class_docstr: Args:
      sequence_dim:
          Single representation channel dimension
      pairwise_dim:
          Pair representation channel dimension
      ipa_dim:
          IPA hidden channel dimension
      resnet_dim:
          Angle resnet (Alg. 23 lines 11-14) hidden channel dimension
      num_heads_ipa:
          Number of IPA heads
      num_qk_points:
          Number of query/key points to generate during IPA
      num_v_points:
          Number of value points to generate during IPA
      dropout_rate:
          Dropout rate used throughout the layer
      num_blocks:
          Number of structure module blocks
      num_transition_layers:
          Number of layers in the single representation transition (Alg. 23 lines 8-9)
      num_resnet_blocks:
          Number of blocks in the angle resnet
      num_angles:
          Number of angles to generate in the angle resnet
      trans_scale_factor:
          Scale of single representation transition hidden dimension
      epsilon:
          Small number used in angle resnet normalization
      inf:
          Large number used for attention masking
class_docstr_tok: ["Args",":","sequence_dim",":","Single","representation","channel","dimension","pairwise_dim",":","Pair","representation","channel","dimension","ipa_dim",":","IPA","hidden","channel","dimension","resnet_dim",":","Angle","resnet","(","Alg",".","23","lines","11-14",")","hidden","channel","dimension","num_heads_ipa",":","Number","of","IPA","heads","num_qk_points",":","Number","of","query\/key","points","to","generate","during","IPA","num_v_points",":","Number","of","value","points","to","generate","during","IPA","dropout_rate",":","Dropout","rate","used","throughout","the","layer","num_blocks",":","Number","of","structure","module","blocks","num_transition_layers",":","Number","of","layers","in","the","single","representation","transition","(","Alg",".","23","lines","8-9",")","num_resnet_blocks",":","Number","of","blocks","in","the","angle","resnet","num_angles",":","Number","of","angles","to","generate","in","the","angle","resnet","trans_scale_factor",":","Scale","of","single","representation","transition","hidden","dimension","epsilon",":","Small","number","used","in","angle","resnet","normalization","inf",":","Large","number","used","for","attention","masking"]
code: def to_dict(self):
      return asdict(self)
  
file_path: transformers/src/transformers/models/esm/configuration_esm.py
imports: from dataclasses import asdict, dataclass
  from typing import Optional
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 for calling the StructureModuleConfig obj's underlying member method code with example usage: obj.to_dict() and returns: asdict