code: def generate_key(self, *shape):
      newshape = list(shape)
      newshape[0] = self._num_passport
      if self._passport_mode == "single":
          if self._passport_distribute == "uniform":
              key = np.random.uniform(self._low, self._high, newshape)
          elif self._passport_distribute == "gaussian":
              key = np.random.normal(self._loc, self._scale, newshape)
          else:
              raise ValueError(
                  "Wrong passport type (uniform or gaussian)"
              )
  
      elif self._passport_mode == "multi":
          assert self._low < self._high
          channel = newshape[1]
          keys = []
          for c in range(channel):
              candidates = range(int(self._low), int(self._high), 1)
              a = random.sample(candidates, 1)[0]
              while a == 0:
                  a = random.sample(candidates, 1)[0]
              b = 1
              newshape[1] = 1
              if self._passport_distribute == "uniform":
                  key = np.random.uniform(
                      self._low, self._high, newshape
                  )
              elif self._passport_distribute == "gaussian":
                  key = np.random.normal(a, b, newshape)
              else:
                  raise ValueError(
                      "Wrong passport type (uniform or gaussian)"
                  )
              keys.append(key)
          key = np.concatenate(keys, axis=1)
      else:
          raise ValueError(
              "Wrong passport mode, in ['single', 'multi']"
          )
      return key
  
imports: import random
  import torch
  from torch import nn
  import numpy
  from typing import Literal
label_desc: Use image node_id 2 for calling the ConvPassportBlock obj's underlying member method code with example usage: obj.generate_key() and returns: key