code: def _process_texts(self, text_list):
      input_tensors = list(map(self._convert_to_tensors, text_list))
      keys = set(input_tensors[0].keys())
      padded = {}
      for key in keys:
          padded[key] = pad(
              input_tensors, key, padding_side="left"
          ).cuda()
      return padded
  
file_path: DeepKE/example/llm/CPM-Bee/src/cpm_live/generation/ant.py
imports: import torch
  import torch.nn.functional
  from .generation_utils import BeamHypotheses, apply_repetition_penalty, top_k_top_p_filtering
  from ..utils import pad
label_desc: Use image node_id 3 for calling the CPMAntGeneration obj's underlying member method code with example usage: obj._process_texts(text_list) and returns: padded