text: /* file: linear_model_predict_container.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 linear regression algorithm container -- a class
  //  that contains fast linear regression prediction kernels
  //  for supported architectures.
  //--
  */
  
  #ifndef __LINEAR_MODEL_PREDICT_CONTAINER_H__
  #define __LINEAR_MODEL_PREDICT_CONTAINER_H__
  
  #include "algorithms/linear_model/linear_model_predict.h"
  #include "src/algorithms/linear_model/linear_model_predict_kernel.h"
  
  #include "src/algorithms/linear_model/oneapi/linear_model_predict_kernel_oneapi.h"
  
  namespace daal
  {
  namespace algorithms
  {
  namespace linear_model
  {
  namespace prediction
  {
  template <typename algorithmFPType, Method method, CpuType cpu>
  BatchContainer<algorithmFPType, method, cpu>::BatchContainer(daal::services::Environment::env * daalEnv) : PredictionContainerIface()
  {
      auto & context    = services::internal::getDefaultContext();
      auto & deviceInfo = context.getInfoDevice();
  
      if (deviceInfo.isCpu)
      {
          __DAAL_INITIALIZE_KERNELS(internal::PredictKernel, algorithmFPType, method);
      }
      else
      {
          __DAAL_INITIALIZE_KERNELS_SYCL(internal::PredictKernelOneAPI, algorithmFPType, method);
      }
  }
  
  template <typename algorithmFPType, Method method, CpuType cpu>
  BatchContainer<algorithmFPType, method, cpu>::~BatchContainer()
  {
      __DAAL_DEINITIALIZE_KERNELS();
  }
  
  template <typename algorithmFPType, Method method, CpuType cpu>
  services::Status BatchContainer<algorithmFPType, method, cpu>::compute()
  {
      Input * input   = static_cast<Input *>(_in);
      Result * result = static_cast<Result *>(_res);
  
      NumericTable * a        = static_cast<NumericTable *>(input->get(data).get());
      linear_model::Model * m = static_cast<linear_model::Model *>(input->get(model).get());
      NumericTable * r        = static_cast<NumericTable *>(result->get(prediction).get());
  
      daal::services::Environment::env & env = *_env;
  
      auto & context    = services::internal::getDefaultContext();
      auto & deviceInfo = context.getInfoDevice();
  
      if (deviceInfo.isCpu)
      {
          __DAAL_CALL_KERNEL(env, internal::PredictKernel, __DAAL_KERNEL_ARGUMENTS(algorithmFPType, method), compute, a, m, r);
      }
      else
      {
          __DAAL_CALL_KERNEL_SYCL(env, internal::PredictKernelOneAPI, __DAAL_KERNEL_ARGUMENTS(algorithmFPType, method), compute, a, m, r)
      }
  }
  
  } // namespace prediction
  } // namespace linear_model
  } // namespace algorithms
  } // namespace daal
  #endif
  