text: /**
   * Copyright 2020 Huawei Technologies Co., Ltd
   *
   * 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 "kernel/cpu/slice_cpu_kernel.h"
  #include "device/cpu/cpu_device_address.h"
  #include "ir/primitive.h"
  
  namespace mindspore {
  namespace kernel {
  void SliceCPUKernel::InitKernel(const CNodePtr &kernel_node) {
    CheckParam(kernel_node);
    input_shape_ = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
    output_shape_ = AnfAlgo::GetOutputInferShape(kernel_node, 0);
  
    begin_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, BEGIN);
    for (size_t i = 0; i < begin_.size(); i++) {
      if (begin_[i] < 0) {
        begin_[i] = begin_[i] + input_shape_[i];
      }
    }
    auto prim = AnfAlgo::GetCNodePrimitive(kernel_node);
    MS_EXCEPTION_IF_NULL(prim);
    auto strides = prim->GetAttr(STRIDES);
    if (strides != nullptr) {
      strides_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, STRIDES);
      end_ = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, END);
      if (strides_.size() != end_.size() || strides_.size() != input_shape_.size()) {
        MS_LOG(EXCEPTION) << "stride|end|input size must be equal";
      }
      for (size_t i = 0; i < strides_.size(); ++i) {
        if (strides_[i] < 0) {
          strides_[i] = (strides_[i] + input_shape_[i]) > 0 ? (strides_[i] + input_shape_[i]) : 0;
        }
        if (end_[i] < 0) {
          end_[i] = (end_[i] + input_shape_[i]) > 0 ? (end_[i] + input_shape_[i]) : 0;
        }
      }
    } else {
      auto sizes = AnfAlgo::GetNodeAttr<std::vector<int>>(kernel_node, SIZE);
      if (sizes.size() != input_shape_.size() || begin_.size() != input_shape_.size()) {
        MS_LOG(EXCEPTION) << "begin|size|input size must be equal";
      }
      for (size_t i = 0; i < sizes.size(); ++i) {
        if (sizes[i] < 0) {
          sizes[i] = (sizes[i] + input_shape_[i]) > 0 ? (sizes[i] + input_shape_[i]) : 0;
        }
        strides_.emplace_back(1);
        end_.emplace_back(begin_[i] + sizes[i]);
      }
    }
  
    ExpandAllMemberDims();
    CPUKernelUtils::GetElementNumEveryDim(input_shape_, &input_element_num_);
    CPUKernelUtils::GetElementNumEveryDim(output_shape_, &output_element_num_);
  }
  
  void SliceCPUKernel::ExpandAllMemberDims() {
    CPUKernelUtils::ExpandDimsTo4(&output_shape_);
  
    auto input_len = input_shape_.size();
    if (input_len < 4) {
      for (size_t i = 0; i < 4 - input_len; ++i) {
        input_shape_.insert(input_shape_.begin(), 1);
        begin_.insert(begin_.begin(), 0);
        strides_.insert(strides_.begin(), 1);
        end_.insert(end_.begin(), 1);
      }
    }
  }
  
  bool SliceCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
                              const std::vector<kernel::AddressPtr> & /*workspace*/,
                              const std::vector<kernel::AddressPtr> &outputs) {
    auto input_addr = reinterpret_cast<float *>(inputs[0]->addr);
    auto output_addr = reinterpret_cast<float *>(outputs[0]->addr);
  
    bool can_copy_memory[3] = {CanCopyMemoryOnAxis(0), CanCopyMemoryOnAxis(1), CanCopyMemoryOnAxis(2)};
    size_t in_start_offset[3] = {begin_[0] * input_element_num_[0], begin_[1] * input_element_num_[1],
                                 begin_[2] * input_element_num_[2]};
    size_t in_step_size[3] = {strides_[0] * input_element_num_[0], strides_[1] * input_element_num_[1],
                              strides_[2] * input_element_num_[2]};
  
