graphengine/tests/ut/ge/graph/passes/infershape_pass_unittest.cc

/**
 * Copyright 2019-2020 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 <gtest/gtest.h>

#define protected public
#define private public
#include "graph/passes/infershape_pass.h"

#include "graph/utils/tensor_utils.h"
#include "graph/utils/graph_utils.h"
#include "graph/operator_factory.h"
#include "graph/operator_reg.h"
#include "graph_builder_utils.h"

using namespace std;
using namespace testing;
namespace ge {
namespace {
// do nothing stub infer_func
const auto stub_func = [](Operator &op) { return GRAPH_SUCCESS; };
// infer from input to output stub infer_func  (input size == output size)
const auto stub_mapping_func = [](Operator &op) {
  size_t in_num = op.GetInputsSize();
  for (size_t i = 0; i < in_num; ++i) {
    auto in_desc = op.GetInputDesc(i);
    auto out_desc = op.GetOutputDesc(i);
    out_desc.SetShape(in_desc.GetShape());
    out_desc.SetDataType(in_desc.GetDataType());
    op.UpdateOutputDesc(out_desc.GetName(), out_desc);
  }
  return GRAPH_SUCCESS;
};
// merge infer_func

// while infer_func
const auto while_infer_func = [](Operator &op) {
  size_t in_num = op.GetInputsSize();
  size_t out_num = op.GetOutputsSize();
  if (in_num != out_num) {
    return GRAPH_FAILED;
  }
  bool need_infer_again = false;
  for (size_t i = 0; i < in_num; ++i) {
    auto in_desc = op.GetDynamicInputDesc("input", i);
    auto out_desc = op.GetDynamicOutputDesc("output", i);
    auto data_shape = in_desc.GetShape();
    auto out_shape = out_desc.GetShape();
    if(out_shape.GetDims() == DUMMY_SHAPE){
      return GRAPH_SUCCESS;
    }
    // check datatype between output and input
    if (in_desc.GetDataType() != out_desc.GetDataType()) {
      return GRAPH_FAILED;
    }

    if (data_shape.GetDims() != out_shape.GetDims()) {
      need_infer_again = true;
      if (data_shape.GetDimNum() != out_shape.GetDimNum()) {
        in_desc.SetUnknownDimNumShape();
      } else {
        size_t data_dim_num = data_shape.GetDimNum();
        std::vector<std::pair<int64_t, int64_t>> data_shape_range = {data_dim_num, std::make_pair(1, UNKNOWN_DIM)};
        for (size_t j = 0; j < data_dim_num; ++j) {
          if (data_shape.GetDim(j) != out_shape.GetDim(j)) {
            data_shape.SetDim(j, UNKNOWN_DIM);
          }
          if (data_shape.GetDim(j) != UNKNOWN_DIM) {
            data_shape_range[j] = std::make_pair(data_shape.GetDim(j), data_shape.GetDim(j));
          }
        }
        in_desc.SetShape(data_shape);
        in_desc.SetShapeRange(data_shape_range);
      }
      op.UpdateDynamicOutputDesc("output", i, in_desc);
      op.UpdateDynamicInputDesc("input", i, in_desc);
    }
  }
  return need_infer_again ? GRAPH_NODE_NEED_REPASS : GRAPH_SUCCESS;
};
}
class UtestGraphInfershapePass : public testing::Test {
 protected:
  void SetUp() {}
  void TearDown() {}
};

static NodePtr CreateNode(ComputeGraph &graph, const string &name, const string &type, int in_num, int out_num,
                          std::function<graphStatus(Operator &)> infer_func = stub_func) {
  OpDescPtr op_desc = std::make_shared<OpDesc>(name, type);
  op_desc->SetStreamId(0);
  static int32_t index = 0;
  op_desc->SetId(index++);

