fix the problem that the static graph of a model fails to trace any tensor constants within.

Motivation

During QAT training, the model being trained contains some tensor constants, such as reg_max=torch.arange(16). These constants are also stored within the model. However, the following logic fails to include these tensors, resulting in a mismatch between the static graph and the actual model during subsequent training.

Modification

elif is added to support tensor objects, as shown in line 147 and 148

BC-breaking (Optional)

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

No

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:

• [❌] 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 tests 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.