code: def test_inference_batch_single_identical(
      self,
      batch_size=2,
      expected_max_diff=1e-4,
  ):
      components = self.get_dummy_components()
      pipe = self.pipeline_class(**components)
      for components in pipe.components.values():
          if hasattr(components, "set_default_attn_processor"):
              components.set_default_attn_processor()
      pipe.to(torch_device)
  
      pipe.set_progress_bar_config(disable=None)
      inputs = self.get_dummy_inputs(torch_device)
  
      # Reset generator in case it is has been used in self.get_dummy_inputs
      inputs["generator"] = torch.Generator("cpu").manual_seed(0)
  
      logger = logging.get_logger(pipe.__module__)
      logger.setLevel(level=diffusers.logging.FATAL)
  
      # batchify inputs
      batched_inputs = {}
      batched_inputs.update(inputs)
  
      batched_inputs["generator"] = [
          torch.Generator("cpu").manual_seed(0)
          for i in range(batch_size)
      ]
      batched_inputs["image"] = torch.cat(
          [inputs["image"]] * batch_size, dim=0
      )
  
      output = pipe(**inputs).frames
      output_batch = pipe(**batched_inputs).frames
  
      assert len(output_batch) == batch_size
  
      max_diff = np.abs(to_np(output_batch[0]) - to_np(output[0])).max()
      assert max_diff < expected_max_diff
  
imports: import gc
  import random
  import tempfile
  import unittest
  import numpy
  import torch
  from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModelWithProjection
  import diffusers
  from diffusers import AutoencoderKLTemporalDecoder, EulerDiscreteScheduler, StableVideoDiffusionPipeline, UNetSpatioTemporalConditionModel
  from diffusers.utils import is_accelerate_available, is_accelerate_version, load_image, logging
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import CaptureLogger, disable_full_determinism, enable_full_determinism, floats_tensor, numpy_cosine_similarity_distance, require_torch_gpu, slow, torch_device
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the StableVideoDiffusionPipelineFastTests obj's underlying member method code with example usage: obj.test_inference_batch_single_identical(batch_size, expected_max_diff) without return types