class_docstr: Algorithm that returns sigmoid learning curves.
  
  This can be helpful for evaluating early stopping algorithms.
class_docstr_tok: ["Algorithm","that","returns","sigmoid","learning","curves",".","This","can","be","helpful","for","evaluating","early","stopping","algorithms","."]
code: def get_default_config(cls) -> AlgorithmConfig:
      return AlgorithmConfig().update_from_dict(
          {
              "width": 100,
              "height": 100,
              "offset": 0,
              "iter_time": 10,
              "iter_timesteps": 1,
          }
      )
  
imports: import os
  import pickle
  import time
  import numpy
  from ray.tune import result
  from ray.rllib.algorithms.algorithm import Algorithm, AlgorithmConfig
  from ray.rllib.utils.annotations import override
label_desc: Use image node_id 1 for calling the _SigmoidFakeData obj's underlying member method code with example usage: obj.get_default_config(cls) and returns: AlgorithmConfig