code: def test_inference_flant5_xl(self):
      processor = InstructBlipProcessor.from_pretrained(
          "Salesforce/instructblip-flan-t5-xl"
      )
      model = InstructBlipForConditionalGeneration.from_pretrained(
          "Salesforce/instructblip-flan-t5-xl",
          torch_dtype=torch.bfloat16,
          low_cpu_mem_usage=True,
      ).to(torch_device)
  
      url = "https://raw.githubusercontent.com/salesforce/LAVIS/main/docs/_static/Confusing-Pictures.jpg"
      image = Image.open(requests.get(url, stream=True).raw).convert(
          "RGB"
      )
      prompt = "What is unusual about this image?"
      inputs = processor(
          images=image, text=prompt, return_tensors="pt"
      ).to(torch_device)
  
      for k, v in inputs.items():
          if torch.is_floating_point(v):
              inputs[k] = v.to(torch.bfloat16)
  
      outputs = model.generate(
          **inputs,
          do_sample=False,
          num_beams=5,
          max_length=256,
          min_length=1,
          top_p=0.9,
          repetition_penalty=1.5,
          length_penalty=1.0,
          temperature=1,
      )
      generated_text = processor.batch_decode(
          outputs, skip_special_tokens=True
      )[0]
  
      expected_outputs = [0, 37, 1023, 9850, 7, 3, 9, 388, 3575, 53, 4954, 30, 8, 223, 13, 3, 9, 4459, 4049, 16, 8, 2214, 13, 3, 9, 3164, 690, 2815, 5, 37, 388, 19, 5119, 3, 9, 4459, 8677, 28, 3, 9, 2756, 4459, 6177, 6, 11, 3, 88, 19, 338, 46, 3575, 53, 1476, 12, 743, 112, 2491, 5, 37, 1023, 19, 7225, 788, 12, 8, 685, 24, 34, 1267, 3, 9, 388, 3575, 53, 4954, 30, 8, 223, 13, 3, 9, 4049, 16, 8, 2214, 13, 3, 9, 3164, 690, 2815, 5, 94, 19, 487, 24, 8, 388, 19, 1119, 12, 1097, 540, 57, 692, 112, 10428, 30, 8, 223, 13, 8, 4049, 6, 68, 34, 19, 92, 487, 24, 3, 88, 19, 1119, 12, 1097, 97, 57, 692, 112, 10428, 30, 8, 223, 13, 8, 4049, 16, 8, 2214, 13, 3, 9, 3164, 690, 2815, 5, 3, 13865, 13, 8, 1053, 21, 8, 388, 31, 7, 2874, 6, 34, 19, 964, 24, 3, 88, 19, 1119, 12, 1097, 97, 57, 692, 112, 10428, 30, 8, 223, 13, 8, 4049, 16, 8, 2214, 13, 3, 9, 3164, 690, 2815, 5, 1]  # fmt: skip
      self.assertEqual(outputs[0].tolist(), expected_outputs)
      self.assertEqual(
          generated_text,
          "The image depicts a man ironing clothes on the back of a yellow van in the middle of a busy city street. The man is wearing a yellow shirt with a bright yellow tie, and he is using an ironing board to complete his task. The image is unusual due to the fact that it shows a man ironing clothes on the back of a van in the middle of a busy city street. It is possible that the man is trying to save money by doing his laundry on the back of the van, but it is also possible that he is trying to save time by doing his laundry on the back of the van in the middle of a busy city street. Regardless of the reason for the man's actions, it is clear that he is trying to save time by doing his laundry on the back of the van in the middle of a busy city street.",
      )
  
imports: import inspect
  import tempfile
  import unittest
  import numpy
  import requests
  from transformers import CONFIG_MAPPING, InstructBlipConfig, InstructBlipProcessor, InstructBlipQFormerConfig, InstructBlipVisionConfig
  from transformers.testing_utils import require_accelerate, require_bitsandbytes, require_torch, require_vision, slow, torch_device
  from transformers.utils import is_torch_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 2 for calling the InstructBlipModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_flant5_xl() without return types