Motivation

I've read the #628 issue and implemented a proposal for MultiTaskClsHead in order to mix multiple classification head to create a multi task classification tool.

Modification

Please briefly describe what modification is made in this PR.

• Created a unit test for MultiTaskClsHead
• the implementation of MultiTaskClsHead

NB : Current implementation is made to be generic and the different head can output different shapes (it will give the ability to mix head from mmcls with heads from mmpose or other projects). The drawback of this is that the output of the simple_test method cannot be a tensor, i choose to deactivate the post_process=False mode for the simple_test method. Any suggestion would be welcome

BC-breaking (Optional)

No

Use cases (Optional)

The basic use case here it to classify multiple classes using the same neural network.
In order to make it work, it is needed to implement a compatible dataset.

I have made the following :

• Starting from the ImageNet dataset
• in load_annotations, info['gt_label'] is a tuple containing one gt_label per head
• evaluate method need to be reworked

Checklist

Before PR:

• Pre-commit or other linting tools are used to fix the potential lint issues.
• Bug fixes are fully covered by unit tests, the case that causes the bug should be added in the unit tests.
• The modification is covered by complete unit tests. If not, please add more unit test to ensure the correctness.
• The documentation has been modified accordingly, like docstring or example tutorials.

After PR:

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