| #include <gtest/gtest.h> | |
| #include <torch/csrc/autograd/generated/variable_factories.h> | |
| #include <torch/csrc/jit/ir/irparser.h> | |
| #include "torch/csrc/jit/frontend/ir_emitter.h" | |
| #include "torch/csrc/jit/ir/alias_analysis.h" | |
| #include "torch/csrc/jit/runtime/custom_operator.h" | |
| #include "torch/csrc/utils/memory.h" | |
| namespace torch { | |
| namespace jit { | |
| inline c10::AliasAnalysisKind aliasAnalysisFromSchema() { | |
| return c10::AliasAnalysisKind::FROM_SCHEMA; | |
| } | |
| // Fixture to set up a graph and make assertions clearer | |
| class TopologicalMoveTest : public ::testing::Test { | |
| protected: | |
| TopologicalMoveTest() { | |
| createGraph(); | |
| aliasDb = torch::make_unique<AliasDb>(graph); | |
| } | |
| // Nodes are named after their output. | |
| // e.g. "a" is an alias for "the node that outputs the value `a`" | |
| void createGraph() { | |
| graph = std::make_shared<Graph>(); | |
| createNode("a", {}); | |
| createNode("b", {"a"}); | |
| createNode("c", {}); | |
| createNode("d", {"a", "b"}); | |
| createNode("e", {"c", "b"}); | |
| createNode("f", {"e"}); | |
| createNode("g", {"e"}); | |
| createNode("h", {"g"}); | |
| createNode("i", {"g"}); | |
| createNode("j", {"i"}); | |
| createNode("k", {"i"}); | |
| createNode("l", {"a"}); | |
| createNode("m", {}, {"l"}); // block depends on l | |
| createNode("n", {"m"}); | |
| createNode("o", {"n"}); | |
| createNode("p", {}); | |
| createNode("q", {}); | |
| createNode("r", {"q"}); | |
| createNode("s", {"q"}); | |
| graph->lint(); | |
| } | |
| void createNode( | |
| const std::string& name, | |
| const std::vector<std::string>& inputNames, | |
| const std::vector<std::string>& blockInputNames = {}) { | |
| std::vector<Value*> inputs; | |
| for (const auto& name_ : inputNames) { | |
| inputs.push_back(nodes.at(name_)->output()); | |
| } | |
| auto node = graph->appendNode(graph->create(prim::AutogradZero, inputs)); | |
| node->output()->setDebugName(name); | |
| nodes[name] = node; | |
| if (blockInputNames.size() != 0) { | |
| node->addBlock(); | |
| std::vector<Value*> blockDeps; | |
| for (const auto& name_ : blockInputNames) { | |
| blockDeps.push_back(nodes.at(name_)->output()); | |
| } | |
| auto block = node->blocks().at(0); | |
| block->appendNode(graph->create(prim::AutogradZero, blockDeps)); | |
| } | |
| } | |
| bool moveBeforeTopologicallyValid( | |
| const std::string& toInsert, | |
| const std::string& insertPoint) { | |
| std::function<bool(Node*, Node*)> func = | |
| [this](Node* toInsert, Node* insertPoint) { | |
| return aliasDb->moveBeforeTopologicallyValid(toInsert, insertPoint); | |
| }; | |
| return moveWithChecks(toInsert, insertPoint, func); | |
| } | |
| bool moveAfterTopologicallyValid( | |
| const std::string& toInsert, | |
| const std::string& insertPoint) { | |
| std::function<bool(Node*, Node*)> func = | |
| [this](Node* toInsert, Node* insertPoint) { | |
| return aliasDb->moveAfterTopologicallyValid(toInsert, insertPoint); | |
| }; | |
| return moveWithChecks(toInsert, insertPoint, func); | |
| } | |
| bool moveWithChecks( | |
| const std::string& toInsert, | |
| const std::string& insertPoint, | |
| std::function<bool(Node*, Node*)> func) { | |
| auto n = nodes.at(toInsert); | |
| auto insert = nodes.at(insertPoint); | |
| bool isAfter = n->isAfter(insert); | |
| std::vector<Node*> originalOrdering; | |
| Node* original = isAfter ? n->next() : n->prev(); | |
| auto curNode = original; | |
| while (curNode != n->owningBlock()->return_node()) { | |
| originalOrdering.push_back(curNode); | |
| if (isAfter) { | |
| curNode = curNode->next(); | |
| } else { | |
| curNode = curNode->prev(); | |
| } | |
| } | |
| const auto couldMove = func(n, insert); | |
| // Check the graph is okay | |
| graph->lint(); | |
| // If this is the picture of nodes | |
| // <some nodes> ... toInsert ... <some more nodes> ... insertPoint | |
| // ^----------^ check that these nodes haven't moved | |
| curNode = original; | |
| size_t idx = 0; | |
| while (curNode != n->owningBlock()->return_node()) { | |
| EXPECT_TRUE(originalOrdering[idx] == curNode); | |
| if (isAfter) { | |
| curNode = curNode->next(); | |
| } else { | |
| curNode = curNode->prev(); | |
| } | |
| idx++; | |
| } | |
| return couldMove; | |
| } | |
| void checkPostCondition( | |
| const std::string& toInsert, | |
| const std::string& insertPoint, | |
| bool after) { | |
| if (after) { | |
| EXPECT_EQ(nodes.at(toInsert)->prev(), nodes.at(insertPoint)); | |
| } else { | |
| EXPECT_EQ(nodes.at(toInsert)->next(), nodes.at(insertPoint)); | |
| } | |
| } | |
| std::shared_ptr<Graph> graph; | |
| std::unique_ptr<AliasDb> aliasDb; | |
| std::unordered_map<std::string, Node*> nodes; | |
| }; | |
| TEST_F(TopologicalMoveTest, SplitsDeps) { | |
| // Check that we are removing `this`'s deps properly when we need to split | |
| // `this` and deps (see code for what the hell that means) | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("q", "s")); | |
| checkPostCondition("q", "s", false); | |
| } | |
| // Move after | |
| TEST_F(TopologicalMoveTest, MoveAfterBackwardSimple) { | |
