class_docstr: TensorFlow optimizer (specification key: `tf_optimizer`, `adadelta`, `adagrad`, `adam`,
  `adamax`, `adamw`, `ftrl`, `lazyadam`, `nadam`, `radam`, `ranger`, `rmsprop`, `sgd`, `sgdw`)
  
  Args:
      optimizer (`adadelta` | `adagrad` | `adam` | `adamax` | `adamw` | `ftrl` | `lazyadam` | `nadam` | `radam` | `ranger` | `rmsprop` | `sgd` | `sgdw`):
          TensorFlow optimizer name, see
          `TensorFlow docs <https://www.tensorflow.org/api_docs/python/tf/keras/optimizers>`__
          and `TensorFlow Addons docs
          <https://www.tensorflow.org/addons/api_docs/python/tfa/optimizers>`__
          (<span style="color:#C00000"><b>required</b></span> unless given by specification key).
      learning_rate (parameter, float > 0.0): Learning rate
          (<span style="color:#C00000"><b>required</b></span>).
      gradient_norm_clipping (parameter, float > 0.0): Clip gradients by the ratio of the sum
          of their norms (<span style="color:#00C000"><b>default</b></span>: 1.0).
      name (string): (<span style="color:#0000C0"><b>internal use</b></span>).
      arguments_spec (specification): <span style="color:#0000C0"><b>internal use</b></span>.
      kwargs: Arguments for the TensorFlow optimizer, special values "decoupled_weight_decay",
          "lookahead" and "moving_average", see
          `TensorFlow docs <https://www.tensorflow.org/api_docs/python/tf/keras/optimizers>`__
          and `TensorFlow Addons docs
          <https://www.tensorflow.org/addons/api_docs/python/tfa/optimizers>`__.
code: def initialize(self):
      super().initialize()
  
      self.tf_optimizer = self.tf_optimizer(
          learning_rate=self.learning_rate.value,
          name="tf_optimizer",
          **self.optimizer_kwargs,
      )
  
      self.register_summary(
          label="update-norm", name="unclipped-gradient-norm"
      )
  
file_path: tensorforce/tensorforce/core/optimizers/tf_optimizer.py
imports: from functools import partial
  import tensorflow
  from tensorforce.core import parameter_modules, tf_function, tf_util
  from tensorforce.core.optimizers import Optimizer
label_desc: Use image node_id 2 for calling the TFOptimizer obj's underlying member method code with example usage: obj.initialize() without return types