code: def _check_conv_inputs(in1, in2, mode, convolution=True):
      if in1.ndim == in2.ndim == 0:
          return in1 * (in2 if convolution else in2.conj())
      if in1.ndim != in2.ndim:
          raise ValueError(
              "in1 and in2 should have the same dimensionality"
          )
      if in1.size == 0 or in2.size == 0:
          return cupy.array([], dtype=in1.dtype)
      if mode not in ("full", "same", "valid"):
          raise ValueError(
              'acceptable modes are "valid", "same", or "full"'
          )
      return None
  
file_path: cupy/cupyx/scipy/signal/_signaltools_core.py
imports: import math
  import cupy
  from cupy._core import internal
  from cupyx.scipy import fft
  from cupyx.scipy.ndimage import _filters
  from cupyx.scipy.ndimage import _util
label_desc: Use image node_id 1 for calling a global function with example usage: _check_conv_inputs(in1, in2, mode, convolution) and returns: None, unknown, cupy