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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/33127 Test Plan: Imported from OSS Differential Revision: D19806503 Pulled By: ZolotukhinM fbshipit-source-id: ab78bdbbac5f12dbcc6c2e2573f5862a16ffcf3d
1360 lines
43 KiB
C++
1360 lines
43 KiB
C++
#include <torch/csrc/autograd/generated/variable_factories.h>
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#include <torch/csrc/jit/irparser.h>
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#include "test/cpp/jit/test_base.h"
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#include "torch/csrc/jit/custom_operator.h"
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#include "torch/csrc/jit/passes/alias_analysis.h"
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#include "torch/csrc/jit/script/ir_emitter.h"
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#include "torch/csrc/utils/memory.h"
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namespace torch {
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namespace jit {
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inline c10::OperatorOptions aliasAnalysisFromSchema() {
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c10::OperatorOptions result;
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result.setAliasAnalysis(c10::AliasAnalysisKind::FROM_SCHEMA);
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return result;
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}
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// Fixture to set up a graph and make assertions clearer
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struct TopoMoveTestFixture {
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TopoMoveTestFixture() {
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createGraph();
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aliasDb = torch::make_unique<AliasDb>(graph);
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}
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// Nodes are named after their output.
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// e.g. "a" is an alias for "the node that outputs the value `a`"
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void createGraph() {
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graph = std::make_shared<Graph>();
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createNode("a", {});
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createNode("b", {"a"});
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createNode("c", {});
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createNode("d", {"a", "b"});
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createNode("e", {"c", "b"});
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createNode("f", {"e"});
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createNode("g", {"e"});
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createNode("h", {"g"});
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createNode("i", {"g"});
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createNode("j", {"i"});
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createNode("k", {"i"});
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createNode("l", {"a"});
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createNode("m", {}, {"l"}); // block depends on l
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createNode("n", {"m"});
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createNode("o", {"n"});
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createNode("p", {});
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createNode("q", {});
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createNode("r", {"q"});
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createNode("s", {"q"});
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graph->lint();
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}
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void createNode(
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const std::string& name,
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const std::vector<std::string>& inputNames,
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const std::vector<std::string>& blockInputNames = {}) {
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std::vector<Value*> inputs;
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for (const auto name : inputNames) {
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inputs.push_back(nodes.at(name)->output());
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}
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auto node = graph->appendNode(graph->create(prim::AutogradZero, inputs));
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node->output()->setDebugName(name);
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nodes[name] = node;
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if (blockInputNames.size() != 0) {
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node->addBlock();
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std::vector<Value*> blockDeps;
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for (const auto name : blockInputNames) {
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blockDeps.push_back(nodes.at(name)->output());
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}
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auto block = node->blocks().at(0);
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block->appendNode(graph->create(prim::AutogradZero, blockDeps));
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}
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}
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bool moveBeforeTopologicallyValid(
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const std::string& toInsert,
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const std::string& insertPoint) {
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std::function<bool(Node*, Node*)> func =
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[this](Node* toInsert, Node* insertPoint) {
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return aliasDb->moveBeforeTopologicallyValid(toInsert, insertPoint);
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};
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return moveWithChecks(toInsert, insertPoint, func);
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}
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bool moveAfterTopologicallyValid(
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const std::string& toInsert,
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const std::string& insertPoint) {
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std::function<bool(Node*, Node*)> func =
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[this](Node* toInsert, Node* insertPoint) {
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return aliasDb->moveAfterTopologicallyValid(toInsert, insertPoint);
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};
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return moveWithChecks(toInsert, insertPoint, func);
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}
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bool moveWithChecks(
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const std::string& toInsert,
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const std::string& insertPoint,
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std::function<bool(Node*, Node*)> func) {
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auto n = nodes.at(toInsert);
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auto insert = nodes.at(insertPoint);
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bool isAfter = n->isAfter(insert);
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std::vector<Node*> originalOrdering;
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Node* original = isAfter ? n->next() : n->prev();
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auto curNode = original;
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while (curNode != n->owningBlock()->return_node()) {
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originalOrdering.push_back(curNode);
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if (isAfter) {
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curNode = curNode->next();
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} else {
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curNode = curNode->prev();
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}
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}
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const auto couldMove = func(n, insert);
