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https://github.com/RYDE-WORK/lnp_ml.git
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35 lines
1.4 KiB
Python
35 lines
1.4 KiB
Python
from lnp_ml.modeling.encoders.rdkit_encoder import CachedRDKitEncoder
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from lnp_ml.modeling.encoders.mpnn_encoder import CachedMPNNEncoder
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# ============ LLM / 分子编码器（可选） ============
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# 这些 encoder 在使用 use_llm=True 时才会被实例化。
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# 为避免在未安装对应依赖（如 torch_geometric、selfies）时导入即报错，
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# 采用惰性导入：实际类在 build_llm_encoder() 内按需 import。
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__all__ = [
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"CachedRDKitEncoder",
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"CachedMPNNEncoder",
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# LLM encoders（按需惰性导入，见 models.build_llm_encoder）
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"LLMEncoder",
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"MolT5Encoder",
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"MoleculeSTMEncoder",
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"SELFIESTEDEncoder",
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]
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def __getattr__(name):
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"""惰性导入 LLM encoder 类，避免未装可选依赖时 import 失败。"""
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if name == "LLMEncoder":
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from lnp_ml.modeling.encoders.llm_encoder import LLMEncoder
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return LLMEncoder
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if name == "MolT5Encoder":
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from lnp_ml.modeling.encoders.molt5_encoder import MolT5Encoder
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return MolT5Encoder
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if name == "MoleculeSTMEncoder":
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from lnp_ml.modeling.encoders.moleculestm_encoder import MoleculeSTMEncoder
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return MoleculeSTMEncoder
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if name == "SELFIESTEDEncoder":
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from lnp_ml.modeling.encoders.selfiested_encoder import SELFIESTEDEncoder
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return SELFIESTEDEncoder
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raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
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