code: def softmax(x: np.ndarray, axis: int = -1) -> np.ndarray:
      x_max = np.max(x, axis=axis, keepdims=True)
      tmp = np.exp(x - x_max)
      s = np.sum(tmp, axis=axis, keepdims=True)
      return tmp / s
  
imports: import torch
  from pathlib import Path
  from .onnx_helper import load_model
  from .learner_ner import group_entities
  from .data_ner import get_labels
  from transformers import AutoTokenizer
  import numpy
  import warnings
label_desc: Use image node_id 1 for calling a global function with example usage: softmax(x, axis) and returns: unknown