Skip to content
Snippets Groups Projects
Commit 098f6a4d authored by Olivier BICHLER's avatar Olivier BICHLER
Browse files

Fixed tests to work with revamped Scheduler

parent 7919837c
No related branches found
No related tags found
2 merge requests!50version 0.2.0,!37Support for recurrent networks
Pipeline #39302 failed
Stage: build
    Stage: test
      Hide whitespace changes
      Inline Side-by-side
      unit_tests/operator/Test_MetaOperator.cpp
      + 129
      − 48
      View file @ 098f6a4d
      ......@@ -191,9 +191,9 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      std::shared_ptr<Node> myPaddedConv =
      PaddedConv(3, 4, {3, 3}, "myPaddedConv", {1, 1}, {1, 1, 1, 1});
      }
      SECTION("LSTM(forward)") {
      auto myLSTM = LSTM(32, 64, 16, true, "ltsm");
      auto pop = Pop();
      auto myLSTM = LSTM(32, 64, 0, true, "ltsm");
      auto op = std::static_pointer_cast<OperatorTensor>(myLSTM->getOperator());
      auto microGraph = std::dynamic_pointer_cast<MetaOperator_Op>(op)->getMicroGraph();
      ......@@ -204,28 +204,55 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      REQUIRE(myLSTM->nbOutputs() == 2);
      std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(
      Array1D<float, 32>{{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0}});
      Array2D<float, 16, 32>{});
      std::shared_ptr<Tensor> myInit = std::make_shared<Tensor>(
      Array2D<float, 1, 64>{{0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0}});
      Array2D<float, 1, 64>{});
      std::shared_ptr<Tensor> myInitW = std::make_shared<Tensor>(
      Array2D<float, 64, 32>{});
      std::shared_ptr<Tensor> myInitR = std::make_shared<Tensor>(
      Array2D<float, 64, 64>{});
      op->associateInput(0, myInput);
      pop->addChild(myLSTM, 0, 0);
      pop->getOperator()->associateInput(0, myInput);
      op->associateInput(17, myInit);
      op->associateInput(18, myInit);
      op->computeOutputDims();
      // Weights X
      myLSTM->input(1).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(2).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(3).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(4).first->getOperator()->setOutput(0, myInitW);
      // Weights H
      myLSTM->input(5).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(6).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(7).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(8).first->getOperator()->setOutput(0, myInitR);
      auto g = getConnectedGraphView(myLSTM);
      g->setDataType(DataType::Float32);
      g->setBackend("cpu");
      auto scheduler = SequentialScheduler(g);
      scheduler.forward(true, true);
      g->save("lstm_outside_dims", true, true);
      microGraph->save("lstm_dims", true, true);
      REQUIRE(op->outputDimsForwarded());
      op->setDataType(DataType::Float32);
      op->setBackend("cpu");
      op->forward();
      auto microGraphScheduler = std::dynamic_pointer_cast<MetaOperator_Op>(op)->getMicroGraphScheduler();
      microGraphScheduler->saveSchedulingDiagram("lstm_scheduling");
      }
      REQUIRE(op->getNbConsumedData(0) == 512);
      REQUIRE(op->getNbConsumedData(1) == 32768);
      REQUIRE(op->getNbProducedData(0) == 1088);
      REQUIRE(op->getNbProducedData(1) == 1088);
      REQUIRE(microGraphScheduler->getStaticScheduling(0).size() == 26);
      REQUIRE(microGraphScheduler->getStaticScheduling(1).size() == 24);
      REQUIRE(microGraphScheduler->getStaticScheduling(15).size() == 24);
      }
      SECTION("LSTM(forward_values)") {
      auto myLSTM = LSTM(2, 3, 1, true, "ltsm");
      auto myLSTM = LSTM(2, 3, 0, true, "ltsm");
      auto op = std::static_pointer_cast<OperatorTensor>(myLSTM->getOperator());
      auto microGraph = std::dynamic_pointer_cast<MetaOperator_Op>(op)->getMicroGraph();
      ......@@ -248,30 +275,32 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      op->associateInput(17, myInit);
      op->associateInput(18, myInit);
      op->computeOutputDims();
      REQUIRE(op->outputDimsForwarded());
      microGraph->save("lstm_values_dims", false, true);
      // Weights X
      op->associateInput(1, myInitW);
      op->associateInput(2, myInitW);
      op->associateInput(3, myInitW);
