code: def conv3d_ndhwc_python(a_np, w_np, stride, padding, groups=1):
      """Convolution 3D operator in NDHWC layout.
  
      Parameters
      ----------
      a_np : numpy.ndarray
          5-D with shape [batch, in_channel, in_depth, in_height, in_width]
  
      w_np : numpy.ndarray
          5-D with shape [num_filter, in_channel, filter_depth, filter_height, filter_width]
  
      stride : int or a list/tuple of three ints
          Stride size, or [stride_depth, stride_height, stride_width]
  
      padding : int or str or a list/tuple of three ints
          Padding size, or ['VALID', 'SAME'], or [pad_depth, pad_height, pad_width]
  
      groups : int
          Number of groups
  
      Returns
      -------
      b_np : np.ndarray
          5-D with shape [batch, out_channel, out_depth, out_height, out_width]
      """
      a_slices = np.array_split(a_np, groups, axis=4)
      w_slices = np.array_split(w_np, groups, axis=4)
      b_slices = [
          _conv3d_ndhwc_python(a_slice, w_slice, stride, padding)
          for a_slice, w_slice in zip(a_slices, w_slices)
      ]
      b_np = np.concatenate(b_slices, axis=4)
      return b_np
  
imports: import numpy
  import scipy.signal
  from tvm.topi.nn.utils import get_pad_tuple3d
label_desc: Use image node_id 2 for calling a global function with example usage: conv3d_ndhwc_python(a_np, w_np, stride, padding, groups) and returns: b_np