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[doc] Fix typo under colossalai and doc(#3618)

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* Fixed several spelling errors under colossalai

* Fix the spelling error in colossalai and docs directory

* Cautious Changed the spelling error under the example folder

* Update runtime_preparation_pass.py

revert autograft to autograd

* Update search_chunk.py

utile to until

* Update check_installation.py

change misteach to mismatch in line 91

* Update 1D_tensor_parallel.md

revert to perceptron

* Update 2D_tensor_parallel.md

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* Update 2p5D_tensor_parallel.md

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* Update 3D_tensor_parallel.md

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* Update README.md

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* Update reorder_graph.py

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* Update p2p.py

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* Update initialize.py

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* Update routers.py

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* Update routers.py

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* Update README.md

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This commit is contained in:
digger-yu
2023-04-26 11:38:43 +08:00
committed by GitHub
parent e1b0a78afa
commit b9a8dff7e5
72 changed files with 158 additions and 158 deletions
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docs/source/en/Colossal-Auto/get_started/run_demo.md
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@@ -4,7 +4,7 @@ Colossal-Auto simplifies the process of deploying large-scale machine learning m
### 1. Basic usage
Colossal-Auto can be used to find a hybrid SPMD parallel strategy includes data, tensor(i.e., 1D, 2D, sequencial) for each operation. You can follow the [GPT example](https://github.com/hpcaitech/ColossalAI/tree/main/examples/language/gpt/experiments/auto_parallel).
Colossal-Auto can be used to find a hybrid SPMD parallel strategy includes data, tensor(i.e., 1D, 2D, sequential) for each operation. You can follow the [GPT example](https://github.com/hpcaitech/ColossalAI/tree/main/examples/language/gpt/experiments/auto_parallel).
Detailed instructions can be found in its `README.md`.
### 2. Integration with activation checkpoint