| // Simple move backward | |
| EXPECT_TRUE(moveAfterTopologicallyValid("c", "a")); | |
| checkPostCondition("c", "a", true); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterBackwardInvalid) { | |
| // simple invalid move backward | |
| EXPECT_FALSE(moveAfterTopologicallyValid("d", "a")); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterNoOp) { | |
| // doesn't actually move anything | |
| EXPECT_TRUE(moveAfterTopologicallyValid("f", "e")); | |
| checkPostCondition("f", "e", true); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterBackwardMultipleDeps) { | |
| // move backward with multiple dependencies | |
| EXPECT_TRUE(moveAfterTopologicallyValid("e", "c")); | |
| checkPostCondition("e", "c", true); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterBackwardNonZeroWorkingSet) { | |
| // Move backward with non-zero working set | |
| EXPECT_TRUE(moveAfterTopologicallyValid("k", "f")); | |
| checkPostCondition("k", "f", true); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterForwardSimple) { | |
| // Simple move forward | |
| EXPECT_TRUE(moveAfterTopologicallyValid("c", "d")); | |
| checkPostCondition("c", "d", true); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveAfterForwardNonZeroWorkingSet) { | |
| // Move forward with non-zero working set | |
| EXPECT_TRUE(moveAfterTopologicallyValid("f", "l")); | |
| checkPostCondition("f", "l", true); | |
| } | |
| // Move before | |
| TEST_F(TopologicalMoveTest, MoveBeforeForwardSimple) { | |
| // Simple move forward | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("b", "d")); | |
| checkPostCondition("b", "d", false); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveBeforeBackwardSimple) { | |
| // Simple move backward | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("c", "a")); | |
| checkPostCondition("c", "a", false); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveBeforeNoOp) { | |
| // doesn't actually move anything | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("a", "b")); | |
| checkPostCondition("a", "b", false); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveBeforeForwardWithDeps) { | |
| // move forward with deps | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("f", "m")); | |
| checkPostCondition("f", "m", false); | |
| } | |
| TEST_F(TopologicalMoveTest, MoveBeforeBackwardWithDeps) { | |
| // move backward with deps | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("l", "f")); | |
| checkPostCondition("l", "f", false); | |
| } | |
| // check that dependencies in blocks are recognized | |
| TEST_F(TopologicalMoveTest, DepsDisallowMove) { | |
| EXPECT_FALSE(moveAfterTopologicallyValid("l", "m")); | |
| EXPECT_FALSE(moveBeforeTopologicallyValid("m", "l")); | |
| EXPECT_FALSE(moveAfterTopologicallyValid("n", "l")); | |
| EXPECT_FALSE(moveBeforeTopologicallyValid("l", "n")); | |
| } | |
| // Test that moveAfter(n) and moveBefore(n->next()) are not necessarily | |
| // equivalent. Here, the dependency ordering is n -> o -> p. So we can't | |
| // move `n` after `o`, but we can move `n` before `p` (which pushes `o` after | |
| // `p`) | |
| TEST_F(TopologicalMoveTest, MoveAfterBeforeWithDeps) { | |
| EXPECT_FALSE(moveAfterTopologicallyValid("n", "o")); | |
| EXPECT_TRUE(moveBeforeTopologicallyValid("o", "p")); | |
| checkPostCondition("o", "p", false); | |
| } | |
| namespace { | |
| Node* insertIf( | |
| Graph& g, | |
| Value* condValue, | |
| std::function<std::vector<Value*>()> trueInst, | |
| std::function<std::vector<Value*>()> falseInst) { | |
| auto if_ = g.insertNode(g.create(prim::If, 0)); | |
| if_->addInput(condValue); // condition value | |
| auto trueBlock = if_->addBlock(); | |
| auto falseBlock = if_->addBlock(); | |
| { | |
| // Mutate in true block | |
| WithInsertPoint g(trueBlock); | |
| auto outputs = trueInst(); | |
| for (auto output : outputs) { | |
| trueBlock->registerOutput(output); | |
| } | |
| } | |
| { | |
| WithInsertPoint g(falseBlock); | |
| auto outputs = falseInst(); | |
| for (auto output : outputs) { | |
| falseBlock->registerOutput(output); | |
| } | |
| } | |
| EXPECT_TRUE(trueBlock->outputs().size() == falseBlock->outputs().size()); | |
| for (auto output : trueBlock->outputs()) { | |
| if_->addOutput()->setType(output->type()); | |
| } | |
| return if_; | |
| } | |
| template <class Exception, class Functor> | |
| inline void expectThrows(Functor&& functor, const char* expectMessageContains) { | |
| try { | |
| std::forward<Functor>(functor)(); | |
| } catch (const Exception& e) { | |
| if (std::string(e.what()).find(expectMessageContains) == | |
| std::string::npos) { | |
| AT_ERROR( | |
| "Expected error message to contain \"", | |
| expectMessageContains, | |
| "\" but error message was: ", | |
| e.what()); | |
| } | |
| return; | |
| } | |
| AT_ERROR( | |
| "Expected to throw exception containing \"", | |
| expectMessageContains, | |
| "\" but didn't throw"); | |
| } | |
| } // namespace | |
| TEST(AliasAnalysisTest, AliasingMutationBlocksMoves) { | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->addInput(); | |
| // addsB = b + b | |
| // c = a + b | |
