class_docstr: If specified, it tries to select samples such that their sum of inputs is >= min_sum and <= max_sum. Only compatible with the WEIGHTS strategy. 
class_docstr_tok: ["If","specified",",","it","tries","to","select","samples","such","that","their","sum","of","inputs","is",">","=","min_sum","and","<","=","max_sum",".","Only","compatible","with","the","WEIGHTS","strategy","."]
docstr: Returns the dictionary representation of the model
docstr_tok: ["Returns","the","dictionary","representation","of","the","model"]
code: def to_dict(self, by_alias: bool = False):
      """Returns the dictionary representation of the model"""
      _dict = self.dict(
          by_alias=by_alias, exclude={}, exclude_none=True
      )
      return _dict
  
file_path: lightly/lightly/openapi_generated/swagger_client/models/selection_config_v3_entry_strategy_all_of_target_range.py
imports: from __future__ import annotations
  import pprint
  import re
  import json
  from typing import Optional, Union
  from pydantic import Extra, BaseModel, Field, confloat, conint
label_desc: Use image node_id 4 for calling the SelectionConfigV3EntryStrategyAllOfTargetRange obj's underlying member method code with example usage: obj.to_dict(by_alias) and returns: _dict