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test_scheduler.cc
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test_scheduler.cc
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/************************************************************
*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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 <sstream>
#include <utility>
#include "gtest/gtest.h"
#include "singa/core/device.h"
#include "singa/core/scheduler.h"
#include "singa/core/tensor.h"
#include "singa/singa_config.h"
typedef std::vector<int> IntVec;
using singa::Blk2InfoMap;
using singa::BlkInfo;
using singa::Block;
using singa::BlockSet;
using singa::BlockType;
using singa::BlockVec;
using singa::Context;
using singa::Device;
using singa::Edge;
using singa::EdgeVec;
using singa::Graph;
using singa::Node;
using singa::NodeVec;
using singa::Shape;
using singa::Tensor;
namespace testing {
namespace internal {
enum GTestColor { COLOR_DEFAULT, COLOR_RED, COLOR_GREEN, COLOR_YELLOW };
extern void ColoredPrintf(GTestColor color, const char *fmt, ...);
} // namespace internal
} // namespace testing
class Gout : public std::stringstream {
public:
~Gout() {
testing::internal::ColoredPrintf(testing::internal::COLOR_GREEN,
"[ ] ");
testing::internal::ColoredPrintf(testing::internal::COLOR_YELLOW,
str().c_str());
}
};
#define GOUT Gout()
#define CheckNode(node, id_, in_edges_, out_edges_) \
do { \
EXPECT_EQ(id_, node->id()); \
EXPECT_EQ(in_edges_.size(), node->in_edges().size()); \
EXPECT_EQ(out_edges_.size(), node->out_edges().size()); \
for (size_t i = 0; i < in_edges_.size(); ++i) { \
EXPECT_EQ(in_edges_[i], node->in_edges()[i]) \
<< "in_edges is wrong at index [" << i << "]"; \
} \
for (size_t i = 0; i < out_edges_.size(); ++i) { \
EXPECT_EQ(out_edges_[i], node->out_edges()[i]) \
<< "out_edges is wrong at index [" << i << "]"; \
} \
} while (false)
#define CheckEdge(edge, id_, block_, src_node_, dst_node_) \
do { \
EXPECT_EQ(id_, edge->id()); \
EXPECT_EQ(block_, edge->block()); \
EXPECT_EQ(src_node_, edge->src_node()); \
EXPECT_EQ(dst_node_, edge->dst_node()); \
} while (false)
#define CheckBlock(blkInfo, id_, blk_, type_, ref_, write_edge_, used_nodes_) \
do { \
EXPECT_EQ(id_, blkInfo->id()); \
EXPECT_EQ(blk_, blkInfo->block()); \
EXPECT_EQ(type_, blkInfo->type()); \
EXPECT_EQ(ref_, blkInfo->graph_ref()); \
EXPECT_EQ(write_edge_, blkInfo->write_edge()); \
EXPECT_EQ(used_nodes_, blkInfo->used_nodes()); \
for (size_t i = 0; i < used_nodes_.size(); ++i) { \
EXPECT_EQ(used_nodes_[i], blkInfo->used_node(i)) \
<< "used_nodes is different at index [" << i << "]"; \
} \
} while (false)
#define CheckLeafBlocks(leaf_blocks, correct_leaf_blocks) \
do { \
EXPECT_EQ(correct_leaf_blocks.size(), leaf_blocks.size()); \
for (auto it : leaf_blocks) { \
auto iter = correct_leaf_blocks.find(it); \
EXPECT_NE(iter, correct_leaf_blocks.end()) << "leaf blocks mismatch"; \
} \
} while (false)
#define CheckFreeBlocks(node_id, blocks, free_blocks, correct_free_blocks) \
do { \
EXPECT_EQ(correct_free_blocks.size(), free_blocks.size()); \
for (size_t i = 0; i < correct_free_blocks.size(); ++i) { \
