class_docstr: Base class for modules.
  
  Args:
      device (string): Device name
          (<span style="color:#00C000"><b>default</b></span>: inherit value of parent module).
      l2_regularization (float >= 0.0): Scalar controlling L2 regularization
          (<span style="color:#00C000"><b>default</b></span>: inherit value of parent module).
      name (string): <span style="color:#0000C0"><b>internal use</b></span>.
code: def submodule(
      self,
      *,
      name,
      module=None,
      modules=None,
      default_module=None,
      is_trainable=True,
      is_saved=True,
      **kwargs,
  ):
      assert self.is_initialized is None
  
      # name
      if any(name == module.name for module in self.this_submodules):
          raise TensorforceError.exists(name="module", value=name)
  
      # is_trainable
      if not isinstance(is_trainable, bool):
          raise TensorforceError.type(
              name="Module.add_module",
              argument="is_trainable",
              dtype=type(is_trainable),
          )
  
      # is_saved
      if not isinstance(is_saved, bool):
          raise TensorforceError.type(
              name="Module.add_module",
              argument="is_saved",
              dtype=type(is_saved),
          )
  
      # module, modules, default_module
      module_cls, args, kwargs = Module.get_module_class_and_args(
          name=name,
          module=module,
          modules=modules,
          default_module=default_module,
          **kwargs,
      )
  
      # Module constructor
      Module._MODULE_STACK.append(module_cls)
      module = module_cls(*args, **kwargs)
      popped = Module._MODULE_STACK.pop()
      assert popped is module
  
      assert module.is_trainable is None
      module.is_trainable = is_trainable
      assert module.is_saved is None
      module.is_saved = is_saved
  
      return module
  
imports: import functools
  import json
  import os
  import re
  import numpy
  import tensorflow
  from tensorforce import TensorforceError, util
  import tensorforce.core
  from tensorforce.core import SignatureDict, TensorSpec, tf_util, VariableDict
label_desc: Use image node_id 19 for calling the Module obj's underlying member method code with example usage: obj.submodule() and returns: module