class_docstr: Class to bind an optimizer, model, strategy, and training step function.
class_docstr_tok: ["Class","to","bind","an","optimizer",",","model",",","strategy",",","and","training","step","function","."]
docstr: Model arg can also be a tf.train.Checkpoint(**dict(submodules)).
docstr_tok: ["Model","arg","can","also","be","a","tf.train.Checkpoint","(","*","*","dict","(","submodules",")",")","."]
code: def get_checkpoint(self, model=None):
      """Model arg can also be a tf.train.Checkpoint(**dict(submodules))."""
      model = model or self.model  # Default to full model.
      return tf.train.Checkpoint(model=model, optimizer=self.optimizer)
  
file_path: ddsp/ddsp/training/trainers.py
imports: import time
  from absl import logging
  from ddsp.training import train_util
  import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the Trainer obj's underlying member method code with example usage: obj.get_checkpoint(model) and returns: tf