Support asym w4a8_int (#15308)

* support asym w4a8_int

* Simplify

* Fixes

comfy/ops.py

@@ -1211,6 +1211,26 @@ def _load_quantized_module(module, super_load, state_dict, prefix, local_metadat
                 "quant_group_size": 64,
                 "linear_dtype": layer_conf.get("linear_dtype", params_conf.get("linear_dtype", "int4")),
             }
+        elif module.quant_format == "asym_w4a8_int8":
+            # int4 weight (packed int8 [N,K/2]) + fp8 per-group scale (weight_s_rel),
+            # fp32 per-channel scale (weight_s_channel) + optional Lloyd-Max codebook.
+            scale = pop_scale("weight_s_rel")
+            if scale is None:
+                raise ValueError(f"Missing W4A8 group scale (weight_s_rel) for layer {layer_name}")
+            if scale.dtype == torch.uint8:
+                scale = scale.view(torch.float8_e4m3fn)
+            params_conf = layer_conf.get("params", {})
+            if not isinstance(params_conf, dict):
+                params_conf = {}
+            scales = {
+                "scale": scale,
+                "s_channel": pop_scale("weight_s_channel"),
+                "codebook": pop_scale("weight_codebook"),
+                "group_size": int(layer_conf.get("group_size", params_conf.get("group_size", 16))),
+                "convrot_groupsize": int(
+                    layer_conf.get("convrot_groupsize", params_conf.get("convrot_groupsize", 256))
+                ),
+            }
         else:
             raise ValueError(f"Unsupported quantization format: {module.quant_format}")
 
@@ -1262,6 +1282,9 @@ def _quantized_weight_state_dict(module, sd, prefix, extra_quant_conf=None, extr
             linear_dtype = getattr(params, "linear_dtype", "int4")
             if linear_dtype != "int4":
                 quant_conf["linear_dtype"] = linear_dtype
+        elif module.quant_format == "asym_w4a8_int8":
+            quant_conf["group_size"] = getattr(params, "group_size", 16)
+            quant_conf["convrot_groupsize"] = getattr(params, "convrot_groupsize", 256)
         if extra_quant_conf:
             quant_conf.update(extra_quant_conf)
         sd[f"{prefix}comfy_quant"] = torch.tensor(list(json.dumps(quant_conf).encode("utf-8")), dtype=torch.uint8)

comfy/quant_ops.py

@@ -28,6 +28,7 @@ try:
         TensorCoreNVFP4Layout as _CKNvfp4Layout,
         TensorCoreConvRotW4A4Layout as _CKTensorCoreConvRotW4A4Layout,
         TensorWiseINT8Layout as _CKTensorWiseINT8Layout,
+        AsymW4A8Int8Layout as _CKAsymW4A8Int8Layout,
         register_layout_op,
         register_layout_class,
         get_layout_class,
@@ -83,6 +84,9 @@ except ImportError as e:
     class _CKTensorCoreConvRotW4A4Layout:
         pass
 
+    class _CKAsymW4A8Int8Layout:
+        pass
+
     def register_layout_class(name, cls):
         pass
 
@@ -212,7 +216,7 @@ class TensorCoreFP8E5M2Layout(_TensorCoreFP8LayoutBase):
 TensorCoreFP8Layout = TensorCoreFP8E4M3Layout
 TensorWiseINT8Layout = _CKTensorWiseINT8Layout
 TensorCoreConvRotW4A4Layout = _CKTensorCoreConvRotW4A4Layout
-
+AsymW4A8Int8Layout = _CKAsymW4A8Int8Layout
 
 # ==============================================================================
 # Registry
@@ -226,6 +230,7 @@ register_layout_class("TensorWiseINT8Layout", _CKTensorWiseINT8Layout)
 register_layout_class("TensorCoreConvRotW4A4Layout", _CKTensorCoreConvRotW4A4Layout)
 if _CK_MXFP8_AVAILABLE:
     register_layout_class("TensorCoreMXFP8Layout", TensorCoreMXFP8Layout)
+register_layout_class("AsymW4A8Int8Layout", _CKAsymW4A8Int8Layout)
 
 QUANT_ALGOS = {
     "float8_e4m3fn": {
@@ -268,6 +273,13 @@ QUANT_ALGOS["convrot_w4a4"] = {
     "quantize_input": False,
 }
 
+QUANT_ALGOS["asym_w4a8_int8"] = {
+    "storage_t": torch.int8,
+    "parameters": {"weight_scale"},
+    "comfy_tensor_layout": "AsymW4A8Int8Layout",
+    "quantize_input": False,
+}
+
 
 # ==============================================================================
 # Re-exports for backward compatibility
@@ -282,6 +294,7 @@ __all__ = [
     "TensorCoreNVFP4Layout",
     "TensorCoreConvRotW4A4Layout",
     "TensorWiseINT8Layout",
+    "AsymW4A8Int8Layout",
     "QUANT_ALGOS",
     "register_layout_op",
 ]