code: def _get_chunk(cls, op, chunk_k, chunk_shape, chunk_idx):
      assert chunk_shape[0] == chunk_shape[1]
      input_idx = chunk_idx[1] if op.k < 0 else chunk_idx[0]
      input_chunk = op.inputs[0].cix[input_idx,]
      op = TensorDiag(
          k=chunk_k, dtype=op.dtype, gpu=op.gpu, sparse=op.sparse
      )
      return op.new_chunk(
          [input_chunk], shape=chunk_shape, index=chunk_idx
      )
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...serialization.serializables import KeyField, Int32Field
  from ...utils import has_unknown_shape
  from ..core import TENSOR_TYPE
  from ...lib.sparse import diag
  from ...lib.sparse.core import issparse, get_array_module, get_sparse_module
  from ...lib import sparse
  from ..core import TensorOrder
  from ..array_utils import create_array
  from .core import TensorHasInput
  from .zeros import TensorZeros
  from .array import tensor
label_desc: Use image node_id 5 for calling the TensorDiag obj's underlying member method code with example usage: obj._get_chunk(cls, op, chunk_k, chunk_shape, chunk_idx) and returns: op