code: def _coo_matvec_abstract_eval(
      data, row, col, v, *, spinfo, transpose
  ):
      assert data.shape == row.shape == col.shape
      assert data.dtype == v.dtype
      assert row.dtype == col.dtype
      assert len(spinfo.shape) == 2
      assert v.ndim == 1
      assert v.shape[0] == (
          spinfo.shape[0] if transpose else spinfo.shape[1]
      )
      out_shape = spinfo.shape[1] if transpose else spinfo.shape[0]
      return core.ShapedArray((out_shape,), data.dtype)
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from functools import partial
  import operator
  from typing import Any, NamedTuple
  import warnings
  import numpy
  import jax
  from jax import lax
  from jax.interpreters import mlir
  from jax.experimental.sparse._base import JAXSparse
  from jax.experimental.sparse.util import _coo_extract, CuSparseEfficiencyWarning
  from jax import tree_util
  from jax._src import core
  from jax._src import dispatch
  from jax._src.interpreters import ad
  from jax._src.lax.lax import _const
  from jax._src.lib.mlir.dialects import hlo
  from jax._src.lib import gpu_sparse
  from jax._src.numpy.util import promote_dtypes
  from jax._src.typing import Array, ArrayLike, DTypeLike
  import jax.numpy
label_desc: Use image node_id 18 for calling a global function with example usage: _coo_matvec_abstract_eval(data, row, col, v) and returns: core