[Core] Support pooling (#229)

This PR added pooling support for vllm-ascend

Tested with `bge-base-en-v1.5` by encode:
```
from vllm import LLM

# Sample prompts.
prompts = [
  "Hello, my name is",
  "The president of the United States is",
  "The capital of France is",
  "The future of AI is",
]
# Create an LLM.
model = LLM(model="./bge-base-en-v1.5", enforce_eager=True)
# Generate embedding. The output is a list of EmbeddingRequestOutputs.
outputs = model.encode(prompts)
# Print the outputs.
for output in outputs:
    print(output.outputs.embedding)  # list of 4096 floats
```

Tested by embedding:
```
from vllm import LLM, SamplingParams

llm = LLM(model="./bge-base-en-v1.5", task="embed")
(output,) = llm.embed("Hello, my name is")

embeds = output.outputs.embedding
print(f"Embeddings: {embeds!r} (size={len(embeds)})")
```

Related: https://github.com/vllm-project/vllm-ascend/issues/200

## Known issue
The accuracy is not correct since this feature rely on `enc-dec`
support. It'll be done in the following PR by @MengqingCao

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

docs/source/user_guide/suppoted_features.md

@@ -7,7 +7,7 @@
 | LoRA | ✗ | Plan in 2025 Q1 |
 | Prompt adapter | ✗ | Plan in 2025 Q1 |
 | Speculative decoding | ✗ | Plan in 2025 Q1 |
-| Pooling | ✗ | Plan in 2025 Q2 |
+| Pooling | ✅ | |
 | Enc-dec | ✗ | Plan in 2025 Q2 |
 | Multi Modality | ✅ (LLaVA/Qwen2-vl/Qwen2-audio/internVL)| Add more model support in 2025 Q1 |
 | LogProbs | ✅ ||