| // a += b | |
| // d = c + c | |
| auto addsB = graph->insert(aten::add, {b, b}); | |
| auto c = graph->insert(aten::add, {a, b}); | |
| auto aMut = graph->insert(aten::add_, {a, b}); | |
| auto d = graph->insert(aten::add, {c, c}); | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| // Can't move past a mutation of a used value | |
| EXPECT_FALSE(aliasDb.moveAfterTopologicallyValid(c->node(), aMut->node())); | |
| EXPECT_TRUE(aliasDb.moveAfterTopologicallyValid(d->node(), c->node())); | |
| // b should alias to a (since they are both inputs) | |
| EXPECT_FALSE( | |
| aliasDb.moveAfterTopologicallyValid(addsB->node(), aMut->node())); | |
| EXPECT_TRUE(aliasDb.moveAfterTopologicallyValid(addsB->node(), c->node())); | |
| graph->lint(); | |
| } | |
| TEST(AliasAnalysisTest, AliasingMutationBlocksMoves2) { | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->addInput(); | |
| auto constant = graph->insertConstant(1); | |
| auto fresh = graph->insert(aten::rand, {constant}); | |
| auto usesB = graph->insert(aten::add, {b, fresh}); | |
| auto aliasesB = graph->insert(aten::select, {a, constant, constant}); | |
| auto mutatesAliasOfB = graph->insert(aten::add_, {aliasesB, fresh}); | |
| graph->insert(aten::add, {fresh, aliasesB}); | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.moveAfterTopologicallyValid( | |
| aliasesB->node(), mutatesAliasOfB->node())); | |
| EXPECT_FALSE(aliasDb.moveAfterTopologicallyValid( | |
| usesB->node(), mutatesAliasOfB->node())); | |
| } | |
| TEST(AliasAnalysisTest, SideEffectsBlockMoves) { | |
| // Test moves across side effectful nodes | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto print1 = graph->insertNode(graph->create(prim::Print, {a}, 0)); | |
| WithInsertPoint guard(print1); | |
| auto print2 = graph->insertNode(graph->create(prim::Print, {a, a}, 0)); | |
| AliasDb aliasDb(graph); | |
| // def foo(a): | |
| // print2(a, a) | |
| // print1(a) | |
| // test moving across each other | |
| EXPECT_FALSE(aliasDb.moveAfterTopologicallyValid(print2, print1)); | |
| EXPECT_FALSE(aliasDb.moveBeforeTopologicallyValid(print1, print2)); | |
| // test moving where they already are | |
| EXPECT_TRUE(aliasDb.moveBeforeTopologicallyValid(print2, print1)); | |
| EXPECT_TRUE(aliasDb.moveAfterTopologicallyValid(print1, print2)); | |
| graph->insertNode(graph->create(prim::MakeTestTensor, {}, 1)); | |
| AliasDb aliasDb2(graph); | |
| // def foo(a): | |
| // print2(a, a) | |
| // non_side_effectful = makeTestTensor() | |
| // print1(a) | |
| // test moving with a side effectful node between | |
| EXPECT_FALSE(aliasDb2.moveAfterTopologicallyValid(print2, print1)); | |
| EXPECT_FALSE(aliasDb2.moveBeforeTopologicallyValid(print2, print1)); | |
| EXPECT_FALSE(aliasDb2.moveAfterTopologicallyValid(print1, print2)); | |
| EXPECT_FALSE(aliasDb2.moveBeforeTopologicallyValid(print1, print2)); | |
| } | |
| TEST(AliasAnalysisTest, MovingAcrossInnerBlocks) { | |
| // Test moves across inner blocks | |
| // a = rand(1) | |
| // b = rand(1) | |
| // if True: | |
| // a.add_(b) | |
| // c = a + b | |
| auto graph = std::make_shared<Graph>(); | |
| auto constant = graph->insertConstant(1); | |
| auto a = graph->insert(aten::rand, {constant}); | |
| auto b = graph->insert(aten::rand, {constant}); | |
| auto if_ = insertIf( | |
| *graph, | |
| constant, | |
| [&]() -> std::vector<Value*> { | |
| auto aMut = graph->insert(aten::add_, {a, b}); | |
| return {aMut}; | |
| }, | |
| [&]() -> std::vector<Value*> { return {a}; }); | |
| auto c = graph->insert(aten::add, {a, b}); | |
| graph->lint(); | |
| // we should not be able to move `c` before the if statement, since it | |
| // may write to `a`. | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.moveBeforeTopologicallyValid(c->node(), if_)); | |
| } | |
| TEST(AliasAnalysisTest, NoneHasNoWriters) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %opt : Tensor? = prim::Constant() | |
| %out : Tensor = prim::unchecked_unwrap_optional(%opt) | |
| %ret.2 : Tensor = aten::div(%out, %out, %out) | |
| return (%opt, %out, %ret.2) | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.hasWriters(vmap["opt"]->node())); | |
| } | |
| TEST(AliasAnalysisTest, SafeToChangeAliasingRelationship) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%x : Tensor): | |
| %3 : int = prim::Constant[value=1]() | |
| %2 : int = prim::Constant[value=0]() | |
| %b : Tensor = aten::add(%x, %2, %3) | |
| %c : Tensor = aten::add(%x, %2, %3) | |
| %d : Tensor = aten::add(%x, %2, %3) | |
| %e : Tensor = aten::add(%x, %2, %3) | |
| %f : Tensor[] = prim::ListConstruct(%e) | |
| %14 : (Tensor, Tensor) = prim::TupleConstruct(%b, %c) | |
| return (%14) | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| // x, b, c escape scope, so we can't introduce an aliasing relationship | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["x"], vmap["b"])); | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["b"], vmap["x"])); | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["b"], vmap["c"])); | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["c"], vmap["b"])); | |
| // e aliases the wildcard set because it's contained in a list | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["e"], vmap["x"])); | |
| EXPECT_FALSE(aliasDb.safeToChangeAliasingRelationship(vmap["x"], vmap["e"])); | |
| // d is a temporary with no writers, safe to change aliasing relationship | |
| // here | |
| EXPECT_TRUE(aliasDb.safeToChangeAliasingRelationship(vmap["c"], vmap["d"])); | |
| EXPECT_TRUE(aliasDb.safeToChangeAliasingRelationship(vmap["d"], vmap["c"])); | |
| } | |
| TEST(WriteTrackingTest, Basic) { | |
| RegisterOperators reg({Operator( | |
| "prim::creates_alias(Tensor(a) x) -> Tensor(a)", | |
| [](Stack* s) {}, | |
| aliasAnalysisFromSchema())}); | |
| const auto creates_alias = Symbol::fromQualString("prim::creates_alias"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->addInput(); | |
| // aten::add(%b, %b) | |
| // aten::add_(%a, %b) | |
| // foo::creates_alias(%a) | |
| auto pureNode = graph->insert(aten::add, {b, b})->node(); | |
| auto writingNode = graph->insert(aten::add_, {a, b})->node(); | |
| auto node3 = graph->insert(creates_alias, {a})->node(); | |
| auto aAlias = node3->output(); | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(aliasDb.mayAlias(aAlias, a)); | |
| EXPECT_TRUE(aliasDb.mayAlias(a, b)); | |
| EXPECT_FALSE( | |
| aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{a})); | |
| EXPECT_FALSE( | |
| aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{b})); | |
| EXPECT_TRUE( | |
| aliasDb.writesToAlias(writingNode, std::unordered_set<const Value*>{a})); | |
| EXPECT_TRUE(aliasDb.writesToAlias( | |
| writingNode, std::unordered_set<const Value*>{a, b})); | |
| EXPECT_TRUE(aliasDb.writesToAlias( | |
| writingNode, std::unordered_set<const Value*>{aAlias})); | |
| } | |
| TEST(WriteTrackingTest, IsMutable) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(%x: Tensor): | |
| %b : Tensor = aten::relu_(%x) | |
| return (%b) | |
| )IR", | |
| &*graph); | |
| auto node_iter = graph->block()->nodes().begin(); | |
| auto relu = *node_iter; | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(aliasDb.isMutable(relu)); | |
| } | |
| TEST(WriteTrackingTest, IsImmutable) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(%x: Tensor, %y : Tensor): | |
| %b : Tensor = aten::mul(%x, %y) | |
| return (%b) | |
| )IR", | |
| &*graph); | |
| auto node_iter = graph->block()->nodes().begin(); | |
| auto mul = *node_iter; | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.isMutable(mul)); | |
| } | |
| TEST(WriteTrackingTest, HasWriters) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%x: Tensor, %y : Tensor): | |
| %c1 : int = prim::Constant[value=1]() | |
| %b : Tensor = aten::add_(%x, %y, %c1) | |
| return (%b) | |
| )IR", | |
| &*graph, | |
| vmap); | |
| auto add = vmap["b"]->node(); | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(aliasDb.hasWriters(add)); | |
| EXPECT_TRUE(aliasDb.isMutable(add)); | |
| } | |
| TEST(ContainerAliasingTest, MayContainAlias) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%inp: Tensor[]): | |
| %x : str = prim::Constant[value="a"]() | |
| %y : Tensor = prim::Constant() | |
| %z : Tensor = prim::Constant() | |
| %a : (Tensor) = prim::TupleConstruct(%y) | |
| %b : Dict(str, Tensor) = prim::DictConstruct(%x, %y) | |
| %c : Tensor[] = prim::ListConstruct(%y) | |
| return (%a, %b, %c) | |
| )IR", | |
| &*graph, | |
| vmap); | |
| auto str_output = vmap["x"]; | |
| auto ten_output = vmap["y"]; | |
| auto local_var = vmap["z"]; | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(graph->outputs().size() == 3); | |
| for (auto out : graph->outputs()) { | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_output, out)); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(local_var, out)); | |
| } | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_output, graph->inputs())); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(local_var, graph->inputs())); | |
| EXPECT_TRUE(aliasDb.mayContainAlias({ten_output}, graph->outputs())); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(str_output, graph->outputs())); | |
| } | |
| TEST(ContainerAliasingTest, PrimitveValuesDontAliasContainers) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %x : str = prim::Constant[value="a"]() | |
| %y : int = prim::Constant[value=1]() | |
| %a : (int) = prim::TupleConstruct(%y) | |
| %b : Dict(str, int) = prim::DictConstruct(%x, %y) | |
| %c : int[] = prim::ListConstruct(%y) | |
| return (%a, %b, %c) | |
| )IR", | |
| &*graph); | |
| auto node_iter = graph->block()->nodes().begin(); | |
| node_iter++; // string | |
| Node* int_node = *node_iter++; | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(graph->outputs().size() == 3); | |
| // primitive values don't need to alias container | |
| for (auto out : graph->outputs()) { | |
| EXPECT_FALSE(aliasDb.mayContainAlias(int_node->output(), out)); | |
| } | |
| } | |
| TEST(ContainerAliasingTest, InputsCanAliasOutputs) { | |
| // Test input aliasing | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(%x: Tensor, %y: Tensor): | |
| %a : (Tensor) = prim::TupleConstruct(%x) | |
| return (%a) | |
| )IR", | |
| &*graph); | |
