[Feature] Add colossalai strategy

[HAOCHENYE]

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Motivation

1. Add colossalai strategy.
2. Move DeepSpeedXXX from mmengine/optim and mmengine/model/ to mmengine/_strategy/deepspeed, and delete useless directory

Note: The optimizer state (learning rate) cannot be resumed correctly now. Maybe it will be fixed by ColossalAI in the future.

Environment

• PyTorch: 2.0.0
• deepspeed: 0.9.3+d755b9d6
• CUDA: 11.7
• GPU: 8 * A100, 80G

Validation

• resume
• load_from

Experiment

MMPreTrain

• vit-large-p16_8xb128-coslr-50e_in1k.py

  ColossalAI GeminiDDP+ bf16: 20.6G per GPU, accuracy: 85.6040

   strategy = dict(
       type='ColossalAIStrategy',
   )
  
   optim_wrapper = dict(
       optimizer=dict(
       type='HybridAdam'),
   )

Training logs

08/14 21:44:53 - mmengine - INFO - Epoch(train)  [1][  20/1252]  base_lr: 4.0000e-03 lr: 9.4379e-09  eta: 11:58:19  time: 0.3768  data_time: 0.0017  memory: 20673  loss: 6.9064
08/14 21:45:00 - mmengine - INFO - Epoch(train)  [1][  40/1252]  base_lr: 4.0000e-03 lr: 1.9056e-08  eta: 9:15:57  time: 0.3779  data_time: 0.0016  memory: 20672  loss: 6.9071
08/14 21:45:08 - mmengine - INFO - Epoch(train)  [1][  60/1252]  base_lr: 4.0000e-03 lr: 2.8673e-08  eta: 8:20:58  time: 0.3760  data_time: 0.0015  memory: 20672  loss: 6.9077
08/14 21:45:16 - mmengine - INFO - Epoch(train)  [1][  80/1252]  base_lr: 4.0000e-03 lr: 3.8291e-08  eta: 7:58:42  time: 0.4151  data_time: 0.0015  memory: 20671  loss: 6.9034
08/14 21:45:25 - mmengine - INFO - Epoch(train)  [1][ 100/1252]  base_lr: 4.0000e-03 lr: 4.7909e-08  eta: 7:57:35  time: 0.3771  data_time: 0.0016  memory: 20671  loss: 6.8877
08/14 21:45:33 - mmengine - INFO - Epoch(train)  [1][ 120/1252]  base_lr: 4.0000e-03 lr: 5.7527e-08  eta: 7:43:16  time: 0.3771  data_time: 0.0015  memory: 20671  loss: 6.8040
08/14 21:45:40 - mmengine - INFO - Epoch(train)  [1][ 140/1252]  base_lr: 4.0000e-03 lr: 6.7144e-08  eta: 7:33:16  time: 0.3781  data_time: 0.0016  memory: 20671  loss: 6.7578
08/14 21:45:48 - mmengine - INFO - Epoch(train)  [1][ 160/1252]  base_lr: 4.0000e-03 lr: 7.6762e-08  eta: 7:25:37  time: 0.3769  data_time: 0.0017  memory: 20671  loss: 6.6219
08/14 21:45:55 - mmengine - INFO - Epoch(train)  [1][ 180/1252]  base_lr: 4.0000e-03 lr: 8.6380e-08  eta: 7:19:39  time: 0.3779  data_time: 0.0016  memory: 20671  loss: 6.4336
08/14 21:46:03 - mmengine - INFO - Epoch(train)  [1][ 200/1252]  base_lr: 4.0000e-03 lr: 9.5998e-08  eta: 7:14:52  time: 0.3765  data_time: 0.0016  memory: 20672  loss: 6.4805
08/14 21:46:12 - mmengine - INFO - Epoch(train)  [1][ 220/1252]  base_lr: 4.0000e-03 lr: 1.0562e-07  eta: 7:18:40  time: 0.5063  data_time: 0.0015  memory: 20671  loss: 6.3190
08/14 21:46:20 - mmengine - INFO - Epoch(train)  [1][ 240/1252]  base_lr: 4.0000e-03 lr: 1.1523e-07  eta: 7:14:53  time: 0.3806  data_time: 0.0016  memory: 20671  loss: 6.2094
08/14 21:46:27 - mmengine - INFO - Epoch(train)  [1][ 260/1252]  base_lr: 4.0000e-03 lr: 1.2485e-07  eta: 7:11:31  time: 0.3773  data_time: 0.0016  memory: 20671  loss: 5.9526
08/14 21:46:35 - mmengine - INFO - Epoch(train)  [1][ 280/1252]  base_lr: 4.0000e-03 lr: 1.3447e-07  eta: 7:08:37  time: 0.3778  data_time: 0.0016  memory: 20671  loss: 6.0162

Modification

Please briefly describe what modification is made in this PR.

BC-breaking (Optional)

Does the modification introduce changes that break the backward-compatibility of the downstream repos?
If so, please describe how it breaks the compatibility and how the downstream projects should modify their code to keep compatibility with this PR.

Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.

Checklist

1. Pre-commit or other linting tools are used to fix the potential lint issues.
2. The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDet or MMCls.
4. The documentation has been modified accordingly, like docstring or example tutorials.