Function IsHybridOperator

tensorflow/lite/delegates/nnapi/nnapi_delegate.cc:224–270

}

bool IsHybridOperator(const TfLiteContext* context, int builtin_code,
                      const TfLiteNode* node) {
  switch (builtin_code) {
    case kTfLiteBuiltinConv2d:
    case kTfLiteBuiltinFullyConnected: {
      const int input_id = node->inputs->data[0];
      const int filter_id = node->inputs->data[1];
      const TfLiteType input_type = context->tensors[input_id].type;
      const TfLiteType filter_type = context->tensors[filter_id].type;
      return IsFloat(input_type) && IsQuantized(filter_type);
    }
    case kTfLiteBuiltinLstm: {
      const int input_id = node->inputs->data[0];
      // Input #1 is optional so use #2 to determine if hybrid.
      const int weights_id = node->inputs->data[2];
      const TfLiteType input_type = context->tensors[input_id].type;
      const TfLiteType weights_type = context->tensors[weights_id].type;
      return isLstmFullKernel(node) && IsFloat(input_type) &&
             IsQuantized(weights_type);
    }
    case kTfLiteBuiltinUnidirectionalSequenceLstm: {
      const int input_id = node->inputs->data[0];
      // Input #1 is optional so use #2 to determine if hybrid.
      const int weights_id = node->inputs->data[2];
      const TfLiteType input_type = context->tensors[input_id].type;
      const TfLiteType weights_type = context->tensors[weights_id].type;
      return IsFloat(input_type) && IsQuantized(weights_type);
    }
    case kTfLiteBuiltinBidirectionalSequenceLstm: {
      const int input_id = node->inputs->data[0];
      // Input #1 is optional so use #2 to determine if hybrid.
      const int weights_id = node->inputs->data[2];
      const TfLiteType input_type = context->tensors[input_id].type;
      const TfLiteType weights_type = context->tensors[weights_id].type;
      return IsFloat(input_type) && IsQuantized(weights_type);
    }
    case kTfLiteBuiltinUnidirectionalSequenceRnn: {
      const int input_id = node->inputs->data[0];
      const int weights_id = node->inputs->data[1];
      const TfLiteType input_type = context->tensors[input_id].type;
      const TfLiteType weights_type = context->tensors[weights_id].type;
      return IsFloat(input_type) && IsQuantized(weights_type);
    }
    default:
      return false;
  }
}

// When using NN API version 1.0 or 1.1, the condition below must be true for
// quantized versions of the following ops: