code: def test_deep_estimator_full(optimizer):
      """Check if serialization works for full dummy."""
      from tensorflow.keras.optimizers import (
          Adamax,
          Optimizer,
          serialize,
      )
  
      if optimizer == "object-adamax":
          optimizer = Adamax()
  
      full_dummy = _DummyDeepClassifierFull(optimizer)
      serialized_full = pickle.dumps(full_dummy)
      deserialized_full = pickle.loads(serialized_full)
  
      if isinstance(optimizer, Optimizer):
          # assert same configuration of optimizer
          assert serialize(
              full_dummy.__dict__["optimizer"]
          ) == serialize(deserialized_full.__dict__["optimizer"])
          assert serialize(full_dummy.optimizer) == serialize(
              deserialized_full.optimizer
          )
  
          # assert weights of optimizers are same
          assert (
              full_dummy.optimizer.variables()
              == deserialized_full.optimizer.variables()
          )
  
          # remove optimizers from both to do full dict check,
          # since two different objects
          del full_dummy.__dict__["optimizer"]
          del deserialized_full.__dict__["optimizer"]
  
      # check if components are same
      assert full_dummy.__dict__ == deserialized_full.__dict__
  
imports: import pickle
  import numpy
  import pandas
  import pytest
  from sklearn.model_selection import KFold
  from sktime.classification.base import BaseClassifier
  from sktime.classification.deep_learning.base import BaseDeepClassifier
  from sktime.classification.distance_based import KNeighborsTimeSeriesClassifier
  from sktime.classification.dummy import DummyClassifier
  from sktime.utils._testing.estimator_checks import _assert_array_almost_equal
  from sktime.utils._testing.panel import _make_classification_y, _make_panel, make_classification_problem
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 14 for calling a global function with example usage: test_deep_estimator_full(optimizer) without return types