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 "common/graph_kernel/substitute_dropout.h"
  
  #include <vector>
  #include <string>
  #include <algorithm>
  #include <memory>
  
  #include "mindspore/core/ops/core_ops.h"
  #include "include/common/utils/utils.h"
  #include "backend/common/optimizer/helper.h"
  #include "common/graph_kernel/graph_kernel_helper.h"
  #include "backend/common/session/anf_runtime_algorithm.h"
  #include "include/common/utils/anfalgo.h"
  #include "ir/tensor.h"
  #include "kernel/kernel_build_info.h"
  #include "runtime/device/kernel_info.h"
  
  namespace mindspore {
  namespace prim {
  inline const PrimitivePtr kPrimGkDropout = std::make_shared<Primitive>("GkDropout");
  }  // namespace prim
  namespace graphkernel {
  using opt::CheckCNodeInputSize;
  using opt::kDropoutInputTensorNum;
  
  int64_t DropoutExpanderDeco::seed_ = time(nullptr);
  
  AnfNodePtr DropoutExpanderDeco::Run(const AnfNodePtr &node) {
    MS_EXCEPTION_IF_NULL(node);
    CNodePtr cnode = node->cast<CNodePtr>();
    MS_EXCEPTION_IF_NULL(cnode);
    auto func_graph = node->func_graph();
    CheckCNodeInputSize(cnode, kDropoutInputTensorNum);
    auto shape = AnfAlgo::GetInputDeviceShape(cnode, 0);
    ShapeVector shape_i64;
    (void)std::transform(shape.begin(), shape.end(), std::back_inserter(shape_i64), SizeToLong);
    // Get seed from original dropout's attrs, rather than set seed by time.
    // Only seed0 and seed1 are all equal to 0, then set seed = time.
    auto node_prim = GetCNodePrimitive(node);
    MS_EXCEPTION_IF_NULL(node_prim);
    int64_t seed = GetValue<int64_t>(node_prim->GetAttr("Seed0"));
    if (seed == 0) {
      seed = GetValue<int64_t>(node_prim->GetAttr("Seed1"));
      if (seed == 0) {
        seed = seed_++;
      }
    }
    // Create a uniform_real kernel to generate random value.
    auto tensor = std::make_shared<tensor::Tensor>(kNumberTypeInt64, ShapeVector(1, SizeToLong(shape.size())),
                                                   static_cast<void *>(&shape[0]), kNumberTypeInt64);
    AnfNodePtrList uniform_real_input = {NewValueNode(prim::kPrimCudnnUniformReal), NewValueNode(tensor)};
    uniform_real_input[1]->set_abstract(tensor->ToAbstract());
    uniform_real_input[1]->set_kernel_info(std::make_shared<device::KernelInfo>());
    auto uniform_real_node = func_graph->NewCNode(uniform_real_input);
    SetNodeAttrSafely("seed", MakeValue(seed), uniform_real_node);
    common::AnfAlgo::SetNodeAttr("seed2", MakeValue(static_cast<int64_t>(0)), uniform_real_node);
    uniform_real_node->set_abstract(std::make_shared<abstract::AbstractTensor>(kFloat32, shape_i64));
    // Set kernel_info for uniform_real node
    auto uniform_real_kernel_info_builder = std::make_shared<kernel::KernelBuildInfo::KernelBuildInfoBuilder>();
    uniform_real_kernel_info_builder->SetInputsFormat({kOpFormat_DEFAULT});
    uniform_real_kernel_info_builder->SetInputsDeviceType({kNumberTypeInt32});
    uniform_real_kernel_info_builder->SetOutputsFormat({kOpFormat_DEFAULT});
    uniform_real_kernel_info_builder->SetOutputsDeviceType({kNumberTypeFloat32});
    uniform_real_kernel_info_builder->SetKernelType(KernelType::UNKNOWN_KERNEL_TYPE);
    uniform_real_kernel_info_builder->SetProcessor(kernel::Processor::CUDA);
    AnfAlgo::SetSelectKernelBuildInfo(uniform_real_kernel_info_builder->Build(), uniform_real_node.get());
  
    // Create a GKDropout node with uniform_real as its second input.
    AnfNodePtrList gkdropout_inputs = {NewValueNode(prim::kPrimGkDropout), cnode->input(1), uniform_real_node};
    auto new_dropout_node = func_graph->NewCNode(gkdropout_inputs);
    SetNodeAttrSafely("keep_prob", MakeValue(common::AnfAlgo::GetNodeAttr<float>(cnode, "keep_prob")), new_dropout_node);
    // the output info is unchanged.
    new_dropout_node->set_abstract(node->abstract());
    auto old_kernel_info = AnfAlgo::GetSelectKernelBuildInfo(node);
    auto dropout_kernel_info_builder = std::make_shared<kernel::KernelBuildInfo::KernelBuildInfoBuilder>(old_kernel_info);
    dropout_kernel_info_builder->SetInputsFormat({old_kernel_info->GetInputFormat(0), kOpFormat_DEFAULT});
    dropout_kernel_info_builder->SetInputsDeviceType({old_kernel_info->GetInputDeviceType(0), kNumberTypeFloat32});
    AnfAlgo::SetSelectKernelBuildInfo(dropout_kernel_info_builder->Build(), new_dropout_node.get());
    return decorated_->Run(new_dropout_node);
  }
  }  // namespace graphkernel
  }  // namespace mindspore
  