| auto node_iter = graph->block()->nodes().begin(); | |
| auto tuple_node = *node_iter; | |
| AliasDb aliasDb(graph); | |
| for (auto input : graph->inputs()) { | |
| EXPECT_TRUE(aliasDb.mayContainAlias(input, tuple_node->output())); | |
| } | |
| EXPECT_TRUE(aliasDb.mayContainAlias(graph->inputs(), graph->outputs())); | |
| } | |
| // Test tuple that doesn't come from construct | |
| TEST(ContainerAliasingTest, NestedTupleConstruct) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(%x : int, | |
| %y : Tensor, | |
| %z : Tensor): | |
| %3 : int = prim::Constant[value=1]() | |
| %4 : bool = aten::eq(%x, %3) | |
| %a : (Tensor) = prim::If(%4) | |
| block0(): | |
| %a.1 : (Tensor) = prim::TupleConstruct(%y) | |
| -> (%a.1) | |
| block1(): | |
| %a.2 : (Tensor) = prim::TupleConstruct(%z) | |
| -> (%a.2) | |
| return (%a) | |
| )IR", | |
| &*graph); | |
| AliasDb aliasDb(graph); | |
| for (auto input : graph->inputs()) { | |
| if (input->type() == IntType::get()) { | |
| continue; | |
| } | |
| EXPECT_TRUE(aliasDb.mayContainAlias(input, graph->outputs().at(0))); | |
| } | |
| } | |
| // test nested types | |
| TEST(ContainerAliasingTest, NestedTypes) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %a : Tensor = prim::MakeTestTensor() | |
| %a_list : Tensor[] = prim::ListConstruct(%a) | |
| %b : Tensor = prim::MakeTestTensor() | |
| %b_list : Tensor[] = prim::ListConstruct(%b) | |
| %13 : (Tensor[], Tensor[]) = prim::TupleConstruct(%a_list, %b_list) | |
| return (%13) | |
| )IR", | |
| &*graph); | |
| AliasDb aliasDb(graph); | |
| auto g_output = graph->outputs().at(0); | |
| auto list_2 = g_output->node()->inputs().at(0); | |
| auto list_1 = g_output->node()->inputs().at(1); | |
| // TODO FIX assume conservatively for now | |
| EXPECT_TRUE(aliasDb.mayContainAlias(list_1, list_2)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(list_2, list_1)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(list_1, g_output)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(list_2, g_output)); | |
| } | |
| // simple example | |
| TEST(ContainerAliasingTest, Simple) { | |
| auto graph = std::make_shared<Graph>(); | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %0 : Tensor = prim::Constant() | |
| %1 : Tensor = prim::Constant() | |
| %13 : (Tensor) = prim::TupleConstruct(%0) | |
| return (%13) | |
| )IR", | |
| &*graph); | |
| AliasDb aliasDb(graph); | |
| auto node_iter = graph->block()->nodes().begin(); | |
| auto first_ten = *node_iter++; | |
| auto second_ten = *node_iter++; | |
| auto tup_node = *node_iter; | |
| EXPECT_TRUE(aliasDb.mayContainAlias(first_ten->output(), tup_node->output())); | |
| EXPECT_TRUE( | |
| !aliasDb.mayContainAlias(second_ten->output(), tup_node->output())); | |
| std::vector<Value*> first_st = {first_ten->output()}; | |
| std::vector<Value*> second_st = {second_ten->output()}; | |
| std::vector<Value*> tup_st = {tup_node->output()}; | |
| EXPECT_TRUE(aliasDb.mayContainAlias(first_st, tup_st)); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(first_st, second_st)); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(second_st, tup_st)); | |
| } | |
| TEST(ContainerAliasingTest, Lists) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %x : str = prim::Constant[value="a"]() | |
| %y : Tensor = prim::Constant() | |
| %c : Tensor[] = prim::ListConstruct(%y) | |
| %d : Tensor[] = prim::ListConstruct(%y) | |
| return (%c, %d) | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto x = vmap["x"]; | |
| auto c = vmap["c"]; | |
| EXPECT_FALSE(aliasDb.mayContainAlias(x, c)); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(c, x)); | |
| auto d = vmap["d"]; | |
| EXPECT_TRUE(aliasDb.mayContainAlias(d, c)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(c, d)); | |
| } | |
| TEST(ContainerAliasingTest, Lists2) { | |
| // Test list container aliasing | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %0 : int = prim::Constant[value=2]() | |
| %1 : int = prim::Constant[value=3]() | |
| %2 : int[] = prim::ListConstruct(%0, %1) | |
| %x : Tensor = prim::MakeTestTensor() | |
| %12 : int[] = prim::ListConstruct(%0, %1) | |
| %y : Tensor = prim::MakeTestTensor() | |
| %22 : int[] = prim::ListConstruct(%0, %1) | |
| %z : Tensor = prim::MakeTestTensor() | |
| %32 : int[] = prim::ListConstruct(%0, %1) | |
| %fresh : Tensor = prim::MakeTestTensor() | |
| %foo : Tensor[] = prim::ListConstruct(%x, %y) | |
| %43 : Tensor[] = aten::append(%foo, %z) | |
| return () | |
| )IR", | |
| graph.get(), | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto x = vmap["x"]; | |
| auto y = vmap["y"]; | |
| auto z = vmap["z"]; | |
| // Tensors x, y, and z went into a list, so they all may alias each other. | |
| EXPECT_TRUE(aliasDb.mayAlias(x, y)); | |
| EXPECT_TRUE(aliasDb.mayAlias(y, z)); | |
| EXPECT_TRUE(aliasDb.mayAlias(x, z)); | |
| // But we know `fresh` didn't go into a list, so x, y, and z should not | |
| // alias it. | |
| auto fresh = vmap["fresh"]; | |
| EXPECT_FALSE(aliasDb.mayAlias(x, fresh)); | |
| EXPECT_FALSE(aliasDb.mayAlias(y, fresh)); | |
| EXPECT_FALSE(aliasDb.mayAlias(z, fresh)); | |
| } | |
| TEST(ContainerAliasingTest, Conservative) { | |