    auto in_n_offset = in_start_offset[0];
    auto out_n_offset = 0;
    for (int i = begin_[0]; i < end_[0];
         i += strides_[0], in_n_offset += in_step_size[0], out_n_offset += output_element_num_[0]) {
      if (can_copy_memory[0]) {
        CopyDataToOutput(inputs, in_n_offset, outputs, out_n_offset, input_element_num_[0]);
        continue;
      }
      auto in_c_offset = in_start_offset[1];
      auto out_c_offset = 0;
      for (int j = begin_[1]; j < end_[1];
           j += strides_[1], in_c_offset += in_step_size[1], out_c_offset += output_element_num_[1]) {
        if (can_copy_memory[1]) {
          CopyDataToOutput(inputs, in_n_offset + in_c_offset, outputs, out_n_offset + out_c_offset,
                           input_element_num_[1]);
          continue;
        }
        auto in_h_offset = in_start_offset[2];
        auto out_h_offset = 0;
        for (int k = begin_[2]; k < end_[2];
             k += strides_[2], in_h_offset += in_step_size[2], out_h_offset += output_element_num_[2]) {
          if (can_copy_memory[2]) {
            CopyDataToOutput(inputs, in_n_offset + in_c_offset + in_h_offset, outputs,
                             out_n_offset + out_c_offset + out_h_offset, input_element_num_[2]);
            continue;
          }
          for (int m = begin_[3]; m < end_[3]; m += strides_[3]) {
            *output_addr++ = input_addr[in_n_offset + in_c_offset + in_h_offset + m];
          }
        }
      }
    }
  
    return true;
  }
  
  bool SliceCPUKernel::CanCopyMemoryOnAxis(size_t dim) const {
    for (size_t i = dim + 1; i < 4; ++i) {
      if (begin_[i] != 0 || end_[i] != SizeToInt(input_shape_[i]) || strides_[i] != 1) {
        return false;
      }
    }
    return true;
  }
  
  void SliceCPUKernel::CopyDataToOutput(const std::vector<kernel::AddressPtr> &inputs, size_t in_offset,
                                        const std::vector<kernel::AddressPtr> &outputs, size_t out_offset,
                                        size_t copy_num) const {
    auto input_addr = reinterpret_cast<float *>(inputs[0]->addr);
    auto in_buff_size = inputs[0]->size;
    auto output_addr = reinterpret_cast<float *>(outputs[0]->addr);
    auto out_buff_size = outputs[0]->size;
  
    if ((in_offset + copy_num) * sizeof(float) > in_buff_size) {
      MS_LOG(EXCEPTION) << "input memory out of bounds.";
    }
    if ((out_offset + copy_num) * sizeof(float) > out_buff_size) {
      MS_LOG(EXCEPTION) << "output memory out of bounds.";
    }
  
    auto ret = memcpy_s(output_addr + out_offset, out_buff_size - out_offset * sizeof(float), input_addr + in_offset,
                        copy_num * sizeof(float));
    if (ret != EOK) {
      MS_LOG(EXCEPTION) << "memcpy failed. ret:" << ret;
    }
  }
  
  void SliceCPUKernel::CheckParam(const CNodePtr &kernel_node) const {
    size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
    if (input_num != 1) {
      MS_LOG(EXCEPTION) << "Input number is " << input_num << ", but SliceCPUKernel needs 1 inputs.";
    }
    size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
    if (output_num != 1) {
      MS_LOG(EXCEPTION) << "Output number is " << output_num << ", but SliceCPUKernel needs 1 output.";
    }
    auto input_shape = AnfAlgo::GetPrevNodeOutputInferShape(kernel_node, 0);
    if (input_shape.size() > 4) {
      MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", but SliceCPUKernel olny support 4d or lower.";
    }
    if (input_shape.size() == 0) {
      MS_LOG(EXCEPTION) << "Input dims is " << input_shape.size() << ", scalar is not supported.";
    }
  }
  }  // namespace kernel
  }  // namespace mindspore
  