code: def get_text_features(
      self,
      input_ids,
      attention_mask=None,
      position_ids=None,
      output_attentions=False,
      output_hidden_states=False,
      return_dict=False,
  ):
      text_outputs = self.text_model(
          input_ids=input_ids,
          position_ids=position_ids,
          attention_mask=attention_mask,
          output_attentions=output_attentions,
          output_hidden_states=output_hidden_states,
          return_dict=return_dict,
      )
      pooled_output = text_outputs[1]
      text_features = paddle.matmul(pooled_output, self.text_projection)
      return text_features
  
imports: import paddle
  import paddle.nn
  from paddlenlp.transformers.clip.modeling import TextTransformer
label_desc: Use image node_id 2 for calling the CLIPText obj's underlying member method code with example usage: obj.get_text_features(input_ids, attention_mask, position_ids, output_attentions, output_hidden_states, return_dict) and returns: text_features