class_docstr: SGD with Momentum module.
  
  Attributes:
    learning_rate: Learning rate.
    momentum: Momentum scalar.
    use_nesterov: `True` if using Nesterov momentum.
    accumulated_momentum: Accumulated momentum for each parameter.
class_docstr_tok: ["SGD","with","Momentum","module",".","Attributes",":","learning_rate",":","Learning","rate",".","momentum",":","Momentum","scalar",".","use_nesterov",":","`","True","`","if","using","Nesterov","momentum",".","accumulated_momentum",":","Accumulated","momentum","for","each","parameter","."]
code: def _initialize(self, parameters):
      with tf.name_scope("accumulated_momentum"):
          self.accumulated_momentum.extend(
              utils.variable_like(p, trainable=False)
              for p in parameters
          )
  
file_path: sonnet/sonnet/src/optimizers/momentum.py
imports: from typing import Optional, Sequence, Union
  from sonnet.src import base
  from sonnet.src import once
  from sonnet.src import types
  from sonnet.src import utils
  from sonnet.src.optimizers import optimizer_utils
  import tensorflow
label_desc: Use image node_id 2 for calling the Momentum obj's underlying member method code with example usage: obj._initialize(parameters) without return types