code: def create_unidiffuser_unet_config_big():
      unet_config = {
          "text_dim": 64,
          "clip_img_dim": 512,
          "num_text_tokens": 77,
          "num_attention_heads": 24,
          "attention_head_dim": 64,
          "in_channels": 4,
          "out_channels": 4,
          "num_layers": 30,
          "dropout": 0.0,
          "norm_num_groups": 32,
          "attention_bias": False,
          "sample_size": 64,
          "patch_size": 2,
          "activation_fn": "gelu",
          "num_embeds_ada_norm": 1000,
          "norm_type": "layer_norm",
          "block_type": "unidiffuser",
          "pre_layer_norm": False,
          "use_timestep_embedding": False,
          "norm_elementwise_affine": True,
          "use_patch_pos_embed": False,
          "ff_final_dropout": True,
          "use_data_type_embedding": False,
      }
      return unet_config
  
imports: import argparse
  from argparse import Namespace
  import torch
  from transformers import CLIPImageProcessor, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig, CLIPVisionModelWithProjection, GPT2Tokenizer
  from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, UniDiffuserModel, UniDiffuserPipeline, UniDiffuserTextDecoder
label_desc: Use image node_id 13 for calling a global function with example usage: create_unidiffuser_unet_config_big() and returns: unet_config