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[doc] add removed change of config.py

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jiangmingyan
2023-05-23 16:42:36 +08:00
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2 changed files with 20 additions and 19 deletions
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docs/source/en/basics/define_your_config.md
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@@ -2,7 +2,8 @@
Author: Guangyang Lu, Shenggui Li, Siqi Mai
- > ⚠️ The information on this page is outdated and will be deprecated. Please check [Booster API](../basics/booster_api.md) for more information.
> ⚠️ The information on this page is outdated and will be deprecated. Please check [Booster API](../basics/booster_api.md) for more information.
**Prerequisite:**
- [Distributed Training](../concepts/distributed_training.md)
@@ -23,7 +24,8 @@ In this tutorial, we will cover how to define your configuration file.
## Configuration Definition
In a configuration file, there are two types of variables. One serves as feature specification and the other serves
as hyper-parameters. All feature-related variables are reserved keywords. For example, if you want to use 1D tensor parallelism, you need to use the variable name `parallel` in the config file and follow a pre-defined format.
as hyper-parameters. All feature-related variables are reserved keywords. For example, if you want to use mixed precision
training, you need to use the variable name `fp16` in the config file and follow a pre-defined format.
### Feature Specification
@@ -35,13 +37,14 @@ To illustrate the use of config file, we use mixed precision training as an exam
follow the steps below.
1. create a configuration file (e.g. `config.py`, the file name can be anything)
2. define the hybrid parallelism configuration in the config file. For example, in order to use 1D tensor parallel, you can just write these lines of code below into your config file.
2. define the mixed precision configuration in the config file. For example, in order to use mixed precision training
natively provided by PyTorch, you can just write these lines of code below into your config file.
```python
parallel = dict(
data=1,
pipeline=1,
tensor=dict(size=2, mode='1d'),
from colossalai.amp import AMP_TYPE
fp16 = dict(
mode=AMP_TYPE.TORCH
)
```
@@ -54,7 +57,7 @@ the current directory.
colossalai.launch(config='./config.py', ...)
```
In this way, Colossal-AI knows what features you want to use and will inject this feature.
In this way, Colossal-AI knows what features you want to use and will inject this feature during `colossalai.initialize`.
### Global Hyper-parameters
@@ -80,4 +83,3 @@ colossalai.launch(config='./config.py', ...)
print(gpc.config.BATCH_SIZE)
```
<!-- doc-test-command: echo "define_your_config.md does not need test" -->