class_docstr: Example of using embedded eager execution in a custom model.
  
  This shows how to use tf.py_function() to execute a snippet of TF code
  in eager mode. Here the `self.forward_eager` method just prints out
  the intermediate tensor for debug purposes, but you can in general
  perform any TF eager operation in tf.py_function().
code: def forward_eager(self, feature_layer):
      assert tf.executing_eagerly()
      if random.random() > 0.99:
          print(
              "Eagerly printing the feature layer mean value",
              tf.reduce_mean(feature_layer),
          )
      return feature_layer
  
file_path: ray/python/ray/rllib/examples/models/eager_model.py
imports: import random
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.models.tf.fcnet import FullyConnectedNetwork
  from ray.rllib.models.tf.tf_modelv2 import TFModelV2
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 4 for calling the EagerModel obj's underlying member method code with example usage: obj.forward_eager(feature_layer) and returns: feature_layer