class_docstr: TagChangeData
class_docstr_tok: ["TagChangeData"]
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={"additional_properties"},
          exclude_none=True,
      )
      # override the default output from pydantic by calling `to_dict()` of initial
      if self.initial:
          _dict[
              "initial" if by_alias else "initial"
          ] = self.initial.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of rename
      if self.rename:
          _dict[
              "rename" if by_alias else "rename"
          ] = self.rename.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of upsize
      if self.upsize:
          _dict[
              "upsize" if by_alias else "upsize"
          ] = self.upsize.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of arithmetics
      if self.arithmetics:
          _dict[
              "arithmetics" if by_alias else "arithmetics"
          ] = self.arithmetics.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of metadata
      if self.metadata:
          _dict[
              "metadata" if by_alias else "metadata"
          ] = self.metadata.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of samples
      if self.samples:
          _dict[
              "samples" if by_alias else "samples"
          ] = self.samples.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of scatterplot
      if self.scatterplot:
          _dict[
              "scatterplot" if by_alias else "scatterplot"
          ] = self.scatterplot.to_dict(by_alias=by_alias)
      # override the default output from pydantic by calling `to_dict()` of sampler
      if self.sampler:
          _dict[
              "sampler" if by_alias else "sampler"
          ] = self.sampler.to_dict(by_alias=by_alias)
      # puts key-value pairs in additional_properties in the top level
      if self.additional_properties is not None:
          for _key, _value in self.additional_properties.items():
              _dict[_key] = _value
  
      return _dict
  
imports: from __future__ import annotations
  import pprint
  import re
  import json
  from typing import Optional
  from pydantic import Extra, BaseModel
  from lightly.openapi_generated.swagger_client.models.tag_change_data_arithmetics import TagChangeDataArithmetics
  from lightly.openapi_generated.swagger_client.models.tag_change_data_initial import TagChangeDataInitial
  from lightly.openapi_generated.swagger_client.models.tag_change_data_metadata import TagChangeDataMetadata
  from lightly.openapi_generated.swagger_client.models.tag_change_data_rename import TagChangeDataRename
  from lightly.openapi_generated.swagger_client.models.tag_change_data_sampler import TagChangeDataSampler
  from lightly.openapi_generated.swagger_client.models.tag_change_data_samples import TagChangeDataSamples
  from lightly.openapi_generated.swagger_client.models.tag_change_data_scatterplot import TagChangeDataScatterplot
  from lightly.openapi_generated.swagger_client.models.tag_change_data_upsize import TagChangeDataUpsize
label_desc: Use image node_id 4 for calling the TagChangeData obj's underlying member method code with example usage: obj.to_dict(by_alias) and returns: _dict