Integrate Automated QDQ placement tool - Part 2

[willg-nv]

What does this PR do?

Type of change: new feature

Overview: This PR integrate automated Q/DQ placement tool to ModelOpt. This PR is 2/4 parts of the cahnges.

Part 1: #701
Part 2: #702
Part 3: #703
Part 4: #704

This PR contains the following changes:

1. Implement RegionPattern to represent the topology structure of Regions. InsertionPoints are also defined on RegionPattern. Regions with same pattern are optimized at the same time
2. Implement RegionSearch class to divide ONNX graph into small regions
3. RegionSearch python file also provides an entry point to print out the region structures.
4. Unit tests for new classse.

Usage

python -m modelopt.onnx.quantization.autotune.region_search --model model.onnx --verbose

Example output:

    ├─ Region 212 (Level 0, Type: COMPOSITE)
    │  ├─ Direct nodes: 0
    │  ├─ Total nodes (recursive): 9
    │  ├─ Children: 1
    │  ├─ Inputs: 3 tensors
    │  │    - xxx
    │  │    - xxx
    │  │    - xxx
    │  └─ Outputs: 1 tensors
    │       - xxx
    │
    │  Child regions:
    │
      ├─ Region 209 (Level 2, Type: LEAF) 
      │  ├─ Direct nodes: 9
      │  ├─ Total nodes (recursive): 9
      │  ├─ Children: 0
      │  ├─ Inputs: 11 tensors
      │  │    - xxx

Testing

Implemented unit tests for new classes. All unit tests could get pass locally.

Before your PR is "Ready for review"

• Make sure you read and follow Contributor guidelines and your commits are signed.
• Is this change backward compatible?: Yes
• Did you write any new necessary tests?: Yes
• Did you add or update any necessary documentation?: No, document change will be in part 4.
• Did you update Changelog?: No. Change log will be included in part 4.

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