code: def _initialize(self, value):
      if isinstance(value, torch.nn.Parameter):
          # Reuse same parameter
          self._value = value
      else:
          self._value = torch.nn.Parameter(
              convert_to_tensor(value, dtype=self._dtype),
              requires_grad=self.trainable,
          ).to(get_device())
  
imports: import contextlib
  import os
  import numpy
  import torch
  import tree
  from keras.backend.common import KerasVariable
  from keras.backend.common import global_state
  from keras.backend.common import standardize_dtype
  from keras.backend.common.dtypes import result_type
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.backend.common.stateless_scope import StatelessScope
  from keras.backend.config import floatx
  from keras.utils.nest import pack_sequence_as
label_desc: Use image node_id 1 for calling the Variable obj's underlying member method code with example usage: obj._initialize(value) without return types