      op->associateInput(4, myInitW);
      myLSTM->input(1).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(2).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(3).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(4).first->getOperator()->setOutput(0, myInitW);
      // Weights H
      op->associateInput(5, myInitR);
      op->associateInput(6, myInitR);
      op->associateInput(7, myInitR);
      op->associateInput(8, myInitR);
      myLSTM->input(5).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(6).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(7).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(8).first->getOperator()->setOutput(0, myInitR);
      op->setDataType(DataType::Float32);
      op->setBackend("cpu");
      auto g = getConnectedGraphView(myLSTM);
      g->setDataType(DataType::Float32);
      g->setBackend("cpu");
      auto scheduler = SequentialScheduler(g);
      scheduler.forward();
      microGraph->save("lstm_values_dims", false, true);
      std::shared_ptr<Tensor> myHiddenState = std::make_shared<Tensor>(
      Array2D<float, 3, 3>{{{0.0952412, 0.0952412, 0.0952412},
      {0.25606447, 0.25606447, 0.25606447},
      {0.40323776, 0.40323776, 0.40323776}}});
      op->forward();
      auto microGraphScheduler = std::dynamic_pointer_cast<MetaOperator_Op>(op)->getMicroGraphScheduler();
      microGraphScheduler->saveSchedulingDiagram("lstm_values_scheduling");
      ......@@ -280,23 +309,73 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      REQUIRE(approxEq<float>(*(op->getOutput(1)), *myHiddenState));
      }
      SECTION("LSTM(forward_values_seq)") {
      auto pop = Pop();
      auto myLSTM = LSTM(2, 3, 2, true, "ltsm");
      auto myGraph = Sequential({pop, myLSTM});
      auto op = std::static_pointer_cast<OperatorTensor>(myLSTM->getOperator());
      REQUIRE(myLSTM->nbInputs() == 3 + 8 + 8);
      REQUIRE(myLSTM->nbData() == 1);
      REQUIRE(myLSTM->nbOutputs() == 2);
      std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(
      Array3D<float, 2, 3, 2>{{{{1.0, 2.0}, {3.0, 4.0}, {5.0, 6.0}}, {{2.0, 3.0}, {4.0, 5.0}, {6.0, 7.0}}}});
      std::shared_ptr<Tensor> myInit = std::make_shared<Tensor>(
      Array2D<float, 3, 3>{{{0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}, {0.0, 0.0, 0.0}}});
      std::shared_ptr<Tensor> myInitW = std::make_shared<Tensor>(
      Array2D<float, 3, 2>{{{0.1, 0.1}, {0.1, 0.1}, {0.1, 0.1}}});
      std::shared_ptr<Tensor> myInitR = std::make_shared<Tensor>(
      Array2D<float, 3, 3>{{{0.1, 0.1, 0.1}, {0.1, 0.1, 0.1}, {0.1, 0.1, 0.1}}});
      pop->getOperator()->associateInput(0, myInput);
      op->associateInput(17, myInit);
      op->associateInput(18, myInit);
      // Weights X
      myLSTM->input(1).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(2).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(3).first->getOperator()->setOutput(0, myInitW);
      myLSTM->input(4).first->getOperator()->setOutput(0, myInitW);
      // Weights H
      myLSTM->input(5).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(6).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(7).first->getOperator()->setOutput(0, myInitR);
      myLSTM->input(8).first->getOperator()->setOutput(0, myInitR);
      auto g = getConnectedGraphView(myLSTM);
      g->setDataType(DataType::Float32);
      g->setBackend("cpu");
      g->save("lstm_seq", true, true);
      auto scheduler = SequentialScheduler(g);
      scheduler.forward(true, true);
      scheduler.saveSchedulingDiagram("lstm_seq_schedule");
      std::shared_ptr<Tensor> myHiddenState = std::make_shared<Tensor>(
      Array2D<float, 3, 3>{{{0.24439372, 0.24439372, 0.24439372},
      {0.49801484, 0.49801484, 0.49801484},
      {0.67162132, 0.67162132, 0.67162132}}});
      myGraph->save("lstm_seq_mygraph", true, true);
      op->getOutput(1)->print();
      myHiddenState->print();
      REQUIRE(approxEq<float>(*(op->getOutput(1)), *myHiddenState));
      }
      SECTION("LSTM(forward_values_seq_flatten)") {
      auto pop = Pop();
      auto myLSTM = LSTM(2, 3, 2, true, "ltsm");
      auto op = std::static_pointer_cast<MetaOperator_Op>(myLSTM->getOperator());
      // NOTE: LSTM really need to be flatten in the graph before execution.
