code: def group_conv1d_ncw(
      data,
      kernel,
      strides=1,
      padding="VALID",
      dilation=1,
      groups=1,
      out_dtype=None,
  ):
      """1D convolution forward operator for NCW layout.
  
      Parameters
      ----------
      data : tvm.te.Tensor
          3-D with shape [batch, in_channel, in_width]
  
      kernel : tvm.te.Tensor
          3-D with shape [num_filter, in_channel, filter_size]
  
      strides : int or tuple
          The spatial stride along width
  
      padding : int, tuple, or str
          Padding size can be an integer for equal padding,
          a tuple of (left, right) or a string in ['VALID', 'SAME'].
  
      dilation : int or tuple
          Dilation rate if convolution should be dilated.
  
      groups : int
          Number of groups
  
      out_dtype : str
          The output data type. If None then output is same type as input.
      """
      return conv(
          data,
          kernel,
          strides,
          padding,
          dilation,
          groups,
          "NCW",
          "OIW",
          out_dtype=out_dtype,
      )
  
imports: from .conv2d import conv
label_desc: Use image node_id 5 for calling a global function with example usage: group_conv1d_ncw(data, kernel, strides, padding, dilation, groups, out_dtype) and returns: conv