GatherND.cpp

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/*
 * Copyright (c) 2024 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright 2021 The TensorFlow Authors. All Rights Reserved.
 *
 * 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.
 */
 
#include "OMStatus.h"
 
#include "core/OMUtils.h"
#include "import/OMKernelConfigureBuilder.h"
#include "execute/OMRuntimeKernel.h"
#include "PALGatherND.h"
 
using namespace onert_micro;
using namespace onert_micro::core;
using namespace onert_micro::execute;
 
namespace
{
 
constexpr uint32_t inputTensorIdx = 0;
constexpr uint32_t positionsTensorIdx = 1;
constexpr uint32_t outputTensorIdx = 0;
 
} // namespace
 
namespace onert_micro
{
namespace import
{
 
OMStatus configure_kernel_CircleGatherND(const OMConfigureArgs &config_args)
{
 
  OMRuntimeContext &runtime_context = config_args.runtime_context;
  uint16_t op_index = config_args.kernel_index;
 
  onert_micro::execute::OMRuntimeKernel runtime_kernel;
 
  OMStatus status = runtime_kernel.readKernel(op_index, runtime_context);
  if (status != Ok)
    return status;
 
  const circle::Tensor *input = runtime_kernel.inputs[inputTensorIdx];
  const circle::Tensor *positions = runtime_kernel.inputs[positionsTensorIdx];
  const circle::Tensor *output = runtime_kernel.outputs[outputTensorIdx];
 
  assert(input != nullptr);
  assert(positions != nullptr);
  assert(output != nullptr);
 
  status = utils::checkCondition(input->type() == output->type());
  if (status != Ok)
    return status;
 
  status = utils::checkCondition(positions->type() == circle::TensorType_INT32);
  if (status != Ok)
    return status;
 
  auto input_type = input->type();
  status = utils::checkCondition(input_type == circle::TensorType_FLOAT32);
  if (status != Ok)
    return status;
 
  core::OMRuntimeShape input_shape(input);
  core::OMRuntimeShape positions_shape(positions);
 
  int32_t shape_num_dims = input_shape.dimensionsCount();
 
  status = utils::checkCondition(shape_num_dims >= 1);
  if (status != Ok)
    return status;
 
  int32_t positions_num_dims = positions_shape.dimensionsCount();
  int32_t positions_num_dims_nd = positions_shape.dims(positions_num_dims - 1);
 
  status = utils::checkCondition(positions_num_dims >= 1);
  if (status != Ok)
    return status;
 
  status = utils::checkCondition(positions_num_dims_nd <= shape_num_dims);
  if (status != Ok)
    return status;
 
  status =
    utils::checkCondition(positions_num_dims_nd <= onert_micro::execute::pal::MAX_INDICES_ND);
  if (status != Ok)
    return status;
 
  return Ok;
}
 
} // namespace import
} // namespace onert_micro