feat(tf2): support or reject TensorFlow-only model features and variants

[njzjz-bot]

Summary

The common schema exposes TensorFlow/common model features such as type_embedding, modifier, compress, hybrid pairwise_dprc, and model variants frozen, pairtab, and linear_ener. TF2 currently rejects or lacks registry entries for these paths.

Scope

• Inventory each feature and variant against the intended TF2 support contract.
• Implement feasible paths using shared dpmodel composition/serialization semantics.
• Add backend-aware validation for intentionally legacy-TF-only features.
• Validate type maps, component compatibility, serialization metadata, and inference behavior.
• Avoid accepting an option and silently ignoring it.

Acceptance criteria

• Each listed feature/variant is explicitly supported or rejected for TF2.
• Supported configurations round-trip through serialization and produce deterministic inference.
• Unsupported configurations fail before model construction with an actionable message.
• Hybrid/composite models validate incompatible component combinations.
• Tests and documentation distinguish legacy TensorFlow from TF2.

Refs #5757.

Coding agent: Codex
Codex version: codex-cli 0.144.4
Model: gpt-5.6-sol
Reasoning effort: xhigh