bool flag = false; \
for (size_t j = 0; j < free_blocks.size(); ++j) { \
if (blocks.find(free_blocks[j])->second->id() == \
correct_free_blocks[i]) { \
flag = true; \
break; \
} \
} \
EXPECT_TRUE(flag) << "block [" << correct_free_blocks[i] \
<< "] is not recycled properly at node " << node_id; \
} \
} while (false)
class TestGraph : public testing::Test {
protected:
virtual void SetUp();
virtual void TearDown();
protected:
std::vector<std::pair<std::string, std::shared_ptr<Device> > > devices;
};
void TestGraph::SetUp() {
auto cpp_cpu = singa::Platform::GetDefaultDevice();
devices.push_back(std::make_pair("cpp_cpu", cpp_cpu));
#ifdef USE_CUDA
auto cuda_gpu = std::make_shared<singa::CudaGPU>();
devices.push_back(std::make_pair("cuda_gpu", cuda_gpu));
#endif
}
void TestGraph::TearDown() { devices.clear(); }
TEST_F(TestGraph, AddOp) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {out.block()});
EXPECT_EQ(1u, nodes.size());
EXPECT_EQ(2u, edges.size());
EXPECT_EQ(2u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto node = nodes[0];
auto edge1 = edges[0];
auto edge2 = edges[1];
auto block1 = blocks.find(in.block())->second;
auto block2 = blocks.find(out.block())->second;
CheckNode(node, 0, EdgeVec({edge1}), EdgeVec({edge2}));
CheckEdge(edge1, 0, in.block(), nullptr, node);
CheckEdge(edge2, 1, out.block(), node, nullptr);
CheckBlock(block1, 0, in.block(), BlockType::kInput, 1, nullptr,
NodeVec({}));
CheckBlock(block2, 1, out.block(), BlockType::kEnd, 1, edge2, NodeVec({}));
CheckLeafBlocks(leaf_blocks, BlockSet({out.block()}));
EXPECT_TRUE(graph.dirty());
}
}
TEST_F(TestGraph, AddSyncOp) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {out.block()});
graph.AddOperation(op, {}, {});
EXPECT_EQ(2u, nodes.size());
EXPECT_EQ(3u, edges.size());
EXPECT_EQ(2u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto node1 = nodes[0];
auto node2 = nodes[1];
auto edge1 = edges[0];
auto edge2 = edges[1];
auto edge3 = edges[2];
auto block1 = blocks.find(in.block())->second;
auto block2 = blocks.find(out.block())->second;
CheckNode(node1, 0, EdgeVec({edge1}), EdgeVec({edge2}));
CheckNode(node2, 1, EdgeVec({edge2}), EdgeVec({edge3}));
CheckEdge(edge1, 0, in.block(), nullptr, node1);
CheckEdge(edge2, 1, out.block(), node1, node2);
CheckEdge(edge3, 2, out.block(), node2, nullptr);
CheckBlock(block1, 0, in.block(), BlockType::kInput, 1, nullptr,
NodeVec({}));
CheckBlock(block2, 1, out.block(), BlockType::kInter, 1, edge3,
NodeVec({}));
CheckLeafBlocks(leaf_blocks, BlockSet({out.block()}));
EXPECT_TRUE(graph.dirty());
}
}
TEST_F(TestGraph, AddInplaceOp) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {in.block()});
EXPECT_EQ(1u, nodes.size());
EXPECT_EQ(2u, edges.size());
EXPECT_EQ(1u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto node1 = nodes[0];
auto edge1 = edges[0];
auto edge2 = edges[1];
auto block1 = blocks.find(in.block())->second;
CheckNode(node1, 0, EdgeVec({edge1}), EdgeVec({edge2}));
CheckEdge(edge1, 0, in.block(), nullptr, node1);
CheckEdge(edge2, 1, in.block(), node1, nullptr);
CheckBlock(block1, 0, in.block(), BlockType::kParam, 2, edge2, NodeVec({}));
