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Allow tensor-strategy for FP8-only compressed-tensor ckpts
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+5
-3
@@ -552,22 +552,24 @@ class ModelBase:
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elif quant_format == "float-quantized" or quant_format == "int-quantized" or quant_format == "naive-quantized":
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block_size = weight_config.get("block_structure", None)
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strategy = weight_config.get("strategy")
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assert strategy == "channel" or strategy == "block"
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assert weight_config.get("group_size") is None # didn't find a model using this yet
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is_fp8 = (
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quant_format == "float-quantized"
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and weight_config.get("type") == "float"
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and weight_config.get("num_bits") == 8
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)
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assert strategy in ("channel", "block") or (is_fp8 and strategy == "tensor")
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assert weight_config.get("group_size") is None # didn't find a model using this yet
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for name in self.model_tensors.keys():
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if name.endswith(".weight_scale"):
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weight_name = name.removesuffix("_scale")
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w = self.model_tensors[weight_name]
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s = self.model_tensors[name]
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self.model_tensors[weight_name] = lambda w=w, s=s: dequant_simple(w(), s(), block_size)
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self.model_tensors[weight_name] = lambda w=w, s=s, bs=block_size: dequant_simple(w(), s(), bs)
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tensors_to_remove.append(name)
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if self._fp8_as_q8 and is_fp8:
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self._fp8_dequantized.add(weight_name)
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if is_fp8 and name.endswith((".input_scale", ".activation_scale", "_activation_scale", ".k_scale", ".v_scale")):
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tensors_to_remove.append(name)
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elif quant_format == "pack-quantized":
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assert weight_config.get("strategy") == "group"
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assert weight_config.get("type", "int") == "int"
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