code: def conv3d_transpose_ncdhw(
      Input, Filter, strides, padding, out_dtype, output_padding
  ):
      """Transposed 3D convolution ncdhw forward operator.
  
      Parameters
      ----------
      Input : tvm.te.Tensor
          5-D with shape [batch, in_channel, in_depth, in_height, in_width]
  
      Filter : tvm.te.Tensor
          5-D with shape [in_channel, num_filter, filter_depth, filter_height, filter_width]
  
      strides : int or a list/tuple of three ints
          The spatial stride along depth,height and 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 : tuple of ints
          Used to get the right output shape for gradients
  
      Returns
      -------
      Output : tvm.te.Tensor
          5-D with shape [batch, out_channel, out_depth, out_height, out_width]
      """
      return declaration_conv3d_transpose_impl(
          Input, Filter, strides, padding, out_dtype, output_padding
      )
  
file_path: tvm/python/tvm/topi/nn/conv3d_transpose.py
imports: import tvm
  from tvm import te
  from tvm import relay
  from .dilate import dilate
  from .pad import pad
  from .utils import get_pad_tuple3d
  from ..utils import simplify
label_desc: Use image node_id 1 for calling a global function with example usage: conv3d_transpose_ncdhw(Input, Filter, strides, padding, out_dtype, output_padding) and returns: declaration_conv3d_transpose_impl