code: def get_dummy_inputs(self, device, seed=0):
      if str(device).startswith("mps"):
          generator = torch.manual_seed(seed)
      else:
          generator = torch.Generator(device=device).manual_seed(seed)
      inputs = {
          "prompt": "A modern livingroom",
          "generator": generator,
          "num_inference_steps": 2,
          "guidance_scale": 6.0,
          "gligen_phrases": ["a birthday cake"],
          "gligen_boxes": [[0.2676, 0.6088, 0.4773, 0.7183]],
          "output_type": "np",
      }
      return inputs
  
file_path: diffusers/tests/pipelines/stable_diffusion/test_stable_diffusion_gligen.py
imports: import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, StableDiffusionGLIGENPipeline, UNet2DConditionModel
  from diffusers.utils.testing_utils import enable_full_determinism
  from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
  from ..test_pipelines_common import PipelineKarrasSchedulerTesterMixin, PipelineLatentTesterMixin, PipelineTesterMixin
label_desc: Use image node_id 2 for calling the GligenPipelineFastTests obj's underlying member method code with example usage: obj.get_dummy_inputs(device, seed) and returns: inputs