code: def DISABLED_test_load_save(self):
      text_field_meta = FieldMeta()
      text_field_meta.vocab = VocabStub()
      text_field_meta.vocab_size = 4
      text_field_meta.unk_token_idx = 1
      text_field_meta.pad_token_idx = 0
      text_field_meta.pretrained_embeds_weight = None
      label_meta = FieldMeta()
      label_meta.vocab = VocabStub()
      label_meta.vocab_size = 3
      metadata = CommonMetadata()
      metadata.features = {DatasetFieldName.TEXT_FIELD: text_field_meta}
      metadata.target = label_meta
  
      saved_model = create_model(
          DocModel.Config(
              representation=BiLSTMDocAttention.Config(
                  save_path=self.representation_path
              ),
              decoder=MLPDecoder.Config(save_path=self.decoder_path),
          ),
          FeatureConfig(save_path=self.embedding_path),
          metadata,
      )
      saved_model.save_modules()
  
      loaded_model = create_model(
          DocModel.Config(
              representation=BiLSTMDocAttention.Config(
                  load_path=self.representation_path
              ),
              decoder=MLPDecoder.Config(load_path=self.decoder_path),
          ),
          FeatureConfig(load_path=self.embedding_path),
          metadata,
      )
  
      random_model = create_model(
          DocModel.Config(
              representation=BiLSTMDocAttention.Config(),
              decoder=MLPDecoder.Config(),
          ),
          FeatureConfig(),
          metadata,
      )
  
      # Loaded and saved modules should be equal. Neither should be equal to
      # a randomly initialised model.
  
      for p1, p2, p3 in itertools.zip_longest(
          saved_model.embedding.parameters(),
          loaded_model.embedding.parameters(),
          random_model.embedding.parameters(),
      ):
          self.assertTrue(p1.equal(p2))
          self.assertFalse(p3.equal(p1))
          self.assertFalse(p3.equal(p2))
  
      for p1, p2, p3 in itertools.zip_longest(
          saved_model.representation.parameters(),
          loaded_model.representation.parameters(),
          random_model.representation.parameters(),
      ):
          self.assertTrue(p1.equal(p2))
          self.assertFalse(p3.equal(p1))
          self.assertFalse(p3.equal(p2))
  
      for p1, p2, p3 in itertools.zip_longest(
          saved_model.decoder.parameters(),
          loaded_model.decoder.parameters(),
          random_model.decoder.parameters(),
      ):
          self.assertTrue(p1.equal(p2))
          self.assertFalse(p3.equal(p1))
          self.assertFalse(p3.equal(p2))
  
file_path: pytext/tests/module_load_save_test.py
imports: import itertools
  import os
  import tempfile
  import unittest
  from pytext.common.constants import DatasetFieldName
  from pytext.config.component import create_model
  from pytext.config.field_config import FeatureConfig
  from pytext.data import CommonMetadata
  from pytext.fields import FieldMeta
  from pytext.models.decoders.mlp_decoder import MLPDecoder
  from pytext.models.doc_model import DocModel
  from pytext.models.representations.bilstm_doc_attention import BiLSTMDocAttention
label_desc: Use image node_id 3 for calling the ModuleLoadSaveTest obj's underlying member method code with example usage: obj.DISABLED_test_load_save() without return types