Enable 4bit bnb prequant MOE

[py-andy-c]

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[github-actions]

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[gemini-code-assist]

Code Review

This pull request aims to enable 4bit bnb prequant MOE. The changes involve modifying the validation logic for MoE quantization and updating a model implementation to selectively quantize the MoE router gate.

My review identified a critical issue in the validation logic that could lead to a runtime crash, and a high-severity design issue in the model implementation that impacts maintainability and correctness. I've provided suggestions to fix both issues.

[gemini-code-assist]

This change incorrectly allows 8-bit MoE quantization when pre_quant is false. The BitsAndBytesMoEMethod for 8-bit weights is not implemented and raises a NotImplementedError (see vllm/model_executor/layers/quantization/bitsandbytes.py). This will lead to a runtime crash for a configuration that this check now allows.

To enable 4-bit pre-quantized MoE while correctly disallowing 8-bit MoE, you should only check for self.load_8bit. The original check for self.pre_quant was what blocked 4-bit pre-quant, and removing it is correct, but the self.load_8bit check should remain as it was to prevent using the unimplemented 8-bit MoE path.

if self.load_8bit:
    raise ValueError(
        "BitsAndBytes 8bit quantization with FusedMoE is not "
        "supported yet.")

[gemini-code-assist]

This implementation for deciding whether to quantize the MoE gate has a couple of issues:

1. Hardcoded Logic: It specifically checks for BitsAndBytesConfig, making it difficult to extend to other quantization methods that might also support gate quantization. This can lead to silent failures where a new quantization method is expected to quantize the gate but doesn't. A more extensible approach would be to have a method on the QuantizationConfig itself to indicate this capability.
2. Incorrect Type Hint: The type hint for quant_config in _maybe_ignore_quant_config is QuantizationConfig, but it can be None at the call site.
3. Clarity: The function name _maybe_ignore_quant_config is a bit ambiguous.

self.gate = ReplicatedLinear(config.hidden_size,
                                     config.num_experts,
                                     bias=False,
                                     quant_config=self._get_gate_quant_config(quant_config),
                                     prefix=f"{prefix}.gate")

    def _get_gate_quant_config(
        self, quant_config: Optional[QuantizationConfig]
    ) -> Optional[QuantizationConfig]:
        # The gate is only quantized for BitsAndBytes for now.
        if isinstance(quant_config, BitsAndBytesConfig):
            return quant_config
        return None

[jeejeelee]

LGTM,thank you for your contribution

[simon-mo]

Please add a PR description. Thanks!