| // test "conservative" analysis writes to the inside of a container. | |
| auto ops = torch::RegisterOperators( | |
| "custom::conservative", [](torch::List<at::Tensor> in) { return in; }); | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %0 : int = prim::Constant[value=2]() | |
| %1 : int = prim::Constant[value=3]() | |
| %2 : int[] = prim::ListConstruct(%0, %1) | |
| %11 : Tensor = prim::MakeTestTensor() | |
| %12 : Tensor[] = prim::ListConstruct(%11) | |
| %out : Tensor[] = custom::conservative(%12) | |
| %ret.2 : Tensor = aten::div(%11, %11) | |
| return () | |
| )IR", | |
| graph.get(), | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto conservativeOp = vmap["out"]->node(); | |
| auto tensor = vmap["11"]; | |
| EXPECT_TRUE(aliasDb.writesToAlias(conservativeOp, ValueSet{tensor})); | |
| } | |
| TEST(ContainerAliasingTest, MovesAcrossContainedWrites) { | |
| auto ops = torch::RegisterOperators().op( | |
| "uses::list", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](torch::List<at::Tensor> in) { | |
| return torch::rand({2, 3}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| // Write to the inside of a list. Check that we can't reorder a | |
| // print across it. | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %35 : int = prim::Constant[value=1]() | |
| %0 : int = prim::Constant[value=2]() | |
| %1 : int = prim::Constant[value=3]() | |
| %23 : int = prim::Constant[value=0]() | |
| %2 : int[] = prim::ListConstruct(%0, %1) | |
| %11 : Tensor = prim::MakeTestTensor() | |
| %12 : int[] = prim::ListConstruct(%0, %1) | |
| %21 : Tensor = prim::MakeTestTensor() | |
| %l : Tensor[] = prim::ListConstruct(%11, %21) | |
| %24 : Tensor = aten::select(%l, %23) | |
| %25 : int[] = prim::ListConstruct(%0, %1) | |
| %34 : Tensor = prim::MakeTestTensor() | |
| %36 : Tensor = aten::add_(%24, %34, %35) | |
| %37 : Tensor = uses::list(%l) | |
| return (%37) | |
| )IR", | |
| graph.get(), | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto listUse = vmap["37"]->node(); | |
| auto internalWrite = vmap["36"]->node(); | |
| EXPECT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite)); | |
| } | |
| TEST(ContainerAliasingTest, MovesAcrossContainedWritesNested) { | |
| // The same as above, but with a nested list | |
| auto ops = torch::RegisterOperators().op( | |
| "uses::list", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](torch::List<at::Tensor> in) { | |
| return torch::rand({2, 3}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| // Write to the inside of a list. Check that we can't reorder a | |
| // print across it. | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(): | |
| %38 : int = prim::Constant[value=1]() | |
| %0 : int = prim::Constant[value=2]() | |
| %1 : int = prim::Constant[value=3]() | |
| %24 : int = prim::Constant[value=0]() | |
| %2 : int[] = prim::ListConstruct(%0, %1) | |
| %11 : Tensor = prim::MakeTestTensor() | |
| %12 : int[] = prim::ListConstruct(%0, %1) | |
| %21 : Tensor = prim::MakeTestTensor() | |
| %l : Tensor[] = prim::ListConstruct(%11, %21) | |
| %25 : Tensor = aten::select(%l, %24) | |
| %27 : Tensor = aten::select(%25, %24, %24) | |
| %28 : int[] = prim::ListConstruct(%0, %1) | |
| %37 : Tensor = prim::MakeTestTensor() | |
| %39 : Tensor = aten::add_(%27, %37, %38) | |
| %40 : Tensor = uses::list(%l) | |
| return (%40) | |
| )IR", | |
| graph.get(), | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto listUse = vmap["40"]->node(); | |
| auto internalWrite = vmap["39"]->node(); | |
| EXPECT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite)); | |
| } | |
| TEST(WildcardsTest, Basic) { | |
| RegisterOperators reg( | |
| {Operator( | |
| "prim::returns_wildcard(Tensor a) -> Tensor(*)", | |
| [](Stack* stack) {}, | |
| aliasAnalysisFromSchema()), | |
| Operator( | |
| "prim::writes(Tensor(z!) a) -> Tensor(a)", | |
| [](Stack* stack) {}, | |
| aliasAnalysisFromSchema())}); | |
| const auto returns_wildcard = | |
| Symbol::fromQualString("prim::returns_wildcard"); | |
| const auto writes = Symbol::fromQualString("prim::writes"); | |
| auto graph = std::make_shared<Graph>(); | |
| const auto a = graph->addInput(); | |
| const auto constant = graph->insertConstant(1); | |
| const auto fresh = graph->insert(aten::rand, {constant}); | |
| const auto fresh2 = graph->insert(aten::rand, {constant}); | |
| const auto wildcard = graph->insert(returns_wildcard, {fresh}); | |
| { | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.mayAlias(a, fresh)); | |
| EXPECT_FALSE(aliasDb.mayAlias(wildcard, fresh)); | |
| EXPECT_TRUE(aliasDb.mayAlias(wildcard, a)); | |
| EXPECT_FALSE(aliasDb.mayAlias(ValueSet{wildcard}, ValueSet{})); | |
| EXPECT_FALSE(aliasDb.hasWriters(wildcard->node())); | |
| } | |
| graph->insert(writes, {fresh2})->node(); | |
| { | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| EXPECT_FALSE(aliasDb.hasWriters(wildcard->node())); | |
| } | |
| const auto wildcardWrite = graph->insert(writes, {wildcard})->node(); | |
| { | |
| graph->lint(); | |
| AliasDb aliasDb(graph); | |
| // Test writes to wildcards | |
| EXPECT_FALSE(aliasDb.writesToAlias( | |
