test-command: echo -->

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@@ -43,12 +43,16 @@ Zero-2 不支持局部梯度累积。如果您坚持使用,虽然可以积累
兼容性问题将在未来修复。
> ⚠ 该插件现在只能加载自己保存的且具有相同进程数的优化器 Checkpoint。这将在未来得到解决。
### Gemini 插件
这个插件实现了基于Chunk内存管理和异构内存管理的 Zero-3。它可以训练大型模型而不会损失太多速度。它也不支持局部梯度累积。更多详细信息请参阅 [Gemini 文档](../features/zero_with_chunk.md).
{{ autodoc:colossalai.booster.plugin.GeminiPlugin }}
> ⚠ 该插件现在只能加载自己保存的且具有相同进程数的优化器 Checkpoint。这将在未来得到解决。
### Torch DDP 插件
更多详细信息,请参阅 [Pytorch 文档](https://pytorch.org/docs/main/generated/torch.nn.parallel.DistributedDataParallel.html#torch.nn.parallel.DistributedDataParallel).
@@ -62,3 +66,5 @@ Zero-2 不支持局部梯度累积。如果您坚持使用,虽然可以积累
更多详细信息,请参阅 [Pytorch 文档](https://pytorch.org/docs/main/fsdp.html).
{{ autodoc:colossalai.booster.plugin.TorchFSDPPlugin }}
<!-- doc-test-command: echo -->