  GeTensorDesc tensor(GeShape(), FORMAT_NCHW, DT_FLOAT);
  TensorUtils::SetSize(tensor, 512);
  vector<int64_t> input_offset;
  for (int i = 0; i < in_num; i++) {
    op_desc->AddInputDesc(tensor);
    input_offset.emplace_back(1024);
  }
  op_desc->SetInputOffset(input_offset);

  vector<int64_t> output_offset;
  for (int i = 0; i < out_num; i++) {
    op_desc->AddOutputDesc(tensor);
    output_offset.emplace_back(1024);
  }
  op_desc->SetOutputOffset(output_offset);

  op_desc->SetWorkspace({});
  op_desc->SetWorkspaceBytes({});
  op_desc->SetOpKernelLibName("DNN_VM_RTS_OP_STORE");

  op_desc->AddInferFunc(infer_func);
  return graph.AddNode(op_desc);
}

/*
TEST_F(UtestGraphInfershapePass, infershape_pass_failed) {
  GeTensorDesc ge_tensor_desc(GeShape({-2, 2, 3, 4}), ge::FORMAT_NCHW, DT_FLOAT16);
  string type = "AddN";
  auto addn_op_desc = std::make_shared<OpDesc>("AddN", type);
  addn_op_desc->AddInputDesc(ge_tensor_desc);
  addn_op_desc->AddOutputDesc(ge_tensor_desc);
  auto graph = std::make_shared<ComputeGraph>("test");
  auto addn_node = std::make_shared<Node>(addn_op_desc, graph);
  addn_node->Init();

  InferShapePass infershape_pass;
  EXPECT_EQ(infershape_pass.Run(addn_node), GE_GRAPH_INFERSHAPE_FAILED);
}
*/

TEST_F(UtestGraphInfershapePass, delete_need_infer_again) {
  auto graph = std::make_shared<ComputeGraph>("test");

  auto no_op_desc = std::make_shared<OpDesc>("No", "NoOp");
  auto no_op_node = graph->AddNode(no_op_desc);
  AttrUtils::SetBool(no_op_desc, "_need_infer_again", false);

  InferShapePass infershape_pass;
  infershape_pass.options_[kOptimizeAfterSubGraph] = "yes";
  EXPECT_EQ(infershape_pass.Run(no_op_node), SUCCESS);
}
TEST_F(UtestGraphInfershapePass, infer_from_pre_to_next) {
  /*
   *   cast->shape
   */
  auto graph = std::make_shared<ComputeGraph>("test_infer_shape");
  auto data1 = CreateNode(*graph, "dataq", DATA, 0, 1);
  auto cast1 = CreateNode(*graph, "cast1", CAST, 1, 1, stub_mapping_func);
  auto cast_in_desc = cast1->GetOpDesc()->MutableInputDesc(0);
  cast_in_desc->SetShape(GeShape({1,2,3}));
  cast_in_desc->SetDataType(DT_INT32);
  auto transdata1 = CreateNode(*graph, "transdata1", TRANSDATA, 1, 1, stub_mapping_func);
  GraphUtils::AddEdge(data1->GetOutDataAnchor(0), cast1->GetInDataAnchor(0));
  GraphUtils::AddEdge(cast1->GetOutDataAnchor(0), transdata1->GetInDataAnchor(0));

