fix(dashboard): Fix SGLang benchmark workflow and integrate into dashboard

[zhuyuhua-v]

Description

This PR introduces a dedicated GitHub Actions workflow for benchmarking ATOM-accelerated SGLang (atom-sglang-benchmark.yaml) and officially integrates its performance results into the benchmark dashboard.

To avoid code duplication, it also refactors the existing vLLM Python scripts into generic plugin scripts shared by both frameworks.

SGLang Benchmark Details

• Trigger Method: Manual only (workflow_dispatch).
• Target Model: DeepSeek-R1-0528 (FP8 TP8).
• Hardware / Runner: Executed on atom-mi355-8gpu-oot-benchmark (MI355 8-GPU machines).
• Workflow: Handles custom SGLang Docker image building, model loading, performance profiling, and result artifact generation.

Dashboard Integration

• Added a dedicated hue offset (-30) for ATOM-SGLang in index.html to visually distinguish its charts from ATOM and ATOM-vLLM.
• Fixed a missing deployment step in the workflow to ensure atom_logo_mini.png is correctly copied to the gh-pages branch.

Script Unification (SGLang & vLLM)

• Renamed the existing oot_benchmark_*.py scripts to plugin_benchmark_*.py to make them framework-agnostic.
• Updated both atom-sglang-benchmark.yaml and atom-vllm-oot-benchmark.yaml to reuse these unified scripts by passing specific arguments (e.g., --title and --default-backend).

Docker Release Workflow Fix

• Fixed mutual exclusivity bug in docker-release.yaml: Previously, if a user checked both only_release_oot and only_release_sglang, the workflow would fail to build either image. The logic has been updated so that if both are checked, both the OOT and SGLang images will be built and released (while still correctly skipping the native image test/push). The UI descriptions for these inputs have been updated to reflect this behavior.