[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>

vllm_ascend/platform.py

@@ -105,7 +105,7 @@ class NPUPlatform(Platform):
     def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
         parallel_config = vllm_config.parallel_config
         if parallel_config.worker_cls == "auto":
-            parallel_config.worker_cls = "vllm_ascend.worker.NPUWorker"
+            parallel_config.worker_cls = "vllm_ascend.worker.worker.NPUWorker"
         cache_config = vllm_config.cache_config
         if cache_config and cache_config.block_size is None:
             # TODO: Set block_size to 128 will lead unexpected accuracy issue in mla case.  Please set block_size to 128 back once the problem is fixed.