//===----------------------------------------------------------------------===//
// LSTMOp
//===----------------------------------------------------------------------===//

mlir::LogicalResult LSTMOp::verify() {
  LSTMOp op = *this;
  auto operands = op.GetStatefulOperands();
  if (operands.size() != 2 || operands[0] != 18 || operands[1] != 19) {
    return op.emitOpError("LSTMOp expected to have two stateful operands");
  }

    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",