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// Check the graph is okay
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graph->lint();
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// If this is the picture of nodes
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// <some nodes> ... toInsert ... <some more nodes> ... insertPoint
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// ^----------^ check that these nodes haven't moved
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curNode = original;
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size_t idx = 0;
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while (curNode != n->owningBlock()->return_node()) {
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AT_ASSERT(originalOrdering[idx] == curNode);
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if (isAfter) {
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curNode = curNode->next();
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} else {
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curNode = curNode->prev();
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}
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idx++;
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}
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return couldMove;
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}
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void checkPostCondition(
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const std::string& toInsert,
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const std::string& insertPoint,
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bool after) {
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if (after) {
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AT_ASSERT(nodes.at(toInsert)->prev() == nodes.at(insertPoint));
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} else {
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AT_ASSERT(nodes.at(toInsert)->next() == nodes.at(insertPoint));
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}
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}
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std::shared_ptr<Graph> graph;
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std::unique_ptr<AliasDb> aliasDb;
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std::unordered_map<std::string, Node*> nodes;
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};
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void testTopologicalMove() {
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{
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// Check that we are removing `this`'s deps properly when we need to split
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// `this` and deps (see code for what the hell that means)
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("q", "s"));
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fixture.checkPostCondition("q", "s", false);
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}
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// Move after
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{
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// Simple move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("c", "a"));
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fixture.checkPostCondition("c", "a", true);
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}
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{
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// simple invalid move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("d", "a"));
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}
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{
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// doesn't actually move anything
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("f", "e"));
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fixture.checkPostCondition("f", "e", true);
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}
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{
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// move backward with multiple dependencies
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("e", "c"));
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fixture.checkPostCondition("e", "c", true);
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}
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{
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// Move backward with non-zero working set
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("k", "f"));
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fixture.checkPostCondition("k", "f", true);
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}
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{
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// Simple move forward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("c", "d"));
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fixture.checkPostCondition("c", "d", true);
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}
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{
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// Move forward with non-zero working set
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("f", "l"));
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fixture.checkPostCondition("f", "l", true);
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}
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// Move before
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{
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// Simple move forward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("b", "d"));
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fixture.checkPostCondition("b", "d", false);
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}
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{
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// Simple move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("c", "a"));
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fixture.checkPostCondition("c", "a", false);
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}
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{
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// doesn't actually move anything
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("a", "b"));
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fixture.checkPostCondition("a", "b", false);
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}
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{
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// move forward with deps
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("f", "m"));
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fixture.checkPostCondition("f", "m", false);
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}
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{
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// move backward with deps
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("l", "f"));
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fixture.checkPostCondition("l", "f", false);
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}
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// check that dependencies in blocks are recognized
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{
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("l", "m"));
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AT_ASSERT(!fixture.moveBeforeTopologicallyValid("m", "l"));
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("n", "l"));
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AT_ASSERT(!fixture.moveBeforeTopologicallyValid("l", "n"));
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}
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// Test that moveAfter(n) and moveBefore(n->next()) are not necessarily
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// equivalent. Here, the dependency ordering is n -> o -> p. So we can't
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// move `n` after `o`, but we can move `n` before `p` (which pushes `o` after
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// `p`)
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{
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("n", "o"));
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("o", "p"));
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fixture.checkPostCondition("o", "p", false);
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}
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}