CheckLeafBlocks(leaf_blocks, BlockSet{in.block()});
EXPECT_TRUE(graph.dirty());
graph.AddOperation(op, {in.block(), out.block()}, {out.block()});
EXPECT_EQ(2u, nodes.size());
EXPECT_EQ(4u, edges.size());
EXPECT_EQ(2u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto node2 = nodes[1];
auto edge3 = edges[2];
auto edge4 = edges[3];
auto block2 = blocks.find(out.block())->second;
CheckNode(node1, 0, EdgeVec({edge1}), EdgeVec({edge2}));
CheckNode(node2, 1, EdgeVec({edge2, edge3}), EdgeVec({edge4}));
CheckEdge(edge2, 1, in.block(), node1, node2);
CheckEdge(edge3, 2, out.block(), nullptr, node2);
CheckEdge(edge4, 3, out.block(), node2, nullptr);
CheckBlock(block1, 0, in.block(), BlockType::kParam, 3, edge2, NodeVec({}));
CheckBlock(block2, 1, out.block(), BlockType::kParam, 2, edge4,
NodeVec({}));
CheckLeafBlocks(leaf_blocks, BlockSet({out.block()}));
EXPECT_TRUE(graph.dirty());
}
}
TEST_F(TestGraph, BlockTypeInput) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {out.block()});
EXPECT_EQ(1u, nodes.size());
EXPECT_EQ(2u, edges.size());
EXPECT_EQ(2u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto block1 = blocks.find(in.block())->second;
CheckBlock(block1, 0, in.block(), BlockType::kInput, 1, nullptr,
NodeVec({}));
}
}
TEST_F(TestGraph, BlockTypeParam) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor mid(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {in.block()});
graph.AddOperation(op, {in.block(), mid.block()}, {out.block()});
graph.AddOperation(op, {out.block()}, {mid.block()});
EXPECT_EQ(3u, nodes.size());
EXPECT_EQ(5u, edges.size());
EXPECT_EQ(3u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto edge2 = edges[1];
auto edge5 = edges[4];
auto block1 = blocks.find(in.block())->second;
auto block2 = blocks.find(mid.block())->second;
CheckBlock(block1, 0, in.block(), BlockType::kParam, 3, edge2, NodeVec({}));
CheckBlock(block2, 1, mid.block(), BlockType::kParam, 2, edge5,
NodeVec({}));
}
}
TEST_F(TestGraph, BlockTypeInter) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor mid(Shape{1}, dev);
Tensor out(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {mid.block(), out.block()});
graph.AddOperation(op, {mid.block()}, {});
graph.AddOperation(op, {out.block()}, {out.block()});
EXPECT_EQ(3u, nodes.size());
EXPECT_EQ(4u, edges.size());
EXPECT_EQ(3u, blocks.size());
EXPECT_EQ(1u, leaf_blocks.size());
auto edge2 = edges[1];
auto edge4 = edges[3];
auto block2 = blocks.find(mid.block())->second;
auto block3 = blocks.find(out.block())->second;
CheckBlock(block2, 1, mid.block(), BlockType::kInter, 2, edge2,
NodeVec({}));
CheckBlock(block3, 2, out.block(), BlockType::kInter, 3, edge4,
NodeVec({}));
}
}
TEST_F(TestGraph, BlockTypeEnd) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor out1(Shape{1}, dev);
Tensor out2(Shape{1}, dev);
auto op = [](Context *ctx) mutable {};
graph.AddOperation(op, {in.block()}, {out1.block()});
graph.AddOperation(op, {}, {out2.block()});
EXPECT_EQ(2u, nodes.size());
EXPECT_EQ(3u, edges.size());
EXPECT_EQ(3u, blocks.size());
EXPECT_EQ(2u, leaf_blocks.size());
auto edge2 = edges[1];
auto edge3 = edges[2];
auto block2 = blocks.find(out1.block())->second;
