code: def conv1d_transpose_ncw(
      data, kernel, stride, padding, out_dtype, output_padding
  ):
      """Transposed 1D convolution ncw forward operator.
  
      Parameters
      ----------
      data : tvm.te.Tensor
          3-D with shape [batch, in_channel, in_width]
  
      kernel : tvm.te.Tensor
          3-D with shape [in_channel, num_filter, filter_width]
  
      stride : ints
          The spatial stride along width
  
      padding : int or str
          Padding size, or ['VALID', 'SAME']
  
      out_dtype : str
          The output data type. This is used for mixed precision.
  
      output_padding : ints
          Used to recover the actual output shape in case there are more
          than one possible shape.  Must be smaller than stride.
  
      Returns
      -------
      output : tvm.te.Tensor
          3-D with shape [batch, out_channel, out_width]
  
      """
  
      batch, channels_in, _ = data.shape
      _, channels_out, kernel_width = kernel.shape
  
      data_pad, transformed_kernel = _conv1d_transpose_ncw_preprocess(
          data, kernel, stride, padding, out_dtype, output_padding
      )
  
      # convolution
      _, _, data_width = data_pad.shape
      out_w = simplify(data_width - kernel_width + 1)
      dc = te.reduce_axis((0, channels_in), name="dc")
      dw = te.reduce_axis((0, kernel_width), name="dw")
      output = te.compute(
          (batch, channels_out, out_w),
          lambda b, c, w: te.sum(
              data_pad[b, dc, w + dw].astype(out_dtype)
              * transformed_kernel[c, dc, dw].astype(out_dtype),
              axis=[dc, dw],
          ),
          tag="conv1d_transpose_ncw",
      )
  
      return output
  
file_path: tvm/python/tvm/topi/nn/conv1d_transpose.py
imports: from tvm import te
  from .dilate import dilate
  from .pad import pad
  from ..utils import simplify
  from .utils import get_pad_tuple1d
label_desc: Use image node_id 2 for calling a global function with example usage: conv1d_transpose_ncw(data, kernel, stride, padding, out_dtype, output_padding) and returns: output