Make old scaled fp8 format use the new mixed quant ops system. (#11000)
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@@ -40,10 +40,10 @@ class HunyuanImageTokenizer(QwenImageTokenizer):
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class Qwen25_7BVLIModel(sd1_clip.SDClipModel):
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def __init__(self, device="cpu", layer="hidden", layer_idx=-3, dtype=None, attention_mask=True, model_options={}):
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llama_scaled_fp8 = model_options.get("qwen_scaled_fp8", None)
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if llama_scaled_fp8 is not None:
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llama_quantization_metadata = model_options.get("llama_quantization_metadata", None)
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if llama_quantization_metadata is not None:
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model_options = model_options.copy()
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model_options["scaled_fp8"] = llama_scaled_fp8
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model_options["quantization_metadata"] = llama_quantization_metadata
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super().__init__(device=device, layer=layer, layer_idx=layer_idx, textmodel_json_config={}, dtype=dtype, special_tokens={"pad": 151643}, layer_norm_hidden_state=False, model_class=comfy.text_encoders.llama.Qwen25_7BVLI, enable_attention_masks=attention_mask, return_attention_masks=attention_mask, model_options=model_options)
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@@ -91,12 +91,12 @@ class HunyuanImageTEModel(QwenImageTEModel):
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else:
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return super().load_sd(sd)
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def te(byt5=True, dtype_llama=None, llama_scaled_fp8=None):
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def te(byt5=True, dtype_llama=None, llama_quantization_metadata=None):
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class QwenImageTEModel_(HunyuanImageTEModel):
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def __init__(self, device="cpu", dtype=None, model_options={}):
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if llama_scaled_fp8 is not None and "scaled_fp8" not in model_options:
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if llama_quantization_metadata is not None:
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model_options = model_options.copy()
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model_options["qwen_scaled_fp8"] = llama_scaled_fp8
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model_options["llama_quantization_metadata"] = llama_quantization_metadata
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if dtype_llama is not None:
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dtype = dtype_llama
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super().__init__(byt5=byt5, device=device, dtype=dtype, model_options=model_options)
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