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namespace {
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Node* insertIf(
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Graph& g,
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Value* condValue,
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std::function<std::vector<Value*>()> trueInst,
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std::function<std::vector<Value*>()> falseInst) {
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auto if_ = g.insertNode(g.create(prim::If, 0));
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if_->addInput(condValue); // condition value
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auto trueBlock = if_->addBlock();
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auto falseBlock = if_->addBlock();
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{
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// Mutate in true block
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WithInsertPoint g(trueBlock);
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auto outputs = trueInst();
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for (auto output : outputs) {
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trueBlock->registerOutput(output);
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}
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}
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{
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WithInsertPoint g(falseBlock);
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auto outputs = falseInst();
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for (auto output : outputs) {
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falseBlock->registerOutput(output);
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}
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}
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AT_ASSERT(trueBlock->outputs().size() == falseBlock->outputs().size());
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for (auto output : trueBlock->outputs()) {
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if_->addOutput()->setType(output->type());
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}
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return if_;
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}
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template <class Exception, class Functor>
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inline void expectThrows(Functor&& functor, const char* expectMessageContains) {
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try {
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std::forward<Functor>(functor)();
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} catch (const Exception& e) {
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if (std::string(e.what()).find(expectMessageContains) ==
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std::string::npos) {
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AT_ERROR(
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"Expected error message to contain \"",
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expectMessageContains,
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"\" but error message was: ",
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e.what());
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}
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return;
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}
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AT_ERROR(
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"Expected to throw exception containing \"",
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expectMessageContains,
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"\" but didn't throw");
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}
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} // namespace
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void testAliasAnalysis() {
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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// addsB = b + b
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// c = a + b
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// a += b
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// d = c + c
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auto addsB = graph->insert(aten::add, {b, b});
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auto c = graph->insert(aten::add, {a, b});
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auto aMut = graph->insert(aten::add_, {a, b});
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auto d = graph->insert(aten::add, {c, c});
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graph->lint();
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AliasDb aliasDb(graph);
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// Can't move past a mutation of a used value
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(c->node(), aMut->node()));
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AT_ASSERT(aliasDb.moveAfterTopologicallyValid(d->node(), c->node()));
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// b should alias to a (since they are both inputs)
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AT_ASSERT(
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!aliasDb.moveAfterTopologicallyValid(addsB->node(), aMut->node()));
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AT_ASSERT(aliasDb.moveAfterTopologicallyValid(addsB->node(), c->node()));
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graph->lint();
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}
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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auto constant = graph->insertConstant(1);
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auto fresh = graph->insert(aten::rand, {constant});
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auto usesB = graph->insert(aten::add, {b, fresh});
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auto aliasesB = graph->insert(aten::select, {a, constant, constant});
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auto mutatesAliasOfB = graph->insert(aten::add_, {aliasesB, fresh});
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graph->insert(aten::add, {fresh, aliasesB});
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graph->lint();
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AliasDb aliasDb(graph);
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(
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aliasesB->node(), mutatesAliasOfB->node()));
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(
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usesB->node(), mutatesAliasOfB->node()));
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}
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{
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// Test moves across inner blocks
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// a = rand(1)
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// b = rand(1)
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// if True:
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// a.add_(b)
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// c = a + b
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auto graph = std::make_shared<Graph>();
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auto constant = graph->insertConstant(1);
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auto a = graph->insert(aten::rand, {constant});
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auto b = graph->insert(aten::rand, {constant});
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auto if_ = insertIf(
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*graph,
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constant,
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[&]() -> std::vector<Value*> {
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auto aMut = graph->insert(aten::add_, {a, b});
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return {aMut};
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},
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[&]() -> std::vector<Value*> { return {a}; });
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auto c = graph->insert(aten::add, {a, b});
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graph->lint();
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// we should not be able to move `c` before the if statement, since it
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// may write to `a`.