  // check before infer cast1
  auto cast_before = graph->FindNode("cast1");
  vector<int64_t> expect_cast1_shape_dim = {1,2,3};
  auto real_cast1_before_shape_dim = cast_before->GetOpDesc()->GetInputDesc(0).GetShape().GetDims();
  auto transdata1_before = graph->FindNode("transdata1");
  vector<int64_t> expect_transdata1_shape_dim = {};
  auto real_transdata1_before_shape_dim = transdata1_before->GetOpDesc()->GetInputDesc(0).GetShape().GetDims();
  EXPECT_EQ(real_cast1_before_shape_dim, expect_cast1_shape_dim);
  EXPECT_EQ(real_transdata1_before_shape_dim, expect_transdata1_shape_dim);
  // run infershape pass
  InferShapePass infer_shape_pass;
  infer_shape_pass.Run(cast_before);
  // check cast1 add transdata1 to repass_immediately
  infer_shape_pass.GetNodesNeedRePassImmediately();
  EXPECT_TRUE(!infer_shape_pass.GetNodesNeedRePassImmediately().empty());
  // check transdata input_shape & datatype after infer
  auto transdata1_after = graph->FindNode("transdata1");
  auto transdata1_opdesc = transdata1_before->GetOpDesc();
  auto real_transdata1_after_shape_dim = transdata1_opdesc->GetInputDesc(0).GetShape().GetDims();
  EXPECT_EQ(real_transdata1_after_shape_dim, expect_cast1_shape_dim);
  auto transdata1_datatype_after = transdata1_opdesc->GetInputDesc(0).GetDataType();
  EXPECT_EQ(transdata1_datatype_after, DT_INT32);
}
TEST_F(UtestGraphInfershapePass, stop_node_for_while_loop) {
/*******************************************************************************
 *      Exit         Identify
 *        \         /       \.
 *         \       /         \.
 *          Switch           Add
 *         /     |            |
 *        /      |            |
 *       /       |            |
 *  LoopCond     |            |
 *      \        |            |
 *       \       |            |
 *        \      |            |
 *       Less    |            |
 *          \    |       NextIteration
 *           \   |            |
 *            \  |            |
 *            Merge <---------|
 *              |
 *              |
 *            Enter
 ******************************************************************************/
  auto graph = std::make_shared<ComputeGraph>("test_infer_shape");
  auto data1 = CreateNode(*graph, "data", DATA, 1, 1);
  auto enter1 = CreateNode(*graph, "enter", ENTER, 1, 1);
  auto merge1 = CreateNode(*graph, "merge", MERGE, 2, 2);
  auto less1 = CreateNode(*graph, "less", LESS, 2, 1);
  auto loop1 = CreateNode(*graph, "loopcond", LOOPCOND, 1, 1);
  auto switch1 = CreateNode(*graph, "switch", SWITCH, 2, 2);
  auto ident1 = CreateNode(*graph, "identity", IDENTITY, 1, 1);
  auto add1 = CreateNode(*graph, "add", ADD, 2, 1);
  auto next1 = CreateNode(*graph, "next", NEXTITERATION, 1, 1);
  auto exit1 = CreateNode(*graph, "exit", EXIT, 1, 1);
  auto value0 = CreateNode(*graph, "const", CONSTANT, 0, 1);
  auto value1 = CreateNode(*graph, "const", CONSTANT, 0, 1);
  auto output1 = CreateNode(*graph, "net_output", NETOUTPUT, 1, 1);

  GraphUtils::AddEdge(data1->GetOutDataAnchor(0), enter1->GetInDataAnchor(0));
  GraphUtils::AddEdge(enter1->GetOutDataAnchor(0), merge1->GetInDataAnchor(0));
  GraphUtils::AddEdge(merge1->GetOutDataAnchor(0), less1->GetInDataAnchor(0));
  GraphUtils::AddEdge(value1->GetOutDataAnchor(0), less1->GetInDataAnchor(1));
  GraphUtils::AddEdge(less1->GetOutDataAnchor(0), loop1->GetInDataAnchor(0));

  GraphUtils::AddEdge(loop1->GetOutDataAnchor(0), switch1->GetInDataAnchor(0));
  GraphUtils::AddEdge(merge1->GetOutDataAnchor(0), switch1->GetInDataAnchor(1));

  GraphUtils::AddEdge(switch1->GetOutDataAnchor(0), exit1->GetInDataAnchor(0));
  GraphUtils::AddEdge(switch1->GetOutDataAnchor(1), ident1->GetInDataAnchor(0));

  GraphUtils::AddEdge(ident1->GetOutDataAnchor(0), add1->GetInDataAnchor(0));
  GraphUtils::AddEdge(value1->GetOutDataAnchor(0), add1->GetInDataAnchor(1));
  GraphUtils::AddEdge(add1->GetOutDataAnchor(0), next1->GetInDataAnchor(0));

  GraphUtils::AddEdge(next1->GetOutDataAnchor(0), merge1->GetInDataAnchor(1));
  GraphUtils::AddEdge(exit1->GetOutDataAnchor(0), output1->GetInDataAnchor(0));

  GEPass ge_passes(graph);
  NamesToPass names_to_passes;
  InferShapePass infer_shape_pass;
  names_to_passes.emplace_back("InferShapePass", &infer_shape_pass);

  EXPECT_EQ(ge_passes.Run(names_to_passes), SUCCESS);
}
}  // namespace ge