auto block3 = blocks.find(out2.block())->second;
CheckBlock(block2, 1, out1.block(), BlockType::kEnd, 1, edge2, NodeVec({}));
CheckBlock(block3, 2, out2.block(), BlockType::kEnd, 1, edge3, NodeVec({}));
}
}
TEST_F(TestGraph, RunGraph) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor mid(Shape{1}, dev);
Tensor out(Shape{1}, dev);
Tensor b1(Shape{1}, dev);
Tensor b2(Shape{1}, dev);
Tensor dx(Shape{1}, dev);
Tensor dx1(Shape{1}, dev);
Tensor dx2(Shape{1}, dev);
Tensor dy1(Shape{1}, dev);
Tensor dy2(Shape{1}, dev);
Tensor db1(Shape{1}, dev);
Tensor db2(Shape{1}, dev);
// function: (in + b1) * in + b2
auto op1 = [in, b1, mid](Context *ctx) mutable {
singa::Add(in, b1, &mid);
};
auto op2 = [mid, in, out](Context *ctx) mutable {
singa::EltwiseMult(mid, in, &out);
};
auto op3 = [out, b2](Context *ctx) mutable { singa::Add(out, b2, &out); };
auto op4 = [out, dy1, db2](Context *ctx) mutable {
dy1.CopyData(out);
db2.CopyData(out);
};
auto op5 = [in, mid, dy1, dy2, dx1](Context *ctx) mutable {
singa::EltwiseMult(dy1, in, &dy2);
singa::EltwiseMult(dy1, mid, &dx1);
};
auto op6 = [dy2, dx2, db1](Context *ctx) mutable {
dx2.CopyData(dy2);
db1.CopyData(dy2);
};
auto op7 = [dx1, dx2, dx](Context *ctx) mutable {
singa::Add(dx1, dx2, &dx);
};
graph.AddOperation(op1, {in.block(), b1.block()}, {mid.block()});
graph.AddOperation(op2, {mid.block(), in.block()}, {out.block()});
graph.AddOperation(op3, {out.block(), b2.block()}, {out.block()});
graph.AddOperation(op4, {out.block()}, {dy1.block(), db2.block()});
graph.AddOperation(op5, {dy1.block()}, {dy2.block(), dx1.block()});
graph.AddOperation(op6, {dy2.block()}, {dx2.block(), db1.block()});
graph.AddOperation(op7, {dx1.block(), dx2.block()}, {dx.block()});
EXPECT_EQ(7u, nodes.size());
EXPECT_EQ(14u, edges.size());
EXPECT_EQ(12u, blocks.size());
EXPECT_EQ(3u, leaf_blocks.size());
in.SetValue(0);
b1.SetValue(-1);
b2.SetValue(2);
graph.RunGraph();
float dx_, db1_, db2_;
dx.ToHost().get_value(&dx_, 1);
db1.ToHost().get_value(&db1_, 1);
db2.ToHost().get_value(&db2_, 1);
EXPECT_EQ(-2, dx_);
EXPECT_EQ(0, db1_);
EXPECT_EQ(2, db2_);
}
}
TEST_F(TestGraph, MultipleIndependentOps) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
Tensor workspace(Shape{1}, dev);
Tensor b1(Shape{1}, dev);
Tensor b2(Shape{1}, dev);
Tensor b3(Shape{1}, dev);
Tensor b4(Shape{1}, dev);
// emulate clean up workspace, use the rnn design as reference
auto clean1 = [workspace](Context *ctx) mutable {};
auto clean2 = [workspace](Context *ctx) mutable {};
auto clean3 = [workspace](Context *ctx) mutable {};
auto clean4 = [workspace](Context *ctx) mutable {};
// emulate usage of workspace, use the rnn design as reference
auto op1 = [workspace, b1](Context *ctx) mutable {};
auto op2 = [workspace, b2](Context *ctx) mutable {};
auto op3 = [workspace, b2](Context *ctx) mutable {};
auto op4 = [workspace, b2](Context *ctx) mutable {};
graph.AddOperation(clean1, {}, {workspace.block()});
graph.AddOperation(op1, {b1.block()}, {workspace.block(), b1.block()});
graph.AddOperation(clean2, {}, {workspace.block()});
graph.AddOperation(op2, {b2.block()}, {workspace.block(), b2.block()});