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AliasDb aliasDb(graph);
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ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(c->node(), if_));
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}
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// test none value does not have writers
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{
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{
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auto graph = std::make_shared<Graph>();
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std::unordered_map<std::string, Value*> vmap;
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script::parseIR(
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R"IR(
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graph():
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%opt : Tensor? = prim::Constant()
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%out : Tensor = prim::unchecked_unwrap_optional(%opt)
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%ret.2 : Tensor = aten::div(%out, %out, %out)
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return (%opt, %out, %ret.2)
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)IR",
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&*graph,
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vmap);
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AliasDb aliasDb(graph);
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AT_ASSERT(!aliasDb.hasWriters(vmap["opt"]->node()));
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}
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}
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// test safeToIntroduceAliasingRelationship
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{
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auto graph = std::make_shared<Graph>();
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std::unordered_map<std::string, Value*> vmap;
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script::parseIR(
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R"IR(
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graph(%x : Tensor):
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%3 : int = prim::Constant[value=1]()
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%2 : int = prim::Constant[value=0]()
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%b : Tensor = aten::add(%x, %2, %3)
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%c : Tensor = aten::add(%x, %2, %3)
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%d : Tensor = aten::add(%x, %2, %3)
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%e : Tensor = aten::add(%x, %2, %3)
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%f : Tensor[] = prim::ListConstruct(%e)
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%14 : (Tensor, Tensor) = prim::TupleConstruct(%b, %c)
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return (%14)
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)IR",
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&*graph,
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vmap);
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AliasDb aliasDb(graph);
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// x, b, c escape scope, so we can't introduce an aliasing relationship
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TORCH_INTERNAL_ASSERT(!aliasDb.safeToChangeAliasingRelationship(vmap["x"], vmap["b"]));
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TORCH_INTERNAL_ASSERT(
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!aliasDb.safeToChangeAliasingRelationship(vmap["b"], vmap["x"]));
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TORCH_INTERNAL_ASSERT(
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!aliasDb.safeToChangeAliasingRelationship(vmap["b"], vmap["c"]));
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TORCH_INTERNAL_ASSERT(
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!aliasDb.safeToChangeAliasingRelationship(vmap["c"], vmap["b"]));
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// e aliases the wildcard set because it's contained in a list
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TORCH_INTERNAL_ASSERT(
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!aliasDb.safeToChangeAliasingRelationship(vmap["e"], vmap["x"]));
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TORCH_INTERNAL_ASSERT(
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!aliasDb.safeToChangeAliasingRelationship(vmap["x"], vmap["e"]));
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// d is a temporary with no writers, safe to change aliasing relationship here
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TORCH_INTERNAL_ASSERT(aliasDb.safeToChangeAliasingRelationship(vmap["c"], vmap["d"]));
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TORCH_INTERNAL_ASSERT(
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aliasDb.safeToChangeAliasingRelationship(vmap["d"], vmap["c"]));
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}
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}
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void testWriteTracking() {
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RegisterOperators reg({Operator(
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"prim::creates_alias(Tensor(a) x) -> Tensor(a)",
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[](Stack& s) { return 0; },
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aliasAnalysisFromSchema())});
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const auto creates_alias = Symbol::fromQualString("prim::creates_alias");
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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// aten::add(%b, %b)
