TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  const auto* params =
      reinterpret_cast<TfLiteUnidirectionalSequenceLSTMParams*>(
          node->builtin_data);
  const OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
  const bool use_layer_norm = op_data->use_layer_norm;
  const bool time_major = params->time_major;
  const TfLiteTensor* input;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kInputTensor, &input));

  const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kInputToInputWeightsTensor);
  const TfLiteTensor* input_to_forget_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kInputToForgetWeightsTensor,
                   &input_to_forget_weights));
  const TfLiteTensor* input_to_cell_weights;
  TF_LITE_ENSURE_OK(context, GetInputSafe(context, node,
                                          lstm::full::kInputToCellWeightsTensor,
                                          &input_to_cell_weights));
  const TfLiteTensor* input_to_output_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kInputToOutputWeightsTensor,
                   &input_to_output_weights));

  const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kRecurrentToInputWeightsTensor);
  const TfLiteTensor* recurrent_to_forget_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToForgetWeightsTensor,
                   &recurrent_to_forget_weights));
  const TfLiteTensor* recurrent_to_cell_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToCellWeightsTensor,
                   &recurrent_to_cell_weights));
  const TfLiteTensor* recurrent_to_output_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToOutputWeightsTensor,
                   &recurrent_to_output_weights));

  const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToInputWeightsTensor);
  const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToForgetWeightsTensor);
  const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToOutputWeightsTensor);

  const TfLiteTensor* input_gate_bias =
      GetOptionalInputTensor(context, node, lstm::full::kInputGateBiasTensor);
  const TfLiteTensor* forget_gate_bias;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kForgetGateBiasTensor,
                            &forget_gate_bias));
  const TfLiteTensor* cell_gate_bias;
  TF_LITE_ENSURE_OK(context,
                    GetInputSafe(context, node, lstm::full::kCellGateBiasTensor,
                                 &cell_gate_bias));
  const TfLiteTensor* output_gate_bias;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kOutputGateBiasTensor,
                            &output_gate_bias));

  const TfLiteTensor* projection_weights = GetOptionalInputTensor(
      context, node, lstm::full::kProjectionWeightsTensor);
  const TfLiteTensor* projection_bias =
      GetOptionalInputTensor(context, node, lstm::full::kProjectionBiasTensor);

  TfLiteTensor* output_state =
      GetVariableInput(context, node, lstm::full::kOutputStateTensor);
  TFLITE_DCHECK(output_state != nullptr);
  TfLiteTensor* cell_state =
      GetVariableInput(context, node, lstm::full::kCellStateTensor);
  TFLITE_DCHECK(cell_state != nullptr);

  const TfLiteTensor* input_layer_norm_coefficients =
      use_layer_norm
          ? GetOptionalInputTensor(
                context, node, lstm::full::kInputLayerNormCoefficientsTensor)
          : nullptr;
  const TfLiteTensor* forget_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kForgetLayerNormCoefficientsTensor)
                     : nullptr;
  const TfLiteTensor* cell_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kCellLayerNormCoefficientsTensor)
                     : nullptr;
  const TfLiteTensor* output_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kOutputLayerNormCoefficientsTensor)
                     : nullptr;

  TfLiteTensor* output;
  TF_LITE_ENSURE_OK(context, GetOutputSafe(context, node,
                                           lstm::full::kOutputTensor, &output));

  // Copy out the LSTM specific params so they can be passed in the function.
  TfLiteLSTMParams lstm_params;
  lstm_params.activation = params->activation;
  lstm_params.cell_clip = params->cell_clip;
  lstm_params.proj_clip = params->proj_clip;
  lstm_params.asymmetric_quantize_inputs = params->asymmetric_quantize_inputs;

  switch (input_to_output_weights->type) {
    case kTfLiteFloat32: {
      // Index the scratch buffers pointers to the global scratch buffer.
      TfLiteTensor* scratch_buffer;
      TF_LITE_ENSURE_OK(context, GetTemporarySafe(context, node, kScratchBuffer,
                                                  &scratch_buffer));
      return lstm_eval::EvalFloat(
          input, input_to_input_weights, input_to_forget_weights,
          input_to_cell_weights, input_to_output_weights,
          recurrent_to_input_weights, recurrent_to_forget_weights,
          recurrent_to_cell_weights, recurrent_to_output_weights,
          cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights,
          input_layer_norm_coefficients, forget_layer_norm_coefficients,
          cell_layer_norm_coefficients, output_layer_norm_coefficients,
          /*aux_input=*/nullptr,
          /*aux_input_to_input_weights=*/nullptr,
          /*aux_input_to_forget_weights=*/nullptr,
          /*aux_input_to_cell_weights=*/nullptr,
          /*aux_input_to_output_weights=*/nullptr, input_gate_bias,
          forget_gate_bias, cell_gate_bias, output_gate_bias,
          projection_weights, projection_bias, &lstm_params,
          /*forward_sequence=*/true, time_major,
          /*output_offset=*/0, scratch_buffer, output_state, cell_state,
          output);
    }
    case kTfLiteUInt8:
    case kTfLiteInt8: {
      const bool is_hybrid = input->type == kTfLiteFloat32;
      if (is_hybrid) {
        // Index the scratch buffers pointers to the global scratch buffer.
        TfLiteTensor* scratch_buffer;
        TF_LITE_ENSURE_OK(
            context,
            GetTemporarySafe(context, node, kScratchBuffer, &scratch_buffer));

        OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
        TfLiteTensor* row_sums;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, kRowSums, &row_sums));
        const int row_sums_size = row_sums->dims->data[0];
        return lstm_eval::EvalHybrid(
            input, input_to_input_weights,
            /*input_to_input_weights_ledger*/ nullptr, input_to_forget_weights,
            /*input_to_forget_weights_ledger*/ nullptr, input_to_cell_weights,
            /*input_to_cell_weights_ledger*/ nullptr, input_to_output_weights,
            /*input_to_output_weights_ledger*/ nullptr,
            recurrent_to_input_weights,
            /*recurrent_to_input_weights_ledger*/ nullptr,
            recurrent_to_forget_weights,
            /*recurrent_to_forget_weights_ledger*/ nullptr,
            recurrent_to_cell_weights,
            /*recurrent_to_cell_weights_ledger*/ nullptr,
            recurrent_to_output_weights,
            /*recurrent_to_output_weights_ledger*/ nullptr,
            cell_to_input_weights, cell_to_forget_weights,
            cell_to_output_weights, input_layer_norm_coefficients,
            forget_layer_norm_coefficients, cell_layer_norm_coefficients,
            output_layer_norm_coefficients,
            /*aux_input=*/nullptr,
            /*aux_input_to_input_weights=*/nullptr,
            /*aux_input_to_forget_weights=*/nullptr,
            /*aux_input_to_cell_weights=*/nullptr,
            /*aux_input_to_output_weights=*/nullptr, input_gate_bias,
            forget_gate_bias, cell_gate_bias, output_gate_bias,
            projection_weights, /*projection_weights_ledger*/ nullptr,
            projection_bias, &lstm_params,
            /*forward_sequence=*/true, time_major,
            /*output_offset=*/0, scratch_buffer,
            GetTemporary(context, node, kInputScalingFactors),
            /*aux_input_sf=*/nullptr,
            GetTemporary(context, node, kOutputStateScalingFactors),
            GetTemporary(context, node, kProductScalingFactors),
            GetTemporary(context, node, kRecoveredCellWeights),
            GetTemporary(context, node, kInputQuantized),
            /*aux_input_quantized=*/nullptr,
            GetTemporary(context, node, kOutputStateQuantized),
            GetTemporary(context, node, kCellStateQuantized), output_state,
            cell_state, GetTemporary(context, node, kAccumScratch), output,
            GetTemporary(context, node, kInputZeroPoints),
            /*aux_input_zp=*/nullptr,
            GetTemporary(context, node, kOutputStateZeroPoints), row_sums,
            row_sums_size, &op_data->compute_row_sums,
            CpuBackendContext::GetFromContext(context));
      } else {
        TfLiteTensor* scratch0;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 0, &scratch0));
        TfLiteTensor* scratch1;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 1, &scratch1));
        TfLiteTensor* scratch2;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 2, &scratch2));
        TfLiteTensor* scratch3;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 3, &scratch3));
        TfLiteTensor* scratch4;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 4, &scratch4));
        TfLiteTensor* scratch5;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 5, &scratch5));
        return lstm_eval::EvalInteger8x8_16(
            input, input_to_input_weights, input_to_forget_weights,
            input_to_cell_weights, input_to_output_weights,
            recurrent_to_input_weights, recurrent_to_forget_weights,
            recurrent_to_cell_weights, recurrent_to_output_weights,
            cell_to_input_weights, cell_to_forget_weights,
            cell_to_output_weights, input_layer_norm_coefficients,
            forget_layer_norm_coefficients, cell_layer_norm_coefficients,
            output_layer_norm_coefficients, input_gate_bias, forget_gate_bias,
            cell_gate_bias, output_gate_bias, projection_weights,
            projection_bias, &lstm_params, /*forward_sequence=*/true,
            time_major, &op_data->integer_lstm_param, output_state, cell_state,
            output, scratch0, scratch1, scratch2, scratch3, scratch4, scratch5,
            CpuBackendContext::GetFromContext(context));
      }
    }
    default:
      TF_LITE_KERNEL_LOG(context, "Type %s is not currently supported.",
                         TfLiteTypeGetName(input_to_output_weights->type));
      return kTfLiteError;
  }
}
TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
  const auto* params =
      reinterpret_cast<TfLiteUnidirectionalSequenceLSTMParams*>(
          node->builtin_data);
  const OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
  const bool use_layer_norm = op_data->use_layer_norm;
  const bool time_major = params->time_major;
  const TfLiteTensor* input;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kInputTensor, &input));

  const TfLiteTensor* input_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kInputToInputWeightsTensor);
  const TfLiteTensor* input_to_forget_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kInputToForgetWeightsTensor,
                   &input_to_forget_weights));
  const TfLiteTensor* input_to_cell_weights;
  TF_LITE_ENSURE_OK(context, GetInputSafe(context, node,
                                          lstm::full::kInputToCellWeightsTensor,
                                          &input_to_cell_weights));
  const TfLiteTensor* input_to_output_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kInputToOutputWeightsTensor,
                   &input_to_output_weights));

  const TfLiteTensor* recurrent_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kRecurrentToInputWeightsTensor);
  const TfLiteTensor* recurrent_to_forget_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToForgetWeightsTensor,
                   &recurrent_to_forget_weights));
  const TfLiteTensor* recurrent_to_cell_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToCellWeightsTensor,
                   &recurrent_to_cell_weights));
  const TfLiteTensor* recurrent_to_output_weights;
  TF_LITE_ENSURE_OK(
      context,
      GetInputSafe(context, node, lstm::full::kRecurrentToOutputWeightsTensor,
                   &recurrent_to_output_weights));

  const TfLiteTensor* cell_to_input_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToInputWeightsTensor);
  const TfLiteTensor* cell_to_forget_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToForgetWeightsTensor);
  const TfLiteTensor* cell_to_output_weights = GetOptionalInputTensor(
      context, node, lstm::full::kCellToOutputWeightsTensor);

  const TfLiteTensor* input_gate_bias =
      GetOptionalInputTensor(context, node, lstm::full::kInputGateBiasTensor);
  const TfLiteTensor* forget_gate_bias;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kForgetGateBiasTensor,
                            &forget_gate_bias));
  const TfLiteTensor* cell_gate_bias;
  TF_LITE_ENSURE_OK(context,
                    GetInputSafe(context, node, lstm::full::kCellGateBiasTensor,
                                 &cell_gate_bias));
  const TfLiteTensor* output_gate_bias;
  TF_LITE_ENSURE_OK(
      context, GetInputSafe(context, node, lstm::full::kOutputGateBiasTensor,
                            &output_gate_bias));

  const TfLiteTensor* projection_weights = GetOptionalInputTensor(
      context, node, lstm::full::kProjectionWeightsTensor);
  const TfLiteTensor* projection_bias =
      GetOptionalInputTensor(context, node, lstm::full::kProjectionBiasTensor);

  TfLiteTensor* output_state =
      GetVariableInput(context, node, lstm::full::kOutputStateTensor);
  TFLITE_DCHECK(output_state != nullptr);
  TfLiteTensor* cell_state =
      GetVariableInput(context, node, lstm::full::kCellStateTensor);
  TFLITE_DCHECK(cell_state != nullptr);

  const TfLiteTensor* input_layer_norm_coefficients =
      use_layer_norm
          ? GetOptionalInputTensor(
                context, node, lstm::full::kInputLayerNormCoefficientsTensor)
          : nullptr;
  const TfLiteTensor* forget_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kForgetLayerNormCoefficientsTensor)
                     : nullptr;
  const TfLiteTensor* cell_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kCellLayerNormCoefficientsTensor)
                     : nullptr;
  const TfLiteTensor* output_layer_norm_coefficients =
      use_layer_norm ? GetInput(context, node,
                                lstm::full::kOutputLayerNormCoefficientsTensor)
                     : nullptr;

  TfLiteTensor* output;
  TF_LITE_ENSURE_OK(context, GetOutputSafe(context, node,
                                           lstm::full::kOutputTensor, &output));

