code: def slice(inputs, start_indices, shape):
      shape_dtype = to_torch_dtype("int64")
      inputs = convert_to_tensor(inputs)
      start_indices = convert_to_tensor(start_indices).to(shape_dtype)
      shape = convert_to_tensor(shape).to(shape_dtype)
  
      python_slice = __builtins__["slice"]
      slices = [
          python_slice(start_index, start_index + length)
          for start_index, length in zip(start_indices, shape)
      ]
      return inputs[slices]
  
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 15 for calling a global function with example usage: slice(inputs, start_indices, shape) and returns: inputs