class_docstr: Wrapper class for networks specified as Keras model (specification key: `keras`).
  
  Args:
      model (tf.keras.Model): Keras model
          (<span style="color:#C00000"><b>required</b></span>).
      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>.
      inputs_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      outputs (iter[string]): <span style="color:#0000C0"><b>internal use</b></span>.
      kwargs: Arguments for the Keras model.
code: def apply(
      self, *, x, horizons, internals, deterministic, independent
  ):
      if x.is_singleton():
          inputs = x.singleton()
      else:
          inputs = list(x.values())
  
      x = self.keras_model(inputs=inputs, training=(not independent))
  
      return tf_util.cast(x=x, dtype="float"), internals
  
file_path: tensorforce/tensorforce/core/networks/keras.py
imports: import tensorflow
  from tensorforce import TensorforceError
  from tensorforce.core import TensorSpec, tf_function, tf_util
  from tensorforce.core.networks import Network
label_desc: Use image node_id 6 for calling the KerasNetwork obj's underlying member method code with example usage: obj.apply() and returns: tf_util,  internals