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// aten::add_(%a, %b)
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// foo::creates_alias(%a)
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auto pureNode = graph->insert(aten::add, {b, b})->node();
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auto writingNode = graph->insert(aten::add_, {a, b})->node();
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auto node3 = graph->insert(creates_alias, {a})->node();
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auto aAlias = node3->output();
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graph->lint();
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AliasDb aliasDb(graph);
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ASSERT_TRUE(aliasDb.mayAlias(aAlias, a));
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ASSERT_TRUE(aliasDb.mayAlias(a, b));
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ASSERT_FALSE(
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aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{a}));
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ASSERT_FALSE(
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aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{b}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{a}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{a, b}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{aAlias}));
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}
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{
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auto graph = std::make_shared<Graph>();
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script::parseIR(
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R"IR(
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|
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);
|
|
AT_ASSERT(aliasDb.isMutable(relu));
|
|
}
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::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);
|
|
AT_ASSERT(!aliasDb.isMutable(mul));
|
|
}
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::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);
|
|
AT_ASSERT(aliasDb.hasWriters(add));
|
|
AT_ASSERT(aliasDb.isMutable(add));
|
|
}
|
|
}
|
|
|
|
void testContainerAliasing() {
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::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);
|
|
|
|
AT_ASSERT(graph->outputs().size() == 3);
|
|
for (auto out : graph->outputs()) {
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_output, out));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(local_var, out));
|
|
}
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_output, graph->inputs()));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(local_var, graph->inputs()));
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias({ten_output}, graph->outputs()));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(str_output, graph->outputs()));
|
|
}
|
|
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::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);
|
|
|
|
AT_ASSERT(graph->outputs().size() == 3);
|
|
// primitive values don't need to alias container
|
|
for (auto out : graph->outputs()) {
|
|
AT_ASSERT(!aliasDb.mayContainAlias(int_node->output(), out));
|
|
}
|
|
}
|
|
|
|
// Test input aliasing
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::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()) {
|
|
AT_ASSERT(aliasDb.mayContainAlias(input, tuple_node->output()));
|
|
}
|
|
AT_ASSERT(aliasDb.mayContainAlias(graph->inputs(), graph->outputs()));
|
|
}
|
|
|
|
// Test tuple that doesn't come from construct
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::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;
|
|
}
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(input, graph->outputs().at(0)));
|
|
}
|
|
}
|
|
|
|
// test nested types
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%4 : Device? = prim::Constant()
|
|
%2 : int? = prim::Constant()
|
|
%0 : float = prim::Constant[value=1]()
|
|
%20 : bool = prim::Constant[value=0]()
|
|
%a : Tensor = aten::tensor(%0, %2, %4, %20)
|
|
%a_list : Tensor[] = prim::ListConstruct(%a)
|
|
%b : Tensor = aten::tensor(%0, %2, %4, %20)
|
|
%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
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_1, list_2));
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_2, list_1));
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_1, g_output));
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_2, g_output));
|
|
}
|
|
|
|
// simple example
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::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;
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(first_ten->output(), tup_node->output()));
|
|
AT_ASSERT(
|
|
!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()};
|
|
AT_ASSERT(aliasDb.mayContainAlias(first_st, tup_st));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(first_st, second_st));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(second_st, tup_st));
|
|
}
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::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"];
|
|
AT_ASSERT(!aliasDb.mayContainAlias(x, c));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(c, x));
|
|
|
|
auto d = vmap["d"];
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(d, c));
|
|
AT_ASSERT(aliasDb.mayContainAlias(c, d));
|
|
}
|
|
{
|
|
// Test list container aliasing
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%x : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%y : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%22 : int[] = prim::ListConstruct(%0, %1)
|
|
%z : Tensor = aten::rand(%22, %4, %4, %8, %10)
|
|
%32 : int[] = prim::ListConstruct(%0, %1)
|
|
%fresh : Tensor = aten::rand(%32, %4, %4, %8, %10)
|
|
%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.