      // Here, we actually don't use the meta-op as a closed black-box,
      // because its scheduling cannot be run independently of the input.
      // Since we use the Pop operator to generate sequential inputs, running
      // the meta-op internal scheduler would not work because it would not
      // update its input!
      // Here we test LSTM as it is was flatten in the graph.
      // We just borrow its micro-graph into our larger myGraph graph.
      auto myGraph = std::make_shared<GraphView>();
      myGraph->add(pop);
      myGraph->add(op->getMicroGraph());
      pop->addChild(op->getMicroGraph()->getOrderedInputs()[0].first, 0, 0);
      myGraph->add(op->getMicroGraph());
      myGraph->add(pop);
      REQUIRE(myLSTM->nbInputs() == 3 + 8 + 8);
      REQUIRE(myLSTM->nbData() == 1);
      ......@@ -316,18 +395,22 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      op->associateInput(18, myInit);
      // Weights X
      op->associateInput(1, myInitW);
      op->associateInput(2, myInitW);
      op->associateInput(3, myInitW);
      op->associateInput(4, myInitW);
      auto prodX = Producer(myInitW);
      prodX->addChild(op->getMicroGraph()->getOrderedInputs()[1].first, 0, 1);
      prodX->addChild(op->getMicroGraph()->getOrderedInputs()[2].first, 0, 1);
      prodX->addChild(op->getMicroGraph()->getOrderedInputs()[3].first, 0, 1);
      prodX->addChild(op->getMicroGraph()->getOrderedInputs()[4].first, 0, 1);
      // Weights H
      op->associateInput(5, myInitR);
      op->associateInput(6, myInitR);
      op->associateInput(7, myInitR);
      op->associateInput(8, myInitR);
      auto prodH = Producer(myInitR);
      prodH->addChild(op->getMicroGraph()->getOrderedInputs()[5].first, 0, 1);
      prodH->addChild(op->getMicroGraph()->getOrderedInputs()[6].first, 0, 1);
      prodH->addChild(op->getMicroGraph()->getOrderedInputs()[7].first, 0, 1);
      prodH->addChild(op->getMicroGraph()->getOrderedInputs()[8].first, 0, 1);
      myGraph->add({prodX, prodH});
      myGraph->setDataType(DataType::Float32);
      myGraph->setBackend("cpu");
      myGraph->save("lstm_seq_flatten", true, true);
      std::shared_ptr<Tensor> myHiddenState = std::make_shared<Tensor>(
      Array2D<float, 3, 3>{{{0.24439372, 0.24439372, 0.24439372},
      ......@@ -335,10 +418,8 @@ TEST_CASE("[cpu/operator] MetaOperator", "[MetaOperator][CPU]") {
      {0.67162132, 0.67162132, 0.67162132}}});
      auto scheduler = SequentialScheduler(myGraph);
      scheduler.forward();
      scheduler.saveSchedulingDiagram("lstm_seq_schedule");
      myGraph->save("lstm_seq", true, true);
      scheduler.forward(true, true);
      scheduler.saveSchedulingDiagram("lstm_seq_flatten_schedule");
      op->getOutput(1)->print();
      myHiddenState->print();
      ......
