target.addDynamicallyLegalOp<TF::TensorListSetItemOp>(is_set_item_legal);
  target.addLegalOp<TFL::CustomOp>();
  // Register fused LSTM/RNN ops as legal.
  target.addLegalOp<TFL::LSTMOp>();
  target.addLegalOp<TFL::UnidirectionalSequenceLSTMOp>();
  target.addLegalOp<TFL::UnidirectionalSequenceRNNOp>();
  target.addLegalOp<TFL::BidirectionalSequenceLSTMOp>();

    unrolling the input along the time or batch dimensions, and
    implements the following operation for
    each element in the sequence s = 1...sequence_length:
      outputs[s] = state = activation(LSTMOp(inputs[s]))

    where LSTMOp is LSTM TF Lite Op and the “activation” is the function passed
    as the “fused_activation_function” argument (if not “NONE”).
  }];

  let arguments = (
    ins TFL_FpTensor:$input,

      continue;
    }
    std::vector<int32_t> intermediates;
    // Build intermediate tensors for tfl.lstm and insert these tensors into
    // flatbuffer.
    if (llvm::isa<mlir::TFL::LSTMOp, mlir::TFL::UnidirectionalSequenceLSTMOp>(
            inst)) {
      std::vector<std::string> intermediate_names = {
          "input_to_input_intermediate", "input_to_forget_intermediate",