| wildcardWrite, std::unordered_set<const Value*>{fresh})); | |
| EXPECT_FALSE(aliasDb.writesToAlias( | |
| wildcardWrite, std::unordered_set<const Value*>{fresh2})); | |
| EXPECT_TRUE(aliasDb.writesToAlias( | |
| wildcardWrite, std::unordered_set<const Value*>{a})); | |
| EXPECT_TRUE(aliasDb.hasWriters(wildcard->node())); | |
| } | |
| } | |
| // test that wildcards are correctly divided by type | |
| TEST(WildcardsTest, TypeIsolation) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%ten_list : Tensor[], %int_list : int[], %opt_ten_list : Tensor[]?): | |
| %ten : Tensor = prim::Constant() | |
| %4 : Tensor[] = aten::append(%ten_list, %ten) | |
| %ten_ten_list : Tensor[][] = prim::Constant() | |
| %int_int_list : int[][] = prim::Constant() | |
| return () | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto opt_ten_list = vmap["opt_ten_list"]; | |
| auto ten_list = vmap["ten_list"]; | |
| auto int_list = vmap["int_list"]; | |
| EXPECT_FALSE(aliasDb.hasWriters(int_list)); | |
| EXPECT_TRUE(aliasDb.hasWriters(opt_ten_list)); | |
| EXPECT_TRUE(aliasDb.hasWriters(ten_list)); | |
| EXPECT_FALSE(aliasDb.mayContainAlias(int_list, opt_ten_list)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_list, opt_ten_list)); | |
| EXPECT_TRUE(aliasDb.mayAlias(ten_list, opt_ten_list)); | |
| auto list_of_tensor_lists = vmap["ten_ten_list"]; | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_list, list_of_tensor_lists)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_list, vmap["ten"])); | |
| EXPECT_TRUE( | |
| !aliasDb.mayContainAlias(vmap["int_int_list"], list_of_tensor_lists)); | |
| } | |
| // test invariant container aliasing | |
| // the containers of different type cannot alias each other, | |
| // however they may contain elements which alias each other | |
| TEST(WildcardsTest, InvariantContainerAliasing) { | |
| { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%ten_list : Tensor[], %ten_opt_list : Tensor?[]): | |
| %ten : Tensor = prim::Constant() | |
| %4 : Tensor[] = aten::append(%ten_list, %ten) | |
| return () | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| auto ten_opt_list = vmap["ten_opt_list"]; | |
| auto ten_list = vmap["ten_list"]; | |
| EXPECT_FALSE(aliasDb.hasWriters(ten_opt_list)); | |
| EXPECT_TRUE(aliasDb.hasWriters(ten_list)); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(ten_list, ten_opt_list)); | |
| EXPECT_FALSE(aliasDb.mayAlias(ten_list, ten_opt_list)); | |
| } | |
| { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%float_3D : Float(*, *, *), %float_2D : Float(*, *)): | |
| return () | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(aliasDb.mayAlias(vmap["float_3D"], vmap["float_2D"])); | |
| } | |
| { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| parseIR( | |
| R"IR( | |
| graph(%float_3D_list : Float(*, *, *)[], %float_2D_list : Float(*, *)[], %ten: Tensor): | |
| return () | |
| )IR", | |
| &*graph, | |
| vmap); | |
| AliasDb aliasDb(graph); | |
| EXPECT_TRUE(aliasDb.mayAlias(vmap["float_3D_list"], vmap["float_2D_list"])); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(vmap["float_3D_list"], vmap["ten"])); | |
| EXPECT_TRUE(aliasDb.mayContainAlias(vmap["float_2D_list"], vmap["ten"])); | |
| } | |
| } | |
| TEST(AliasRegistrationTest, ConservativeWithInferredSchema) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand1", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::CONSERVATIVE)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand1"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // Conservatively we assume there is a reference | |
| EXPECT_TRUE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, ConservativeWithSpecifiedSchema) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand2(Tensor arg1) -> Tensor", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::CONSERVATIVE)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand2"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // Conservatively we assume there is a reference | |
| EXPECT_TRUE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, ConservativeWithAliasingAnnotationsShouldError) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand3(Tensor(a) arg1) -> Tensor(b)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::CONSERVATIVE)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand3"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| graph->insert(rand_op, {a}); | |
| // Registration time is okay, but throw exception when fetch from | |
| // registration. | |
| expectThrows<c10::Error>( | |
| [&graph] { AliasDb aliasDb(graph); }, | |
| "Tried to register operator foo::rand3(Tensor(a) arg1) -> (Tensor(b)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA"); | |
| } | |
| TEST(AliasRegistrationTest, ConservativeWithAliasingAnnotationsShouldError2) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand4(Tensor(a) arg1) -> Tensor(a)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::CONSERVATIVE)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand4"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| graph->insert(rand_op, {a}); | |
| // Registration time is okay, but throw exception when fetch from | |