      unit_tests/operator/Test_PaddedConv.cpp
      + 18
      − 12
      View file @ 098f6a4d
      ......@@ -150,12 +150,15 @@ TEST_CASE("[cpu/operator] PaddedConv(forward)", "[PaddedConv][CPU]") {
      });
      myConv->getOperator()->associateInput(0,myInput);
      myConv->getOperator()->associateInput(1,myWeights);
      myConv->getOperator()->associateInput(2,myBias);
      myConv->getOperator()->setDataType(DataType::Int32);
      myConv->getOperator()->setBackend("cpu");
      op->computeOutputDims();
      myConv->forward();
      myConv->input(1).first->getOperator()->setOutput(0, myWeights);
      myConv->input(2).first->getOperator()->setOutput(0, myBias);
      auto g = getConnectedGraphView(myConv);
      g->setDataType(DataType::Int32);
      g->setBackend("cpu");
      auto scheduler = SequentialScheduler(g);
      scheduler.forward();
      REQUIRE(*(op->getOutput(0)) == *myOutput);
      }
      ......@@ -309,12 +312,15 @@ TEST_CASE("[cpu/operator] PaddedConv(forward)", "[PaddedConv][CPU]") {
      });
      myConv->getOperator()->associateInput(0,myInput);
      myConv->getOperator()->associateInput(1,myWeights);
      myConv->getOperator()->associateInput(2,myBias);
      myConv->getOperator()->setDataType(DataType::Int32);
      myConv->getOperator()->setBackend("cpu");
      op->computeOutputDims();
      myConv->forward();
      myConv->input(1).first->getOperator()->setOutput(0, myWeights);
      myConv->input(2).first->getOperator()->setOutput(0, myBias);
      auto g = getConnectedGraphView(myConv);
      g->setDataType(DataType::Int32);
      g->setBackend("cpu");
      auto scheduler = SequentialScheduler(g);
      scheduler.forward();
      REQUIRE(*(op->getOutput(0)) == *myOutput);
      }
      ......
      unit_tests/recipies/Test_FuseBatchNorm.cpp
      + 2
      − 5
      View file @ 098f6a4d
      ......@@ -86,14 +86,11 @@ TEST_CASE("[core/recipies] FuseBatchNorm", "[recipies][FuseBatchNorm]") {
      myBNOp -> setInput(4, std::make_shared<Tensor>(Array1D<float,3> {{0.4470, 0.3064, 0.7061}}));
      auto g1 = Sequential({
      myProd,
      myConv,
      myBN
      });
      g1 -> setName("fuseBNGraph");
      myProd -> addChild(myConv); // set graph input
      myProdOp -> setDataType(DataType::Float32);
      myProdOp -> setBackend("cpu");
      g1 -> compile("cpu", DataType::Float32);
      auto s = SequentialScheduler(g1);
      ......@@ -107,7 +104,7 @@ TEST_CASE("[core/recipies] FuseBatchNorm", "[recipies][FuseBatchNorm]") {
      std::shared_ptr<Tensor> res2 = std::make_shared<Tensor>(*(myConvOp -> getOutput(0)));
      REQUIRE(g1 -> outputNodes().size() == 1);
      REQUIRE(g1 -> inputNodes().size() == 1);
      REQUIRE(g1 -> inputNodes().size() == 0);
      bool eq = true;
      for (std::size_t i = 0; i < res1->size(); ++i) {
      eq &= std::abs(res1->get<float>(i) - res2->get<float>(i)) < 1.0e-06;
      ......
      unit_tests/scheduler/Test_Scheduler.cpp
      + 3
      − 2
      View file @ 098f6a4d
      ......@@ -218,14 +218,15 @@ TEST_CASE("[cpu/scheduler] SequentialScheduler(forward)") {
      auto add2 = Add(2, "add2");
      auto bias = Producer(biasTensor, "bias");
      auto init = Producer(initTensor, "init");
      auto input = Producer(in, "input");
      std::shared_ptr<GraphView> g = Sequential({add1, mem, add2});
      init->addChild(mem, 0, 1);
      mem->addChild(add1, 1, 1);
      bias->addChild(add2, 0, 1);
      add1->getOperator()->setInput(0, in);
      input->addChild(add1, 0, 0);
      // Update GraphView inputs/outputs following previous connections:
      g->add({mem, add1, add2, init, bias});
      g->add({mem, add1, add2, init, bias, input});
      g->setBackend("cpu");
      g->setDataType(Aidge::DataType::Int32);
      ......
      0% or .
      You are about to add 0 people to the discussion. Proceed with caution.
      Finish editing this message first!
      Please register or to comment

      Copyright © Eclipse Foundation, Inc. All Rights Reserved.     Privacy Policy | Terms of Use | Copyright Agent