28 lines
1.2 KiB
Python
28 lines
1.2 KiB
Python
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from typing import Any, Dict
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import torch
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import bitsandbytes as bnb
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from transformers.quantizers.quantizer_bnb_4bit import Bnb4BitHfQuantizer, get_module_from_name
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from transformers.modeling_utils import PreTrainedModel
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# CogVLM stores inv_freq in the state dictionary but it is not in models._parameters so it cannot be quantized
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# was patched in transformers for other models here: https://github.com/huggingface/transformers/pull/28837/files but cog is not part of transformers
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def _patched_check_quantized_param(
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self, model: "PreTrainedModel", param_value: "torch.Tensor", param_name: str, state_dict: Dict[str, Any]
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) -> bool:
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# if "inv_freq" in param_name: # detect failure case
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# print("check_quantized_param", param_name)
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module, tensor_name = get_module_from_name(model, param_name)
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if ("inv_freq" == tensor_name): # the fix
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return False
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if isinstance(module._parameters[tensor_name], bnb.nn.Params4bit): # will throw key error for inv_freq
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return True
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elif isinstance(module, bnb.nn.Linear4bit) and tensor_name == "bias":
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return True
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else:
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return False
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def patch_cog():
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Bnb4BitHfQuantizer.check_quantized_param = _patched_check_quantized_param
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