[example] add train resnet/vit with booster example (#3694)

* [example] add train vit with booster example

* [example] update readme

* [example] add train resnet with booster example

* [example] enable ci

* [example] enable ci

* [example] add requirements

* [hotfix] fix analyzer init

* [example] update requirements

examples/tutorial/new_api/cifar_vit/README.md

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+# Train ViT on CIFAR-10 from scratch
+
+## 🚀 Quick Start
+
+This example provides a training script, which provides an example of training ViT on CIFAR10 dataset from scratch.
+
+- Training Arguments
+  - `-p`, `--plugin`: Plugin to use. Choices: `torch_ddp`, `torch_ddp_fp16`, `low_level_zero`. Defaults to `torch_ddp`.
+  - `-r`, `--resume`: Resume from checkpoint file path. Defaults to `-1`, which means not resuming.
+  - `-c`, `--checkpoint`: The folder to save checkpoints. Defaults to `./checkpoint`.
+  - `-i`, `--interval`: Epoch interval to save checkpoints. Defaults to `5`. If set to `0`, no checkpoint will be saved.
+  - `--target_acc`: Target accuracy. Raise exception if not reached. Defaults to `None`.
+
+### Install requirements
+
+```bash
+pip install -r requirements.txt
+```
+
+### Train
+
+```bash
+# train with torch DDP with fp32
+colossalai run --nproc_per_node 4 train.py -c ./ckpt-fp32
+
+# train with torch DDP with mixed precision training
+colossalai run --nproc_per_node 4 train.py -c ./ckpt-fp16 -p torch_ddp_fp16
+
+# train with low level zero
+colossalai run --nproc_per_node 4 train.py -c ./ckpt-low_level_zero -p low_level_zero
+```
+
+Expected accuracy performance will be:
+
+| Model     | Single-GPU Baseline FP32 | Booster DDP with FP32 | Booster DDP with FP16 | Booster Low Level Zero |
+| --------- | ------------------------ | --------------------- | --------------------- | ---------------------- |
+| ViT       | 83.00%                   | 84.03%                | 84.00%                | 84.43%                 |