mindspore2022/mindspore/ccsrc/device/cpu/kernel_select_cpu.cc

/**
 * 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 "device/cpu/kernel_select_cpu.h"

#include <string>
#include <memory>
#include <algorithm>

#include "kernel/cpu/cpu_kernel_factory.h"

namespace mindspore {
namespace device {
namespace cpu {
using AnfAlgo = mindspore::session::AnfRuntimeAlgorithm;
using mindspore::kernel::KernelBuildInfo;
namespace {
bool IsInputNotCNode(const CNodePtr &kernel_node, size_t input_index) {
  auto input_node = AnfAlgo::VisitKernel(kernel_node->input(input_index + 1), 0).first;
  MS_EXCEPTION_IF_NULL(input_node);
  if (input_node->isa<Parameter>() || input_node->isa<ValueNode>()) {
    return true;
  }
  return false;
}

void UpdatePrevNotCNodeFormatDtype(const KernelAttr &kernel_attr, const std::vector<size_t> &input_not_cnode_indexes,
                                   const CNodePtr kernel_node) {
  for (auto &input_index : input_not_cnode_indexes) {
    auto input_node = AnfAlgo::VisitKernel(kernel_node->input(input_index + 1), 0).first;
    MS_EXCEPTION_IF_NULL(input_node);
    std::vector<TypeId> output_types;
    output_types.emplace_back(kernel_attr.GetInputAttr(input_index).first);
    auto builder = std::make_shared<kernel::KernelBuildInfo::KernelBuildInfoBuilder>();
    MS_EXCEPTION_IF_NULL(builder);
    builder->SetOutputsFormat({kOpFormat_DEFAULT});
    builder->SetOutputsDeviceType(output_types);
    AnfAlgo::SetSelectKernelBuildInfo(builder->Build(), input_node.get());
  }
}

void GetInputFormatsAndDtypes(const CNodePtr &kernel_node, std::vector<std::string> *input_formats,
                              std::vector<TypeId> *input_types, std::vector<size_t> *input_no_cnode_indexes) {
  size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
  for (size_t input_index = 0; input_index < input_num; ++input_index) {
    TypeId dtype = kTypeUnknown;
    if (IsInputNotCNode(kernel_node, input_index)) {
      input_no_cnode_indexes->emplace_back(input_index);
      dtype = AnfAlgo::GetPrevNodeOutputInferDataType(kernel_node, input_index);
    } else {
      dtype = AnfAlgo::GetPrevNodeOutputDeviceDataType(kernel_node, input_index);
    }
    input_formats->emplace_back(kOpFormat_DEFAULT);
    input_types->emplace_back(dtype);
  }
}

void GetOutputFormatsAndDtypes(const CNodePtr &kernel_node, const KernelAttr &kernel_attr,
                               std::vector<std::string> *output_formats, std::vector<TypeId> *output_types) {
  size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
  for (size_t output_index = 0; output_index < output_num; ++output_index) {
    output_formats->emplace_back(kernel_attr.GetOutputAttr(output_index).second);
    auto dtype = kernel_attr.GetOutputAttr(output_index).first;
    output_types->emplace_back(dtype);
  }
}

bool IsInputFormatDtypeMatched(const KernelAttr &kernel_attr, const std::vector<std::string> &input_formats,
                               const std::vector<TypeId> &input_types,
                               const std::vector<size_t> &input_not_cnode_indexes) {
  if (kernel_attr.GetInputSize() != input_types.size()) {
    MS_LOG(DEBUG) << "required input num:" << kernel_attr.GetInputSize() << ", actual input num:" << input_types.size();
    return false;
  }
  auto input_num = input_types.size();
  for (size_t i = 0; i < input_num; ++i) {
    bool is_not_cnode_idx = std::any_of(input_not_cnode_indexes.begin(), input_not_cnode_indexes.end(),
                                        [i](size_t index) { return index == i; });
    bool have_cnode_input = (input_types.size() != input_not_cnode_indexes.size());
    if (have_cnode_input && is_not_cnode_idx) {
      continue;
    }
    if (kernel_attr.GetInputAttr(i).first != input_types[i]) {
      MS_LOG(DEBUG) << "required dtype:" << kernel_attr.GetInputAttr(i).first
                    << ", actual input dtype:" << input_types[i];
      return false;
    }
    if (kernel_attr.GetInputAttr(i).second != input_formats[i]) {
      MS_LOG(DEBUG) << "required format:" << kernel_attr.GetInputAttr(i).second
                    << ", actual input format:" << input_formats[i];
      return false;
    }
  }
  return true;
}

void ExpandKernelAttr(const CNodePtr &kernel_node, KernelAttr *kernel_attr) {
  MS_EXCEPTION_IF_NULL(kernel_attr);
  TypeId input_dtype = kernel_attr->GetInputAttr(0).first;
  size_t input_num = AnfAlgo::GetInputTensorNum(kernel_node);
  for (size_t i = 1; i < input_num; ++i) {
    kernel_attr->AddInputAttr(input_dtype);
  }

  TypeId output_dtype = kernel_attr->GetOutputAttr(0).first;
  size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
  for (size_t i = 1; i < output_num; ++i) {
    kernel_attr->AddOutputAttr(output_dtype);
  }
}
}  // namespace

void SetKernelInfo(const CNodePtr &kernel_node) {
  std::vector<std::string> input_formats;
  std::vector<TypeId> input_types;
  std::vector<size_t> input_not_cnode_indexes;
  std::vector<std::string> output_formats;
  std::vector<TypeId> output_types;

  MS_LOG(INFO) << "SetKernelInfo, CNode Name: " << AnfAlgo::GetCNodeName(kernel_node);
  GetInputFormatsAndDtypes(kernel_node, &input_formats, &input_types, &input_not_cnode_indexes);

  auto kernel_attrs =
    kernel::CPUKernelFactory::GetInstance().GetSupportedKernelAttrList(AnfAlgo::GetCNodeName(kernel_node));

  for (size_t index = 0; index < kernel_attrs.size(); ++index) {
    auto kernel_attr = kernel_attrs[index];
    if (kernel_attr.GetAllSame()) {
      ExpandKernelAttr(kernel_node, &kernel_attr);
    }
    if (IsInputFormatDtypeMatched(kernel_attr, input_formats, input_types, input_not_cnode_indexes)) {
      size_t output_num = AnfAlgo::GetOutputTensorNum(kernel_node);
      if (kernel_attr.GetOutputSize() != output_num) {
        MS_LOG(DEBUG) << "Output num is not equal!";
        continue;
      }
      MS_LOG(INFO) << "Input format and dtype is matched, index: " << index;
      GetOutputFormatsAndDtypes(kernel_node, kernel_attr, &output_formats, &output_types);
      UpdatePrevNotCNodeFormatDtype(kernel_attr, input_not_cnode_indexes, kernel_node);
      for (auto &input_index : input_not_cnode_indexes) {
        input_types[input_index] = kernel_attr.GetInputAttr(input_index).first;
      }
      break;
    }
  }

  auto builder = std::make_shared<kernel::KernelBuildInfo::KernelBuildInfoBuilder>();
  MS_EXCEPTION_IF_NULL(builder);
  builder->SetInputsFormat(input_formats);
  builder->SetInputsDeviceType(input_types);
  builder->SetOutputsFormat(output_formats);
  builder->SetOutputsDeviceType(output_types);
  AnfAlgo::SetSelectKernelBuildInfo(builder->Build(), kernel_node.get());
}
}  // namespace cpu
}  // namespace device
}  // namespace mindspore