text: /* file: decision_tree_classification_train_container_v1.h */
  /*******************************************************************************
  * Copyright 2014-2021 Intel Corporation
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
  *
  *     http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
  *******************************************************************************/
  
  /*
  //++
  //  Implementation of K-Nearest Neighbors container.
  //--
  */
  
  #ifndef __DECISION_TREE_CLASSIFICATION_TRAIN_CONTAINER_V1_H__
  #define __DECISION_TREE_CLASSIFICATION_TRAIN_CONTAINER_V1_H__
  
  #include "src/algorithms/kernel.h"
  #include "data_management/data/numeric_table.h"
  #include "services/daal_shared_ptr.h"
  #include "algorithms/decision_tree/decision_tree_classification_training_batch.h"
  #include "src/algorithms/decision_tree/decision_tree_classification_train_kernel.h"
  #include "src/algorithms/decision_tree/decision_tree_classification_model_impl.h"
  
  namespace daal
  {
  namespace algorithms
  {
  namespace decision_tree
  {
  namespace classification
  {
  namespace training
  {
  namespace interface1
  {
  using namespace daal::data_management;
  
  /**
   *  \brief Initialize list of Decision tree kernels with implementations for supported architectures
   */
  template <typename algorithmFPType, training::Method method, CpuType cpu>
  BatchContainer<algorithmFPType, method, cpu>::BatchContainer(daal::services::Environment::env * daalEnv)
  {
      __DAAL_INITIALIZE_KERNELS(internal::DecisionTreeTrainBatchKernel, algorithmFPType, decision_tree::classification::interface1::Parameter, method);
  }
  
  template <typename algorithmFPType, training::Method method, CpuType cpu>
  BatchContainer<algorithmFPType, method, cpu>::~BatchContainer()
  {
      __DAAL_DEINITIALIZE_KERNELS();
  }
  
  /**
   *  \brief Choose appropriate kernel to calculate Decision tree model.
   */
  template <typename algorithmFPType, training::Method method, CpuType cpu>
  services::Status BatchContainer<algorithmFPType, method, cpu>::compute()
  {
      const decision_tree::classification::training::Input * const input = static_cast<decision_tree::classification::training::Input *>(_in);
      Result * const result                                              = static_cast<Result *>(_res);
  
      const NumericTableConstPtr x  = input->get(classifier::training::data);
      const NumericTableConstPtr y  = input->get(classifier::training::labels);
      const NumericTableConstPtr px = input->get(dataForPruning);
      const NumericTableConstPtr py = input->get(labelsForPruning);
  
      const ModelPtr r = result->get(classifier::training::model);
  
      const decision_tree::classification::interface1::Parameter * const par =
          static_cast<decision_tree::classification::interface1::Parameter *>(_par);
      daal::services::Environment::env & env = *_env;
  
      __DAAL_CALL_KERNEL(env, internal::DecisionTreeTrainBatchKernel,
                         __DAAL_KERNEL_ARGUMENTS(algorithmFPType, decision_tree::classification::interface1::Parameter, method), compute, x.get(),
                         y.get(), 0, px.get(), py.get(), r.get(), par);
  }
  } // namespace interface1
  } // namespace training
  } // namespace classification
  } // namespace decision_tree
  } // namespace algorithms
  } // namespace daal
  
  #endif
  