173     params_.activation = static_cast<TfLiteFusedActivation>(getScalarDataWithDefault<int32_t>(  in BidirectionalSequenceLSTM()
178         params_.cell_clip = getScalarDataWithDefault<float>(clipOperand, 0.0f);  in BidirectionalSequenceLSTM()
179         params_.proj_clip = getScalarDataWithDefault<float>(projOperand, 0.0f);  in BidirectionalSequenceLSTM()
181         params_.cell_clip =  in BidirectionalSequenceLSTM()
183         params_.proj_clip =  in BidirectionalSequenceLSTM()
187     params_.merge_outputs = getScalarDataWithDefault<bool>(mergeOutputsOperand, false);  in BidirectionalSequenceLSTM()
189     params_.time_major = getScalarDataWithDefault<bool>(timeMajorOperand, false);  in BidirectionalSequenceLSTM()
190     params_.use_layer_norm = !IsNullInput(fw_input_layer_norm_weights_);  in BidirectionalSequenceLSTM()
193     if (!params_.merge_outputs) {  in BidirectionalSequenceLSTM()
197     params_.output_state = (operation.outputs.size() == 5 || operation.outputs.size() == 6);  in BidirectionalSequenceLSTM()
198     if (params_.output_state) {  in BidirectionalSequenceLSTM()
199         uint32_t delta = params_.merge_outputs ? 1 : 0;  in BidirectionalSequenceLSTM()
269     const uint32_t max_time = SizeOfDimension(input_, params_.time_major ? 0 : 1);  in Prepare()
270     const uint32_t n_batch = SizeOfDimension(input_, params_.time_major ? 1 : 0);  in Prepare()
297                 fw_output_layer_norm_weights_, n_fw_input, n_fw_output, n_fw_cell, &params_)) {  in Prepare()
301     if (params_.use_cifg) {  in Prepare()
307             ((params_.use_cifg || !IsNullInput(fw_aux_input_to_input_weights_)) &&  in Prepare()
316             ((params_.use_cifg || !IsNullInput(bw_aux_input_to_input_weights_)) &&  in Prepare()
388     fwOutputShape->dimensions[0] = params_.time_major ? max_time : n_batch;  in Prepare()
389     fwOutputShape->dimensions[1] = params_.time_major ? n_batch : max_time;  in Prepare()
390     fwOutputShape->dimensions[2] = params_.merge_outputs ? n_fw_output + n_bw_output : n_fw_output;  in Prepare()
405                 bw_output_layer_norm_weights_, n_bw_input, n_bw_output, n_bw_cell, &params_)) {  in Prepare()
409     if (!params_.merge_outputs) {  in Prepare()
414         bwOutputShape->dimensions[0] = params_.time_major ? max_time : n_batch;  in Prepare()
415         bwOutputShape->dimensions[1] = params_.time_major ? n_batch : max_time;  in Prepare()
419     if (params_.output_state) {  in Prepare()
426     if (params_.use_cifg) {  in Prepare()
472             if (params_.output_state) {  in Eval()
486                     params_, GetBuffer<const float>(input_), input_->shape(),  in Eval()
517                     GetBuffer<float>(fw_output_), fw_scratch_buffer.data(), params_.time_major,  in Eval()
524             if (params_.output_state) {  in Eval()
538                     params_, bwInput, bwInputShape,  in Eval()
569                     params_.merge_outputs ? GetBuffer<float>(fw_output_) + n_fw_output_elements  in Eval()
571                     bw_scratch_buffer.data(), params_.time_major, kBackwardSequence);  in Eval()
572             if (params_.merge_outputs) {  in Eval()
595             if (params_.output_state) {  in Eval()
610                     params_, GetBuffer<const _Float16>(input_), input_->shape(),  in Eval()
641                     GetBuffer<_Float16>(fw_output_), fw_scratch_buffer.data(), params_.time_major,  in Eval()
648             if (params_.output_state) {  in Eval()
663                     params_, bwInput, bwInputShape,  in Eval()
694                     params_.merge_outputs ? GetBuffer<_Float16>(fw_output_) + n_fw_output_elements  in Eval()
696                     bw_scratch_buffer.data(), params_.time_major, kBackwardSequence);  in Eval()
697             if (params_.merge_outputs) {  in Eval()