code: def _predict(self, input_data: InputData):
      x = self._scale(input_data.features.copy())
      x = torch.Tensor(x).to(self.device)
      predict = self.forward(x).cpu().detach().numpy()
      predict = self._inverse_scale(predict)
      return predict
  
imports: import numpy
  from golem.utilities.requirements_notificator import warn_requirement
  from fedot.core.data.data import InputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
label_desc: Use image node_id 7 for calling the CGRUImplementation obj's underlying member method code with example usage: obj._predict(input_data) and returns: predict