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 compute_dynamic_batch_size(
      self,
      curr_epoch: int,
      scheduler_config: BatcherSchedulerConfig,
      curr_steps: int,
  ) -> int:
      raise NotImplementedError()
  
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 3 for calling the DynamicPoolingBatcher obj's underlying member method code with example usage: obj.compute_dynamic_batch_size(curr_epoch, scheduler_config, curr_steps) without return types