code: def execute(cls, ctx, op):
      chunk = op.outputs[0]
      if op.issparse():
          in_data = naked(ctx[op.inputs[0].key])
          xps = get_sparse_module(in_data)
          xp = get_array_module(in_data)
          ctx[chunk.key] = SparseNDArray(
              xps.csr_matrix(
                  (
                      xp.empty_like(in_data.data, dtype=op.dtype),
                      in_data.indices,
                      in_data.indptr,
                  ),
                  shape=in_data.shape,
              )
          )
      else:
          ctx[chunk.key] = create_array(op)(
              "empty_like",
              ctx[op.inputs[0].key],
              dtype=op.dtype,
              order=op.order,
          )
  
imports: import numpy
  from ...None import opcodes
  from ...serialization.serializables import KeyField, StringField
  from ...lib.sparse import SparseNDArray
  from ...lib.sparse.core import naked, get_array_module, get_sparse_module
  from ..array_utils import create_array
  from ..utils import get_order
  from .core import TensorNoInput, TensorLike
  from .array import tensor
label_desc: Use image node_id 3 for calling the TensorEmptyLike obj's underlying member method code with example usage: obj.execute(cls, ctx, op) without return types