code: def execute_sparse(cls, ctx, op):
      chunk = op.outputs[0]
      in_data = naked(ctx[op.input.key])
      xps = get_sparse_module(in_data)
      xp = get_array_module(in_data)
      ctx[chunk.key] = SparseNDArray(
          xps.csr_matrix(
              (
                  xp.ones_like(in_data.data, dtype=chunk.op.dtype),
                  in_data.indices,
                  in_data.indptr,
              ),
              shape=in_data.shape,
          )
      )
  
imports: import numpy
  from ...None import opcodes
  from ...lib.sparse import SparseNDArray
  from ...lib.sparse.core import get_sparse_module, get_array_module, naked
  from ...serialization.serializables import FieldTypes, AnyField, TupleField, KeyField, StringField
  from ..array_utils import create_array, convert_order
  from ..utils import get_order
  from .core import TensorNoInput, TensorLike
  from .array import tensor
label_desc: Use image node_id 2 for calling the TensorOnesLike obj's underlying member method code with example usage: obj.execute_sparse(cls, ctx, op) without return types