| // registration. | |
| expectThrows<c10::Error>( | |
| [&graph] { AliasDb aliasDb(graph); }, | |
| "Tried to register operator foo::rand4(Tensor(a) arg1) -> (Tensor(a)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA"); | |
| } | |
| TEST(AliasRegistrationTest, FromSchemaWithInferredSchemaShouldError) { | |
| expectThrows<c10::Error>( | |
| [] { | |
| torch::RegisterOperators().op( | |
| "foo::rand5", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA)); | |
| }, | |
| "Tried to register operator foo::rand5(Tensor _0) -> (Tensor _0) with AliasAnalysisKind::FROM_SCHEMA, but the schema is inferred"); | |
| } | |
| TEST(AliasRegistrationTest, FromSchemaInferredPure) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand6(Tensor arg1) -> Tensor", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand6"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // The schema doesn't contain alias information, which means it's pure | |
| // (meh!) | |
| EXPECT_FALSE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, FromSchemaAliased) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand7(Tensor(a) arg1) -> Tensor(a)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; }) | |
| .aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand7"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // The schema has an alias reference | |
| EXPECT_TRUE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, FromSchemaPure) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand8(Tensor(a) arg1) -> Tensor(b)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; }) | |
| .aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand8"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // The schema does not have an alias reference | |
| EXPECT_FALSE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, PureNoSchema) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand9", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand9"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // The schema is pure, there cannot be any alias | |
| EXPECT_FALSE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, PureWithSchema) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand10(Tensor arg1) -> Tensor", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor) -> at::Tensor { | |
| return at::rand({2, 2}); | |
| }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand10"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| auto b = graph->insert(rand_op, {a}); | |
| AliasDb aliasDb(graph); | |
| // The schema is pure, there cannot be any alias | |
| EXPECT_FALSE(aliasDb.mayAlias(a, b)); | |
| } | |
| TEST(AliasRegistrationTest, PureWithAnnotationsShouldError) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand11(Tensor(a) arg1) -> Tensor(a)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand11"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| graph->insert(rand_op, {a}); | |
| // Registration time is okay, but throw exception when fetch from | |
| // registration. | |
| expectThrows<c10::Error>( | |
| [&graph] { AliasDb aliasDb(graph); }, | |
| "Tried to register operator foo::rand11(Tensor(a) arg1) -> (Tensor(a)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA"); | |
| } | |
| TEST(AliasRegistrationTest, AliasMoveAtenListOp) { | |
| auto graph = std::make_shared<Graph>(); | |
| std::unordered_map<std::string, Value*> vmap; | |
| auto graph_string = R"IR( | |
| graph(): | |
| %x : Tensor = prim::MakeTestTensor() | |
| %8 : int = prim::Constant[value=0]() | |
| %5 : int = prim::Constant[value=1]() | |
| %4 : int = prim::Constant[value=2]() | |
| %y : Tensor[] = prim::ListConstruct(%x) | |
| %6 : Tensor = aten::add_(%x, %4, %5) | |
| %9 : Tensor = aten::cat(%y, %8) | |
| return (%9))IR"; | |
| torch::jit::parseIR(graph_string, graph.get(), vmap); | |
| AliasDb aliasDb(graph); | |
| // bc y.1 has a single used in a single non-aliasing aten op, | |
| // x is added to y.1 contained elements instead of wildcard set | |
| EXPECT_TRUE(!aliasDb.mayAlias(vmap["x"], vmap["9"])); | |
| // write to contained element should prevent move | |
| EXPECT_TRUE(!aliasDb.moveBeforeTopologicallyValid( | |
| vmap["y"]->node(), vmap["9"]->node())); | |
| } | |
| TEST(AliasRegistrationTest, PureWithAnnotationsShouldError2) { | |
| auto registry = torch::RegisterOperators().op( | |
| "foo::rand12(Tensor(a) arg1) -> Tensor(b)", | |
| torch::RegisterOperators::options() | |
| .catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; }) | |
| .aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION)); | |
| const auto rand_op = Symbol::fromQualString("foo::rand12"); | |
| auto graph = std::make_shared<Graph>(); | |
| auto a = graph->addInput(); | |
| graph->insert(rand_op, {a}); | |
| // Registration time is okay, but throw exception when fetch from | |
| // registration. | |
| expectThrows<c10::Error>( | |
| [&graph] { AliasDb aliasDb(graph); }, | |
| "Tried to register operator foo::rand12(Tensor(a) arg1) -> (Tensor(b)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA"); | |
| } | |
| } // namespace jit | |
| } // namespace torch |