code: def get_inputs(self, device, dtype=torch.float32, seed=0):
      generator = torch.manual_seed(seed)
      latents = np.random.RandomState(seed).standard_normal(
          (1, 4, 32, 32)
      )
      latents = torch.from_numpy(latents).to(device=device, dtype=dtype)
      inputs = {
          "prompt": "A painting of a squirrel eating a burger",
          "latents": latents,
          "generator": generator,
          "num_inference_steps": 3,
          "guidance_scale": 6.0,
          "output_type": "numpy",
      }
      return inputs
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism, load_numpy, nightly, require_torch_gpu, torch_device
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineTesterMixin
label_desc: Use image node_id 2 for calling the LDMTextToImagePipelineSlowTests obj's underlying member method code with example usage: obj.get_inputs(device, dtype, seed) and returns: inputs