graph.AddOperation(clean3, {}, {workspace.block()});
graph.AddOperation(op3, {b3.block()}, {workspace.block(), b3.block()});
graph.AddOperation(clean4, {}, {workspace.block()});
graph.AddOperation(op4, {b4.block()}, {workspace.block(), b4.block()});
EXPECT_EQ(8u, nodes.size());
graph.RunGraph();
}
}
TEST_F(TestGraph, RunInSerial) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
Tensor in(Shape{1}, dev);
Tensor mid(Shape{1}, dev);
Tensor out(Shape{1}, dev);
Tensor b1(Shape{1}, dev);
Tensor b2(Shape{1}, dev);
Tensor dx(Shape{1}, dev);
Tensor dx1(Shape{1}, dev);
Tensor dx2(Shape{1}, dev);
Tensor dy1(Shape{1}, dev);
Tensor dy2(Shape{1}, dev);
Tensor db1(Shape{1}, dev);
Tensor db2(Shape{1}, dev);
auto op1 = [in, b1, mid](Context *ctx) mutable {
singa::Add(in, b1, &mid);
};
auto op2 = [mid, in, out](Context *ctx) mutable {
singa::EltwiseMult(mid, in, &out);
};
auto op3 = [out, b2](Context *ctx) mutable { singa::Add(out, b2, &out); };
auto op4 = [out, dy1, db2](Context *ctx) mutable {
dy1.CopyData(out);
db2.CopyData(out);
};
auto op5 = [in, mid, dy1, dy2, dx1](Context *ctx) mutable {
singa::EltwiseMult(dy1, in, &dy2);
singa::EltwiseMult(dy1, mid, &dx1);
};
auto op6 = [dy2, dx2, db1](Context *ctx) mutable {
dx2.CopyData(dy2);
db1.CopyData(dy2);
};
auto op7 = [dx1, dx2, dx](Context *ctx) mutable {
singa::Add(dx1, dx2, &dx);
};
graph.AddOperation(op1, {in.block(), b1.block()}, {mid.block()});
graph.AddOperation(op2, {mid.block(), in.block()}, {out.block()});
graph.AddOperation(op3, {out.block(), b2.block()}, {out.block()});
graph.AddOperation(op4, {out.block()}, {dy1.block(), db2.block()});
graph.AddOperation(op5, {dy1.block()}, {dy2.block(), dx1.block()});
graph.AddOperation(op6, {dy2.block()}, {dx2.block(), db1.block()});
graph.AddOperation(op7, {dx1.block(), dx2.block()}, {dx.block()});
EXPECT_EQ(7u, nodes.size());
EXPECT_EQ(14u, edges.size());
EXPECT_EQ(12u, blocks.size());
EXPECT_EQ(3u, leaf_blocks.size());
in.SetValue(0);
b1.SetValue(-1);
b2.SetValue(2);
graph.RunInSerial();
float dx_, db1_, db2_;
dx.ToHost().get_value(&dx_, 1);
db1.ToHost().get_value(&db1_, 1);
db2.ToHost().get_value(&db2_, 1);
EXPECT_EQ(-2, dx_);
EXPECT_EQ(0, db1_);
EXPECT_EQ(2, db2_);
}
}
TEST_F(TestGraph, AutoRecycle) {
for (auto &it : devices) {
GOUT << "Test graph on device [" << it.first << "]" << std::endl;
auto dev = it.second;
Graph graph(dev.get());
auto &nodes = graph.nodes();
auto &edges = graph.edges();
auto &blocks = graph.blocks();
auto &leaf_blocks = graph.leaf_blocks();
{
Tensor in(Shape{1}, dev);
Tensor mid1(Shape{1}, dev);
Tensor mid2(Shape{1}, dev);
Tensor out(Shape{1}, dev);
Tensor b1(Shape{1}, dev);
Tensor b2(Shape{1}, dev);
Tensor dx(Shape{1}, dev);
Tensor dx1(Shape{1}, dev);
Tensor dx2(Shape{1}, dev);
Tensor dx3(Shape{1}, dev);
Tensor dy1(Shape{1}, dev);
Tensor dy2(Shape{1}, dev);
Tensor dy3(Shape{1}, dev);
Tensor db1(Shape{1}, dev);
Tensor db2(Shape{1}, dev);
// function: (in + b1) * in + (in + b2)
auto op1 = [in, b1, mid1](Context *ctx) mutable {
singa::Add(in, b1, &mid1);
};
auto op2 = [mid1, in, out](Context *ctx) mutable {
singa::EltwiseMult(mid1, in, &out);
};
