code: def _optimizers(proto, default_context, networks, datasets):
      optimizers = OrderedDict()
  
      for o in proto.optimizer:
          ctx = (
              default_context
              if not o.solver.context.backends
              else _context(o.solver.context)
          )
          optimizer = _create_optimizer(ctx, o, networks, datasets)
          optimizers[o.name] = optimizer
  
      return optimizers
  
imports: from collections import OrderedDict
  import google.protobuf.text_format
  import itertools
  import numpy
  import os
  import re
  import shutil
  import tempfile
  from nnabla.initializer import NormalInitializer, UniformInitializer, ConstantInitializer, RangeInitializer, calc_normal_std_he_forward, calc_normal_std_he_backward, calc_normal_std_glorot, calc_uniform_lim_glorot
  from nnabla.logger import logger
  from nnabla.parameter import get_parameter_or_create
  from nnabla.utils import nnabla_pb2
  from nnabla.utils.data_iterator import data_iterator_csv_dataset, data_iterator_cache
  from nnabla.utils.create_cache import CreateCache
  from nnabla.utils.load_function import _create_function_instance
  from nnabla.utils.nnp_format import nnp_version
  from nnabla.utils.communicator_util import current_communicator, single_or_rankzero
  from nnabla.utils.learning_rate_scheduler import PolynomialScheduler, CosineScheduler, ExponentialScheduler, StepScheduler, LinearWarmupScheduler
  from legacy_network import Network
  from nnabla.utils.progress import progress
  from legacy_get_file_handle import get_file_handle_load, get_buf_type
  import nnabla
  import nnabla.function
  import nnabla.solver
label_desc: Use image node_id 15 for calling a global function with example usage: _optimizers(proto, default_context, networks, datasets) and returns: optimizers