class_docstr: Allows dynamic batch training, extends pooling batcher with a scheduler
  config, which specifies how batch size should increase
class_docstr_tok: ["Allows","dynamic","batch","training",",","extends","pooling","batcher","with","a","scheduler","config",",","which","specifies","how","batch","size","should","increase"]
code: def finished_dynamic(self) -> bool:
      return (
          self.scheduler_config.epoch_period != -1
          and self.curr_epoch >= self.scheduler_config.epoch_period
      )
  
imports: import math
  from typing import Iterable
  from pytext.common.constants import Stage
  from pytext.config.module_config import ModuleConfig
  from .data import PoolingBatcher
  from .sources import RawExample
label_desc: Use image node_id 5 for calling the DynamicPoolingBatcher obj's underlying member method code with example usage: obj.finished_dynamic() and returns: unknown