[Core][Diffusion] Add a typed pre-D2H video media contract (#6615)

Signed-off-by: NancyFyong <NancyFyong@users.noreply.github.com>
Signed-off-by: Samit <285365963@qq.com>
Co-authored-by: NancyFyong <NancyFyong@users.noreply.github.com>
Co-authored-by: Samit <285365963@qq.com>

docs/user_guide/diffusion/device_side_video_postprocess.md

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+# Device-side video postprocessing
+
+vLLM-Omni can convert decoded WAN2.2 video from normalized floating-point
+`[B, C, T, H, W]` tensors to contiguous `uint8` `[B, T, H, W, C]` frames before
+the worker-to-engine device-to-host transfer. This reduces the transported video
+payload by four times when the original IPC path widens bfloat16 to float32.
+
+The optimization is disabled by default. Enable it with a structured diffusion
+configuration:
+
+```python
+from vllm_omni import Omni
+
+engine = Omni(
+    model="Wan-AI/Wan2.2-TI2V-5B-Diffusers",
+    video_output_transport={"enable_device_postprocess": True},
+)
+```
+
+For the server CLI, pass the same object as JSON:
+
+```bash
+vllm serve Wan-AI/Wan2.2-TI2V-5B-Diffusers --omni \
+  --video-output-transport '{"enable_device_postprocess": true}'
+```
+
+For a deploy configuration, place it on the diffusion stage:
+
+```yaml
+stages:
+  - stage_id: 0
+    video_output_transport:
+      enable_device_postprocess: true
+```
+
+## Runtime contract
+
+WAN2.2 emits decoded video through the typed `DiffusionOutput.media` field. The
+model runner validates and splits the batch into request-local tensors before
+preparing each video for transport. The worker then performs the D2H copy and
+shared-memory IPC using the prepared representation. The engine uses the generic
+media finalizer instead of a model-specific postprocessor.
+
+The runtime leaves the video in normalized floating-point form when:
+
+- `enable_device_postprocess` is false;
+- the requested output type is not `np`; or
+- frame interpolation still requires the floating-point tensor.
+
+These are policy fallbacks, not malformed-contract errors. If the device cannot
+allocate the temporary conversion buffer, the runner logs a warning and prepares
+the request-local float representation instead. Invalid tensor layout, encoding,
+value range, lifecycle state, and non-memory runtime failures still fail before
+IPC.
+
+## Precision
+
+Device preparation converts to float32 before denormalization and quantization.
+For bfloat16 WAN output this is more precise than the historical host path,
+which denormalizes in bfloat16. Relative to that path, values may differ by at
+most one level out of 255. Float32 inputs remain byte-identical after
+quantization.
+
+## Scope
+
+WAN2.2 is the reference migration for the first contract version. Other video
+pipelines continue using their existing output paths until they can declare the
+same typed media contract without bypassing model-specific float consumers such
+as safety checks or audio/video packaging.
+
+See [RFC #6541](https://github.com/vllm-project/vllm-omni/issues/6541) for the
+contract, lifecycle, batching rules, and migration plan.