auto op3 = [in, b2, mid2](Context *ctx) mutable {
singa::Add(in, b2, &mid2);
};
auto op4 = [out, mid2](Context *ctx) mutable {
singa::Add(out, mid2, &out);
};
auto op5 = [out, dy1, dy2](Context *ctx) mutable {
dy1.CopyData(out);
dy2.CopyData(out);
};
auto op6 = [in, mid1, dy1, dy3, dx1](Context *ctx) mutable {
singa::EltwiseMult(dy1, in, &dy3);
singa::EltwiseMult(dy1, mid1, &dx1);
};
auto op7 = [dy3, dx2, db1](Context *ctx) mutable {
dx2.CopyData(dy3);
db1.CopyData(dy3);
};
auto op8 = [dy2, dx3, db2](Context *ctx) mutable {
dx3.CopyData(dy2);
db2.CopyData(dy2);
};
auto op9 = [dx1, dx2, dx](Context *ctx) mutable {
singa::Add(dx1, dx2, &dx);
};
auto op10 = [dx, dx3](Context *ctx) mutable { singa::Add(dx, dx3, &dx); };
graph.AddOperation(op1, {in.block(), b1.block()}, {mid1.block()});
graph.AddOperation(op2, {mid1.block(), in.block()}, {out.block()});
graph.AddOperation(op3, {in.block(), b2.block()}, {mid2.block()});
graph.AddOperation(op4, {out.block(), mid2.block()}, {out.block()});
graph.AddOperation(op5, {out.block()}, {dy1.block(), dy2.block()});
graph.AddOperation(op6, {in.block(), mid1.block(), dy1.block()},
{dy3.block(), dx1.block()});
graph.AddOperation(op7, {dy3.block()}, {dx2.block(), db1.block()});
graph.AddOperation(op8, {dy2.block()}, {dx3.block(), db2.block()});
graph.AddOperation(op9, {dx1.block(), dx2.block()}, {dx.block()});
graph.AddOperation(op10, {dx.block(), dx3.block()}, {dx.block()});
in.SetValue(0);
b1.SetValue(-1);
b2.SetValue(2);
}
EXPECT_EQ(10u, nodes.size());
EXPECT_EQ(21u, edges.size());
EXPECT_EQ(15u, blocks.size());
EXPECT_EQ(3u, leaf_blocks.size());
graph.RunGraph();
auto &begin_nodes = graph.begin_nodes();
auto &next_nodes = graph.next_nodes();
auto &free_blocks = graph.free_blocks();
EXPECT_FALSE(graph.dirty());
EXPECT_EQ(nodes[0], begin_nodes[0]);
EXPECT_EQ(nodes[2], begin_nodes[1]);
EXPECT_EQ(nodes[1], next_nodes[0][0]);
EXPECT_EQ(nodes[3], next_nodes[1][0]);
EXPECT_EQ(nodes[4], next_nodes[3][0]);
EXPECT_EQ(nodes[5], next_nodes[4][0]);
EXPECT_EQ(nodes[7], next_nodes[4][1]);
EXPECT_EQ(nodes[6], next_nodes[5][0]);
EXPECT_EQ(nodes[8], next_nodes[6][0]);
EXPECT_EQ(nodes[9], next_nodes[8][0]);
CheckFreeBlocks(0, blocks, free_blocks[0], IntVec({}));
CheckFreeBlocks(1, blocks, free_blocks[1], IntVec({}));
CheckFreeBlocks(2, blocks, free_blocks[2], IntVec({}));
CheckFreeBlocks(3, blocks, free_blocks[3], IntVec({5}));
CheckFreeBlocks(4, blocks, free_blocks[4], IntVec({3}));
CheckFreeBlocks(5, blocks, free_blocks[5], IntVec({2, 6}));
CheckFreeBlocks(6, blocks, free_blocks[6], IntVec({8, 11}));
CheckFreeBlocks(7, blocks, free_blocks[7], IntVec({7, 13}));
CheckFreeBlocks(8, blocks, free_blocks[8], IntVec({9, 10}));
CheckFreeBlocks(9, blocks, free_blocks[9], IntVec({12, 14}));
// in 0 b1 1 mid1 2 out 3 b2 4
// mid2 5 dy1 6 dy2 7 dy3 8 dx1 9
// dx2 10 db1 11 dx3 12 db2 13 dx 14
bool state[15] = {true, true, false, false, true, false, false, false,
false, false, false, false, false, false, false};
for (auto it : blocks) {
int id = it.second->id();
EXPECT_EQ(state[id], it.first->initialized())
<< "The memory of the block[" << id << "] is not properly recycled"
<< std::endl;
}
}
}