code: def _np_conv_ok(volume, kernel, mode):
      """
      See if numpy supports convolution of `volume` and `kernel` (i.e. both are
      1D ndarrays and of the appropriate shape).  NumPy's 'same' mode uses the
      size of the larger input, while SciPy's uses the size of the first input.
  
      Invalid mode strings will return False and be caught by the calling func.
      """
      if volume.ndim == kernel.ndim == 1:
          if mode in ("full", "valid"):
              return True
          elif mode == "same":
              return volume.size >= kernel.size
      else:
          return False
  
imports: import operator
  import math
  import timeit
  from scipy.spatial import cKDTree
  from .None import sigtools, dlti
  from ._upfirdn import upfirdn, _output_len, _upfirdn_modes
  from scipy import linalg, fft
  from scipy.fft._helper import _init_nd_shape_and_axes
  from scipy._lib._util import prod
  import numpy
  from scipy.special import lambertw
  from .windows import get_window
  from ._arraytools import axis_slice, axis_reverse, odd_ext, even_ext, const_ext
  from .filter_design import cheby1, _validate_sos
  from .fir_filter_design import firwin
  from ._sosfilt import _sosfilt
  import warnings
label_desc: Use image node_id 17 for calling a global function with example usage: _np_conv_ok(volume, kernel, mode) and returns: False, True, unknown