code: def create_and_check_model_as_decoder(
      self,
      config,
      input_ids,
      token_type_ids,
      input_mask,
      sequence_labels,
      token_labels,
      choice_labels,
      encoder_hidden_states,
      encoder_attention_mask,
  ):
      config.add_cross_attention = True
      model = PhiModel(config)
      model.to(torch_device)
      model.eval()
      result = model(
          input_ids,
          attention_mask=input_mask,
          encoder_hidden_states=encoder_hidden_states,
          encoder_attention_mask=encoder_attention_mask,
      )
      result = model(
          input_ids,
          attention_mask=input_mask,
          encoder_hidden_states=encoder_hidden_states,
      )
      result = model(input_ids, attention_mask=input_mask)
      self.parent.assertEqual(
          result.last_hidden_state.shape,
          (self.batch_size, self.seq_length, self.hidden_size),
      )
  
imports: import unittest
  import pytest
  from transformers import PhiConfig, is_torch_available
  from transformers.testing_utils import require_bitsandbytes, require_flash_attn, require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 5 for calling the PhiModelTester obj's underlying member method code with example usage: obj.create_and_check_model_as_decoder(config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels, encoder_hidden_states, encoder_attention_mask) without return types