|
|
ASSERT_TRUE(aliasDb.mayAlias(x, y));
|
|
ASSERT_TRUE(aliasDb.mayAlias(y, z));
|
|
ASSERT_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"];
|
|
ASSERT_FALSE(aliasDb.mayAlias(x, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(y, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(z, fresh));
|
|
}
|
|
{
|
|
// 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;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%11 : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%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"];
|
|
ASSERT_TRUE(aliasDb.writesToAlias(conservativeOp, ValueSet{tensor}));
|
|
}
|
|
{
|
|
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;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%35 : int = prim::Constant[value=1]()
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%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 = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%21 : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%l : Tensor[] = prim::ListConstruct(%11, %21)
|
|
%24 : Tensor = aten::select(%l, %23)
|
|
%25 : int[] = prim::ListConstruct(%0, %1)
|
|
%34 : Tensor = aten::rand(%25, %4, %4, %8, %10)
|
|
%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();
|
|
ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite));
|
|
}
|
|
{
|
|
// 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;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%38 : int = prim::Constant[value=1]()
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%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 = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%21 : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%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 = aten::rand(%28, %4, %4, %8, %10)
|
|
%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();
|
|
ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite));
|
|
}
|
|
}
|
|
|
|
void testWildcards() {
|
|
RegisterOperators reg({Operator(
|
|
"prim::returns_wildcard(Tensor a) -> Tensor(*)",
|
|
[](Stack& stack) { return 0; },
|
|
aliasAnalysisFromSchema()),
|
|
Operator(
|
|
"prim::writes(Tensor(z!) a) -> Tensor(a)",
|
|
[](Stack& stack) { return 0; },
|
|
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);
|
|
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(wildcard, fresh));
|
|
ASSERT_TRUE(aliasDb.mayAlias(wildcard, a));
|
|
ASSERT_FALSE(aliasDb.mayAlias(ValueSet{wildcard}, ValueSet{}));
|
|
ASSERT_FALSE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
|
|
graph->insert(writes, {fresh2})->node();
|
|
{
|
|
graph->lint();
|
|
AliasDb aliasDb(graph);
|
|
ASSERT_FALSE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
|
|
const auto wildcardWrite = graph->insert(writes, {wildcard})->node();
|
|
{
|
|
graph->lint();
|
|
AliasDb aliasDb(graph);
|
|
// Test writes to wildcards
|
|
ASSERT_FALSE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{fresh}));
|
|
ASSERT_FALSE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{fresh2}));
|
|
ASSERT_TRUE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{a}));
|
|
ASSERT_TRUE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
|
|
// test that wildcards are correctly divided by type
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::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"];
|
|
AT_ASSERT(!aliasDb.hasWriters(int_list));
|
|
AT_ASSERT(aliasDb.hasWriters(opt_ten_list));
|
|
AT_ASSERT(aliasDb.hasWriters(ten_list));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(int_list, opt_ten_list));
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_list, opt_ten_list));
|
|
AT_ASSERT(aliasDb.mayAlias(ten_list, opt_ten_list));
|
|
|
|
auto list_of_tensor_lists = vmap["ten_ten_list"];
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_list, list_of_tensor_lists));
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_list, vmap["ten"]));
|
|
|
|
AT_ASSERT(
|
|
!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
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::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"];
|
|
AT_ASSERT(!aliasDb.hasWriters(ten_opt_list));
|
|
AT_ASSERT(aliasDb.hasWriters(ten_list));
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_list, ten_opt_list));
|
|
AT_ASSERT(!aliasDb.mayAlias(ten_list, ten_opt_list));
