code: def get_dummy_inputs(self):
      noisy_latents = torch.randn(
          self.batch_size,
          self.num_in_channels,
          self.latent_height,
          self.latent_width,
          generator=self.generator,
      ).to(torch_device)
      timesteps = torch.randint(
          0, 1000, size=(self.batch_size,), generator=self.generator
      ).to(torch_device)
      encoder_hidden_states = torch.randn(
          self.batch_size,
          self.prompt_length,
          self.text_encoder_hidden_dim,
          generator=self.generator,
      ).to(torch_device)
      return noisy_latents, timesteps, encoder_hidden_states
  
file_path: llmga/llmga/diffusers/tests/others/test_ema.py
imports: import tempfile
  import unittest
  import torch
  from diffusers import UNet2DConditionModel
  from diffusers.training_utils import EMAModel
  from diffusers.utils.testing_utils import enable_full_determinism, skip_mps, torch_device
label_desc: Use image node_id 2 for calling the EMAModelTests obj's underlying member method code with example usage: obj.get_dummy_inputs() and returns: noisy_latents,  timesteps,  encoder_hidden_states