{"IfMsghdr.Msglen", Field, 0},
		{"IfMsghdr.Pad1", Field, 2},
		{"IfMsghdr.Pad2", Field, 2},
		{"IfMsghdr.Pad_cgo_0", Field, 0},
		{"IfMsghdr.Pad_cgo_1", Field, 2},
		{"IfMsghdr.Tableid", Field, 2},
		{"IfMsghdr.Type", Field, 0},
		{"IfMsghdr.Version", Field, 0},
		{"IfMsghdr.Xflags", Field, 2},
		{"IfaMsghdr", Type, 0},
		{"IfaMsghdr.Addrs", Field, 0},
		{"IfaMsghdr.Flags", Field, 0},

step.

The tensors at corresponding positions in the three input lists
must have the same shape, i.e. rank 1 with dim_size() equal to the total
number of lookups into the table described by the corresponding table_id.
  }];

  let arguments = (ins
    Arg<Variadic<TF_I32OrI64Tensor>, [{A list of rank 1 Tensors specifying the training example and
feature to which the corresponding embedding_indices and aggregation_weights