code: def get_images_embeddings(self, images):
      features = self.image_encoder.forward_features(images)
      return self.image_pooler(features)
  
imports: from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import nn
  from torchvision.transforms import *
  from transformers import AutoConfig, AutoTokenizer
  from transformers.configuration_utils import PretrainedConfig
  from transformers.modeling_outputs import CausalLMOutputWithPast
  from transformers.modeling_utils import PreTrainedModel
  from transformers.models.auto.modeling_auto import AutoModel, AutoModelForCausalLM
  from transformers.processing_utils import ProcessorMixin
  from transformers.tokenization_utils_base import BatchEncoding
  from uform.models import VisualEncoder
label_desc: Use image node_id 4 for calling the VLMForCausalLM obj's underlying member method code with example usage: obj.get_images_embeddings(images) and returns: self