[NPUW] Support prefill-chunk for text-embedding model

[mengweiguo]

Details:

Qwen3-text-embedding is a transformer-based casual model and it's not the traditional LLM and is not directly adapted to NPUW.
The benefits of prefill-chunk for Qwen3-text-embedding:

• support long context
• Performance improvement

Changes:

• Added KVCache nodes in model and updated shapes for related nodes.
• Added positon_ids input node since it's hardcoded in original model.
• Created a separate model to handle the post-processing.
• Cached the output of prefill since mean post-processing needs entire output data.

Notes:

1. Though kvcache model is not needed at all, it's still there. As I don't want to add many if-else. And the penalty is the compilation time increasing.
2. Padding is only supported in the mean post-processing mode for now, which makes thing simple. I can add the padding support on left in following PRs if required.
3. GenAI PR: [NPU] Support NPUW for text-embedding models openvino.genai#3088
4. The tests has been verified to work with both NPUW and GenAI updates.

Tickets:

• CVS-177453