[refactor] replace scattered business kwargs with typed request objects and explicit stage boundaries (#7024)

### What this PR does / why we need it?
Refactor `vllm_ascend/ops/fused_moe` to replace scattered MoE business
`**kwargs` with typed request objects and explicit stage boundaries.

- Prepare, dispatch, MLP, and quant stages now have clearer ownership.
- Main MoE path no longer depends on business `kwargs.get(...)` lookups.
- Comm and dispatcher interfaces are request-only on the main path.
- UTs can assert stage-level fields directly instead of inferring
behavior indirectly.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
CI passed.

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>

vllm_ascend/quantization/__init__.py

@@ -16,24 +16,30 @@
 #
 """Ascend quantization module.
 
-This module provides quantization support for Ascend NPU.
-
-Supported quantization tools:
-- ModelSlim: Use AscendModelSlimConfig
-- LLM-Compressor (compressed_tensors): Use AscendCompressedTensorsConfig
-
-Public API:
-- Config classes: AscendModelSlimConfig, AscendCompressedTensorsConfig
-- For scheme implementations, import from vllm_ascend.quantization.methods
+This module intentionally avoids eager imports so that importing lightweight
+submodules (for example ``quant_type``) does not trigger heavy registration
+paths and circular imports during startup.
 """
 
-# LLM-Compressor (compressed_tensors) quantization config
-from .compressed_tensors_config import AscendCompressedTensorsConfig
+from typing import TYPE_CHECKING, Any
 
-# ModelSlim quantization config
-from .modelslim_config import AscendModelSlimConfig
+if TYPE_CHECKING:
+    from .compressed_tensors_config import AscendCompressedTensorsConfig
+    from .modelslim_config import AscendModelSlimConfig
 
 __all__ = [
     "AscendModelSlimConfig",
     "AscendCompressedTensorsConfig",
 ]
+
+
+def __getattr__(name: str) -> Any:
+    if name == "AscendModelSlimConfig":
+        from .modelslim_config import AscendModelSlimConfig
+
+        return AscendModelSlimConfig
+    if name == "AscendCompressedTensorsConfig":
+        from .compressed_tensors_config import AscendCompressedTensorsConfig
+
+        return AscendCompressedTensorsConfig
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")