[Feature]: FP8 Quantization Support for DiT (#1034)

Signed-off-by: lishunyang <lishunyang12@163.com>
Signed-off-by: SYLAR <125541396+lishunyang12@users.noreply.github.com>

vllm_omni/diffusion/quantization/__init__.py

@@ -0,0 +1,114 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""Quantization support for diffusion models.
+
+This module provides a unified interface for quantizing diffusion transformers
+using various methods (FP8, etc.). It wraps vLLM's quantization infrastructure
+while allowing diffusion-model-specific defaults and optimizations.
+
+Example usage:
+    from vllm_omni.diffusion.quantization import (
+        get_diffusion_quant_config,
+        get_vllm_quant_config_for_layers,
+    )
+
+    # Create FP8 config for diffusion model
+    diff_config = get_diffusion_quant_config("fp8")
+
+    # Get vLLM config to pass to linear layers
+    vllm_config = get_vllm_quant_config_for_layers(diff_config)
+
+    # Use in model initialization
+    linear_layer = QKVParallelLinear(..., quant_config=vllm_config)
+"""
+
+from typing import TYPE_CHECKING
+
+from vllm.logger import init_logger
+
+from .base import DiffusionQuantizationConfig
+from .fp8 import DiffusionFp8Config
+
+if TYPE_CHECKING:
+    from vllm.model_executor.layers.quantization.base_config import (
+        QuantizationConfig,
+    )
+
+logger = init_logger(__name__)
+
+# Registry of supported quantization methods
+# To add a new method, create a new config class and register it here
+_QUANT_CONFIG_REGISTRY: dict[str, type[DiffusionQuantizationConfig]] = {
+    "fp8": DiffusionFp8Config,
+}
+
+SUPPORTED_QUANTIZATION_METHODS = list(_QUANT_CONFIG_REGISTRY.keys())
+
+
+def get_diffusion_quant_config(
+    quantization: str | None,
+    **kwargs,
+) -> DiffusionQuantizationConfig | None:
+    """Factory function to create quantization config for diffusion models.
+
+    Args:
+        quantization: Quantization method name ("fp8", etc.) or None to disable
+        **kwargs: Method-specific parameters passed to the config constructor
+
+    Returns:
+        DiffusionQuantizationConfig instance or None if quantization is disabled
+
+    Raises:
+        ValueError: If the quantization method is not supported
+
+    Example:
+        # Default FP8 with dynamic activation scaling
+        config = get_diffusion_quant_config("fp8")
+
+        # FP8 with custom parameters
+        config = get_diffusion_quant_config(
+            "fp8",
+            activation_scheme="static",
+            ignored_layers=["proj_out"],
+        )
+    """
+    if quantization is None or quantization.lower() == "none":
+        return None
+
+    quantization = quantization.lower()
+    if quantization not in _QUANT_CONFIG_REGISTRY:
+        raise ValueError(
+            f"Unknown quantization method: {quantization!r}. Supported methods: {SUPPORTED_QUANTIZATION_METHODS}"
+        )
+
+    config_cls = _QUANT_CONFIG_REGISTRY[quantization]
+    logger.info("Creating diffusion quantization config: %s", quantization)
+    return config_cls(**kwargs)
+
+
+def get_vllm_quant_config_for_layers(
+    diffusion_quant_config: DiffusionQuantizationConfig | None,
+) -> "QuantizationConfig | None":
+    """Get the vLLM QuantizationConfig to pass to linear layers.
+
+    This extracts the underlying vLLM config from a DiffusionQuantizationConfig,
+    which can then be passed to vLLM linear layers (QKVParallelLinear, etc.).
+
+    Args:
+        diffusion_quant_config: The diffusion quantization config, or None
+
+    Returns:
+        vLLM QuantizationConfig instance, or None if input is None
+    """
+    if diffusion_quant_config is None:
+        return None
+    return diffusion_quant_config.get_vllm_quant_config()
+
+
+__all__ = [
+    "DiffusionQuantizationConfig",
+    "DiffusionFp8Config",
+    "get_diffusion_quant_config",
+    "get_vllm_quant_config_for_layers",
+    "SUPPORTED_QUANTIZATION_METHODS",
+]