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54 lines
2.2 KiB
54 lines
2.2 KiB
# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ..core_model_loading import ConversionOps
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from ..utils import is_torch_available
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if is_torch_available():
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import torch
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class QuarkDeserialize(ConversionOps):
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def __init__(self, hf_quantizer):
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self.hf_quantizer = hf_quantizer
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def convert(
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self,
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input_dict: torch.Tensor,
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model: torch.nn.Module | None = None,
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missing_keys: list[str] | None = None,
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full_layer_name: str | None = None,
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**kwargs,
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) -> dict[str, torch.Tensor]:
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# target_key should be in the form of weight_scale, bias_scale, input_scale, output_scale, weight_zero_point, bias_zero_point, input_zero_point, output_zero_point
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target_key, value = tuple(input_dict.items())[0]
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value = value[0] if isinstance(value, list) else value
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# this will get the param name : weight, input, bias or output
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param = target_key.split("_", 1)[0]
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# quant_state should be in the form of scale, or zero_point
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quant_state = target_key.split("_", 1)[-1]
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# here we change the name for example from the form of :
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# model.layers.0.mlp.down_proj.weight_scale to model.layers.0.mlp.down_proj.weight_quantizer.scale to fit within
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# the QParamsLinear module of quark
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sub_module_state = full_layer_name.rsplit(".", 1)[0] + "." + param + "_quantizer" + "." + quant_state
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# since quark module was expecting keys in the form of model.layers.0.mlp.down_proj.weight_scale
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# we need to remove it from the missing_keys list
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missing_keys.discard(full_layer_name)
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return {sub_module_state: value}
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