|
|
}
|
|
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph(%float_3D : Float(*, *, *), %float_2D : Float(*, *)):
|
|
return ()
|
|
)IR",
|
|
&*graph,
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
AT_ASSERT(aliasDb.mayAlias(vmap["float_3D"], vmap["float_2D"]));
|
|
}
|
|
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph(%float_3D_list : Float(*, *, *)[], %float_2D_list : Float(*, *)[], %ten: Tensor):
|
|
return ()
|
|
)IR",
|
|
&*graph,
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
AT_ASSERT(aliasDb.mayAlias(vmap["float_3D_list"], vmap["float_2D_list"]));
|
|
AT_ASSERT(aliasDb.mayContainAlias(vmap["float_3D_list"], vmap["ten"]));
|
|
AT_ASSERT(aliasDb.mayContainAlias(vmap["float_2D_list"], vmap["ten"]));
|
|
}
|
|
}
|
|
|
|
void testMemoryDAG() {
|
|
auto graph = std::make_shared<Graph>();
|
|
const Value* aValue = graph->addInput();
|
|
const Value* bValue = graph->addInput();
|
|
const Value* cValue = graph->addInput();
|
|
const Value* dValue = graph->addInput();
|
|
const Value* eValue = graph->addInput();
|
|
const Value* fValue = graph->addInput();
|
|
const Value* gValue = graph->addInput();
|
|
|
|
{
|
|
// a <- b <- c
|
|
// b <- d
|
|
// a <- e
|
|
// f <- e
|
|
// g is by itself
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
auto c = t.makeFreshValue(cValue);
|
|
auto d = t.makeFreshValue(dValue);
|
|
auto e = t.makeFreshValue(eValue);
|
|
auto f = t.makeFreshValue(fValue);
|
|
auto g = t.makeFreshValue(gValue);
|
|
t.makePointerTo(b, a);
|
|
t.makePointerTo(c, b);
|
|
t.makePointerTo(d, b);
|
|
t.makePointerTo(e, a);
|
|
t.makePointerTo(e, f);
|
|
|
|
/**
|
|
* Test mayAlias()
|
|
*/
|
|
// Values should alias themselves
|
|
ASSERT_TRUE(t.mayAlias(a, a));
|
|
ASSERT_TRUE(t.mayAlias(g, g));
|
|
|
|
// Values that point to the same location should alias
|
|
ASSERT_TRUE(t.mayAlias(a, b));
|
|
ASSERT_TRUE(t.mayAlias(a, c));
|
|
ASSERT_TRUE(t.mayAlias(c, d));
|
|
|
|
// e may point to a OR f
|
|
ASSERT_TRUE(t.mayAlias(e, a));
|
|
ASSERT_TRUE(t.mayAlias(e, f));
|
|
// But a and f don't alias
|
|
ASSERT_FALSE(t.mayAlias(a, f));
|
|
}
|
|
{
|
|
// Test invalidation of memory locations
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
// `a` does not point to `b`
|
|
ASSERT_FALSE(a->getMemoryLocations().test(b->index));
|
|
t.makePointerTo(a, b);
|
|
ASSERT_TRUE(a->getMemoryLocations().test(b->index));
|
|
}
|
|
{
|
|
// x(y) -> x contains y
|
|
|
|
// b(a)
|
|
// c(a)
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
t.addToContainedElements(a, b);
|
|
|
|
auto c = t.makeFreshValue(cValue);
|
|
t.addToContainedElements(a, c);
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, b));
|
|
AT_ASSERT(t.mayContainAlias(b, a));
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, c));
|
|
AT_ASSERT(t.mayContainAlias(c, a));
|
|
|
|
AT_ASSERT(t.mayContainAlias(b, c));
|
|
AT_ASSERT(t.mayContainAlias(c, b));
|
|
|
|
// containers contain an element in themselves
|
|
AT_ASSERT(t.mayContainAlias(b, b));
|
|
AT_ASSERT(t.mayContainAlias(c, c));
|
|
AT_ASSERT(t.mayContainAlias(a, a));
|
|
|
|
auto d = t.makeFreshValue(dValue);
|
|
|
|
// b(a)
|
|
// c(a)
|
|
// d(b(a))
|
|
t.addToContainedElements(b, d);
|
|
AT_ASSERT(t.mayContainAlias(b, d));
|
|
AT_ASSERT(t.mayContainAlias(d, b));
|
|
|
|
AT_ASSERT(t.mayContainAlias(c, d));
|
|
AT_ASSERT(t.mayContainAlias(d, c));
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, d));
|
|
|
|
// f(e)
|
|
auto f = t.makeFreshValue(aValue);
|
|
auto e = t.makeFreshValue(bValue);
|
|
|
|
t.addToContainedElements(f, e);
|
|
|
|
for (auto elem : {a, b, c, d}) {
|
|
AT_ASSERT(!t.mayContainAlias(f, elem));
|
|
AT_ASSERT(!t.mayContainAlias(e, elem));
|
|
}
|
|
}
|
|
}
|
|
|
|
void testAliasRegistration() {
|
|
{
|
|
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
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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");
|
|
}
|
|
{
|
|
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");
|
|
}
|
|
{
|
|
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");
|
|
}
|
|
{
|
|
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!)
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
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");
|
|
}
|
|
{
|
|
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
|