   
  TfLiteLSTMParams lstm_params;
  lstm_params.activation = params->activation;
  lstm_params.cell_clip = params->cell_clip;
  lstm_params.proj_clip = params->proj_clip;
  lstm_params.asymmetric_quantize_inputs = params->asymmetric_quantize_inputs;

  switch (input_to_output_weights->type) {
    case kTfLiteFloat32: {
       
      TfLiteTensor* scratch_buffer;
      TF_LITE_ENSURE_OK(context, GetTemporarySafe(context, node, kScratchBuffer,
                                                  &scratch_buffer));
      return lstm_eval::EvalFloat(
          input, input_to_input_weights, input_to_forget_weights,
          input_to_cell_weights, input_to_output_weights,
          recurrent_to_input_weights, recurrent_to_forget_weights,
          recurrent_to_cell_weights, recurrent_to_output_weights,
          cell_to_input_weights, cell_to_forget_weights, cell_to_output_weights,
          input_layer_norm_coefficients, forget_layer_norm_coefficients,
          cell_layer_norm_coefficients, output_layer_norm_coefficients,
           nullptr,
           nullptr,
           nullptr,
           nullptr,
           nullptr, input_gate_bias,
          forget_gate_bias, cell_gate_bias, output_gate_bias,
          projection_weights, projection_bias, &lstm_params,
           true, time_major,
           0, scratch_buffer, output_state, cell_state,
          output);
    }
    case kTfLiteUInt8:
    case kTfLiteInt8: {
      const bool is_hybrid = input->type == kTfLiteFloat32;
      if (is_hybrid) {
         
        TfLiteTensor* scratch_buffer;
        TF_LITE_ENSURE_OK(
            context,
            GetTemporarySafe(context, node, kScratchBuffer, &scratch_buffer));

        OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
        TfLiteTensor* row_sums;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, kRowSums, &row_sums));
        const int row_sums_size = row_sums->dims->data[0];
        return lstm_eval::EvalHybrid(
            input, input_to_input_weights,
              nullptr, input_to_forget_weights,
              nullptr, input_to_cell_weights,
              nullptr, input_to_output_weights,
              nullptr,
            recurrent_to_input_weights,
              nullptr,
            recurrent_to_forget_weights,
              nullptr,
            recurrent_to_cell_weights,
              nullptr,
            recurrent_to_output_weights,
              nullptr,
            cell_to_input_weights, cell_to_forget_weights,
            cell_to_output_weights, input_layer_norm_coefficients,
            forget_layer_norm_coefficients, cell_layer_norm_coefficients,
            output_layer_norm_coefficients,
             nullptr,
             nullptr,
             nullptr,
             nullptr,
             nullptr, input_gate_bias,
            forget_gate_bias, cell_gate_bias, output_gate_bias,
            projection_weights,   nullptr,
            projection_bias, &lstm_params,
             true, time_major,
             0, scratch_buffer,
            GetTemporary(context, node, kInputScalingFactors),
             nullptr,
            GetTemporary(context, node, kOutputStateScalingFactors),
            GetTemporary(context, node, kProductScalingFactors),
            GetTemporary(context, node, kRecoveredCellWeights),
            GetTemporary(context, node, kInputQuantized),
             nullptr,
            GetTemporary(context, node, kOutputStateQuantized),
            GetTemporary(context, node, kCellStateQuantized), output_state,
            cell_state, GetTemporary(context, node, kAccumScratch), output,
            GetTemporary(context, node, kInputZeroPoints),
             nullptr,
            GetTemporary(context, node, kOutputStateZeroPoints), row_sums,
            row_sums_size, &op_data->compute_row_sums,
            CpuBackendContext::GetFromContext(context));
      } else {
        TfLiteTensor* scratch0;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 0, &scratch0));
        TfLiteTensor* scratch1;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 1, &scratch1));
        TfLiteTensor* scratch2;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 2, &scratch2));
        TfLiteTensor* scratch3;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 3, &scratch3));
        TfLiteTensor* scratch4;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 4, &scratch4));
        TfLiteTensor* scratch5;
        TF_LITE_ENSURE_OK(context,
                          GetTemporarySafe(context, node, 5, &scratch5));
        return lstm_eval::EvalInteger8x8_16(
            input, input_to_input_weights, input_to_forget_weights,
            input_to_cell_weights, input_to_output_weights,
            recurrent_to_input_weights, recurrent_to_forget_weights,
            recurrent_to_cell_weights, recurrent_to_output_weights,
            cell_to_input_weights, cell_to_forget_weights,
            cell_to_output_weights, input_layer_norm_coefficients,
            forget_layer_norm_coefficients, cell_layer_norm_coefficients,
            output_layer_norm_coefficients, input_gate_bias, forget_gate_bias,
            cell_gate_bias, output_gate_bias, projection_weights,
            projection_bias, &lstm_params,  true,
            time_major, &op_data->integer_lstm_param, output_state, cell_state,
            output, scratch0, scratch1, scratch2, scratch3, scratch4, scratch5,
            CpuBackendContext::GetFromContext(context));
      }
    }
    default:
      TF_LITE_KERNEL_LOG(context, "Type %s is not currently supported.",
                         TfLiteTypeGetName(input_to_output_weights->type));
      return kTfLiteError;
  }
}