Plumb dbias request in isolation into the common backend selector

Describe the bug

cuDNN FE can model bias input separately from dBias, but TE does not yet plumb whether dBias is requested into the common backend selector. Until that distinction is available, the D=256 SM10x gate requires no bias.

Steps/Code to reproduce bug

Please list minimal steps or code snippet for us to be able to reproduce the bug.

A helpful guide on on how to craft a minimal bug report http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports.

Expected behavior

A clear and concise description of what you expected to happen.

Environment overview (please complete the following information)

• Environment location: [Bare-metal, Docker, Cloud(specify cloud provider - AWS, Azure, GCP, Collab)]
• Method of Transformer Engine install: [pip install or from source]. Please specify exact commands you used to install.
• If method of install is [Docker], provide docker pull & docker run commands used

Environment details

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:

• OS version
• PyTorch version
• Python version
• Transformer Engine version
• CUDA version
• CUDNN version

Device details

• GPU model

Additional context

Add any other context about the problem here.

No files or tests are identified. Start by tracing the Transformer Engine path into the common backend selector and the D=256 SM10x gate, then determine where the dBias-request state is available; done means the selector distinguishes dBias requests while preserving the stated gate behavior.