code: def dummy_text_encoder(self):
      torch.manual_seed(0)
      config = RobertaSeriesConfig(
          hidden_size=32,
          project_dim=32,
          intermediate_size=37,
          layer_norm_eps=1e-05,
          num_attention_heads=4,
          num_hidden_layers=5,
          pad_token_id=1,
          vocab_size=5006,
      )
      return RobertaSeriesModelWithTransformation(config)
  
imports: import gc
  import random
  import unittest
  import numpy
  import torch
  from transformers import XLMRobertaTokenizer
  from diffusers import AltDiffusionImg2ImgPipeline, AutoencoderKL, PNDMScheduler, UNet2DConditionModel
  from diffusers.image_processor import VaeImageProcessor
  from diffusers.pipelines.alt_diffusion.modeling_roberta_series import RobertaSeriesConfig, RobertaSeriesModelWithTransformation
  from diffusers.utils import load_image
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, load_numpy, nightly, require_torch_gpu, torch_device
label_desc: Use image node_id 5 for calling the AltDiffusionImg2ImgPipelineFastTests obj's underlying member method code with example usage: obj.dummy_text_encoder() and returns: RobertaSeriesModelWithTransformation