[Feature] Support RoiawarePool3d with cambricon MLU backend.

[ZhangLearning]

Motivation

The motivation of the PR is to support running RoiawarePool3d with Cambricon MLU backend.

It includes three parts:

1. Add roiaware_pool3d_mlu_kernel.mlu src code as MLU kernel.
2. Add roiaware_pool3d_mlu.cpp to support launching kernel in PyTorch.
3. Refactor test_roiaware_pool3d.py to support testing RoiawarePool3d with MLU backend.

Modification

• MLU src code
  Add MLU src code of RoiawarePool3d in directory mmcv/ops/csrc/common/mlu/roiaware_pool3d_mlu_kernel.mlu.
• PyTorch adaptation
  Adapt RoiawarePool3d for PyTorch in mmcv/ops/csrc/pytorch/mlu/roiaware_pool3d_mlu.cpp.
• Unit test
  Support test RoiawarePool3d with various backends in tests/test_ops/test_roiaware_pool3d.py.

BC-breaking (Optional)

Does the modification introduce changes that break the backward-compatibility of the downstream repositories?
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

Before PR:

• I have read and followed the workflow indicated in the CONTRIBUTING.md to create this PR.
• Pre-commit or linting tools indicated in CONTRIBUTING.md are used to fix the potential lint issues.
• Bug fixes are covered by unit tests, the case that causes the bug should be added in the unit tests.
• New functionalities are covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• The documentation has been modified accordingly, including docstring or example tutorials.

After PR:

• If the modification has potential influence on downstream or other related projects, this PR should be tested with some of those projects, like MMDet or MMCls.
• CLA has been signed and all committers have signed the CLA in this PR.

[CLAassistant]

All committers have signed the CLA.

[grimoire]

LGTM

[OpenMMLab-Assistant005]

Hi @ZhangLearning ！First of all, we want to express our gratitude for your significant PR in the MMCV project. Your contribution is highly appreciated, and we are grateful for your efforts in helping improve this open-source project during your personal time. We believe that many developers will benefit from your PR.

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