// [1, num_rows, num_cols] -> [num_rows, num_cols]
    auto reshape_op = createReshapeOp(value, {num_rows, num_cols}, element_type,
                                      loc, rewriter);
    sliced.emplace_back(reshape_op.getOutput());
  } else {
    // Reshape to rank-3 tensor with first dimension as the batch size.
    auto reshape_op = createReshapeOp(value, {batch_size, num_rows, num_cols},

  return rewriter->create<TF::TransposeOp>(loc, transposed_type, value,
                                           perm_op);
}

TF::ReshapeOp createReshapeOp(Value value, ArrayRef<int64_t> shape,
                              Type element_type, Location loc,
                              PatternRewriter* rewriter) {
  auto shape_tensor = createI64ConstantOp(