class_docstr: A mutable module is a module that supports variable input data.
  
  Parameters
  ----------
  symbol : Symbol
  data_names : list of str
  label_names : list of str
  logger : Logger
  context : Context or list of Context
  work_load_list : list of number
  max_data_shapes : list of (name, shape) tuple, designating inputs whose shape vary
  max_label_shapes : list of (name, shape) tuple, designating inputs whose shape vary
  fixed_param_prefix : list of str, indicating fixed parameters
code: def forward(self, data_batch, is_train=None):
      assert self.binded and self.params_initialized
  
      # get current_shapes
      if self._curr_module.label_shapes is not None:
          current_shapes = dict(
              self._curr_module.data_shapes
              + self._curr_module.label_shapes
          )
      else:
          current_shapes = dict(self._curr_module.data_shapes)
  
      # get input_shapes
      if data_batch.provide_label is not None:
          input_shapes = dict(
              data_batch.provide_data + data_batch.provide_label
          )
      else:
          input_shapes = dict(data_batch.provide_data)
  
      # decide if shape changed
      shape_changed = False
      for k, v in current_shapes.items():
          if v != input_shapes[k]:
              shape_changed = True
  
      if shape_changed:
          module = Module(
              self._symbol,
              self._data_names,
              self._label_names,
              logger=self.logger,
              context=self._context,
              work_load_list=self._work_load_list,
              fixed_param_names=self._fixed_param_names,
          )
          module.bind(
              data_batch.provide_data,
              data_batch.provide_label,
              self._curr_module.for_training,
              self._curr_module.inputs_need_grad,
              force_rebind=False,
              shared_module=self._curr_module,
          )
          self._curr_module = module
  
      self._curr_module.forward(data_batch, is_train=is_train)
  
imports: import logging
  from mxnet import context
  from mxnet.initializer import Uniform
  from mxnet.module.base_module import BaseModule
  from mxnet.module.module import Module
label_desc: Use image node_id 12 for calling the MutableModule obj's underlying member method code with example usage: obj.forward(data_batch, is_train) without return types