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Make old scaled fp8 format use the new mixed quant ops system. (#11000)

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comfyanonymous
2025-12-05 11:35:42 -08:00
committed by GitHub
parent 0ec05b1481
commit 43071e3de3
24 changed files with 278 additions and 275 deletions
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19
comfy/text_encoders/sd3_clip.py
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@@ -6,14 +6,15 @@ import torch
import os
import comfy.model_management
import logging
import comfy.utils
class T5XXLModel(sd1_clip.SDClipModel):
def __init__(self, device="cpu", layer="last", layer_idx=None, dtype=None, attention_mask=False, model_options={}):
textmodel_json_config = os.path.join(os.path.dirname(os.path.realpath(__file__)), "t5_config_xxl.json")
t5xxl_scaled_fp8 = model_options.get("t5xxl_scaled_fp8", None)
if t5xxl_scaled_fp8 is not None:
t5xxl_quantization_metadata = model_options.get("t5xxl_quantization_metadata", None)
if t5xxl_quantization_metadata is not None:
model_options = model_options.copy()
model_options["scaled_fp8"] = t5xxl_scaled_fp8
model_options["quantization_metadata"] = t5xxl_quantization_metadata
model_options = {**model_options, "model_name": "t5xxl"}
super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config=textmodel_json_config, dtype=dtype, special_tokens={"end": 1, "pad": 0}, model_class=comfy.text_encoders.t5.T5, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
@@ -25,9 +26,9 @@ def t5_xxl_detect(state_dict, prefix=""):
if t5_key in state_dict:
out["dtype_t5"] = state_dict[t5_key].dtype
scaled_fp8_key = "{}scaled_fp8".format(prefix)
if scaled_fp8_key in state_dict:
out["t5xxl_scaled_fp8"] = state_dict[scaled_fp8_key].dtype
quant = comfy.utils.detect_layer_quantization(state_dict, prefix)
if quant is not None:
out["t5_quantization_metadata"] = quant
return out
@@ -156,11 +157,11 @@ class SD3ClipModel(torch.nn.Module):
else:
return self.t5xxl.load_sd(sd)
def sd3_clip(clip_l=True, clip_g=True, t5=True, dtype_t5=None, t5xxl_scaled_fp8=None, t5_attention_mask=False):
def sd3_clip(clip_l=True, clip_g=True, t5=True, dtype_t5=None, t5_quantization_metadata=None, t5_attention_mask=False):
class SD3ClipModel_(SD3ClipModel):
def __init__(self, device="cpu", dtype=None, model_options={}):
if t5xxl_scaled_fp8 is not None and "t5xxl_scaled_fp8" not in model_options:
if t5_quantization_metadata is not None:
model_options = model_options.copy()
model_options["t5xxl_scaled_fp8"] = t5xxl_scaled_fp8
model_options["t5xxl_quantization_metadata"] = t5_quantization_metadata
super().__init__(clip_l=clip_l, clip_g=clip_g, t5=t5, dtype_t5=dtype_t5, t5_attention_mask=t5_attention_mask, device=device, dtype=dtype, model_options=model_options)
return SD3ClipModel_