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fixup_trace_scope_blocks.cpp
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fixup_trace_scope_blocks.cpp
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#include <torch/csrc/jit/passes/fixup_trace_scope_blocks.h>
#include <c10/util/irange.h>
#include <torch/csrc/jit/frontend/schema_matching.h>
#include <torch/csrc/jit/passes/canonicalize.h>
#include <torch/csrc/jit/passes/dead_code_elimination.h>
#include <torch/csrc/jit/passes/inliner.h>
#include <torch/csrc/jit/passes/lower_tuples.h>
#include <algorithm>
namespace torch {
namespace jit {
namespace {
bool isEligibleNode(Node* n) {
return n->kind() == prim::TracedModuleForward ||
n->kind() == prim::TracedFork;
}
// This pass does several things:
// 1) It looks at TracedModuleForward nodes and resolves the type of `self`
// for that (to-be) method call. It adds an input of that type to the
// block, and adds the TracedAttr value corresponding to that `self`
// value as a Node input. This ensures `self` is an explicit Use on
// the node, a property we take advantage of downstream. Example:
// 2) Convert all references to prim::TracedAttr values to prim::GetAttr
// calls in the tightest scope possible. Concretely, for each use of
// a prim::TracedAttr value, we compare the scope of that attribute
// to the scope of the Use. We emit GetAttr nodes for all atoms
// that are not shared between the two. For example, if an
// attribute `f.param` is referenced in scope `f`, we emit a
// GetAttr[name="param"](%self) node in the `f` block, where
// `self` is the previously-added `self` argument to the block.
// 3) Destroy all the prim::TracedAttr nodes, as they should have
// no more uses.
//
// A quick example:
//
//
// Input graph:
//
// graph(%self : ClassType<Module>,
// %x : Float(3, 4)):
// %1 : bool = prim::TracedAttr[scope="__module.training"]()
// %2 : ClassType<Module> = prim::TracedAttr[scope="__module.f"]()
// %3 : Float(4, 4) = prim::TracedAttr[scope="__module.f.param"]()
// %4 : bool = prim::TracedAttr[scope="__module.f.training"]()
// = prim::TracedModuleForward[scope="__module.f"](),
// block0():
// %6 : Float(3, 4) = aten::mm(%x, %3),
// -> ()
// return (%6)
//
// The diff after step (1)
//
// - = prim::TracedModuleForward[scope="__module.f"](),
// - block0():
// + = prim::TracedModuleForward[scope="__module.f"](%2),
// + block0(%self : ClassType<Module>):
//
// The diff after step (2)
//
// graph(%self.1 : ClassType<Module>,
// %x : Float(3, 4)):
// + %9 : ClassType<Module> = prim::GetAttr[name="f"](%self.1)
// %1 : bool = prim::TracedAttr[scope="__module.training"]()
// <....>
// %4 : bool = prim::TracedAttr[scope="__module.f.training"]()
// - = prim::TracedModuleForward[scope="__module.f"](%2),
// + = prim::TracedModuleForward[scope="__module.f"](%9),
// block0(%self : ClassType<Module>):
// - %6 : Float(3, 4) = aten::mm(%x, %3),
// + %8 : Tensor = prim::GetAttr[name="param"](%self)
// + %6 : Float(3, 4) = aten::mm(%x, %8),
// -> ()
// return (%6)
//
// The diff after step (3)
//
// - %1 : bool = prim::TracedAttr[scope="__module.training"]()
// - %2 : ClassType<Module> = prim::TracedAttr[scope="__module.f"]()
// - %3 : Float(4, 4) = prim::TracedAttr[scope="__module.f.param"]()
// - %4 : bool = prim::TracedAttr[scope="__module.f.training"]()
struct ConvertTracedAttrReferences {
void run(const std::shared_ptr<Graph>& graph) {
// Build a table mapping--for each TracedAttr node--the
// qualified name of the attribute to the Value* output
// of the Node.
buildAttrMap(graph);
// Step 1
addSelfArgToTracedForwardNodes(graph->block());
// Step 2
convertAttrReferencesToLocalGetAttrs(
graph->block(), "__module", graph->inputs()[0]);
// Step 3
destroyTracedAttrNodes(graph);
}
private:
void buildAttrMap(const std::shared_ptr<Graph>& graph) {
for (Node* n : graph->nodes()) {
if (n->kind() == prim::TracedAttr) {
attr_qualname_to_value[n->s(attr::scope)] = n->output();
}
}
}
void addSelfArgToTracedForwardNodes(Block* b) {
for (Node* n : b->nodes()) {
if (n->kind() == prim::TracedModuleForward) {
n->addInput(attr_qualname_to_value.at(n->s(attr::scope)));
n->blocks()[0]->addInput("self")->setType(
attr_qualname_to_value.at(n->s(attr::scope))->type());
addSelfArgToTracedForwardNodes(n->blocks()[0]);
}
if (n->kind() == prim::TracedFork) {
addSelfArgToTracedForwardNodes(n->blocks()[0]);
}
}
}
// This is a recursive function that descends down all blocks in the Graph
// (NB: not just TracedModuleForward blocks). Each descension has a
// corresponding `prefix`, i.e. the qualified name of the scope this
// Block represents (or the scope in which this block resides for
// non-TracedModuleForward nodes). We use this prefix to make decisions
// about whether to emit a GetAttr node for an attribute reference, or
// to defer that emission to the caller (in the case where an attribute
// reference does not reside in the `prefix` scope).
std::vector<Value*> convertAttrReferencesToLocalGetAttrs(
Block* b,
const c10::QualifiedName& prefix,
Value* self) {
// Store away Value*'s which are references to TracedAttr's which are
// not in the `prefix` scope. We pass this back to the caller, who
// should add these Values as explicit inputs as well as inductively
// make the same decision on those Values.
std::vector<Value*> unresolved_tracedattrs;
// To ensure we don't emit redundant GetAttr Nodes in a given scope,
// we maintain this map of original TracedAttr Value* to the Value*
// corresponding to the GetAttr for that attribute.
// We don't rely on CSE here because we currently can't reason about
// the correctness of CSE over GetAttr Nodes (i think)
std::unordered_map<Value*, Value*> local_remaps;
for (Node* n : b->nodes()) {
// The only difference between these two branches is for
// TracedModuleForward we advance the scope, but for other
// Nodes with Blocks we don't
if (n->kind() == prim::TracedModuleForward) {
auto sub_unresolved = convertAttrReferencesToLocalGetAttrs(
n->blocks()[0], n->s(attr::scope), n->blocks()[0]->inputs()[0]);
for (Value* v : sub_unresolved) {
n->addInput(v);
}
} else if (n->blocks().size()) {
for (Block* sub_block : n->blocks()) {
auto sub_unresolved =
convertAttrReferencesToLocalGetAttrs(sub_block, prefix, self);
for (Value* v : sub_unresolved) {
n->addInput(v);
}
}
}
for (size_t inp_idx = 0; inp_idx < n->inputs().size(); ++inp_idx) {
Value* inp = n->input(inp_idx);
// Short circuit: if we've already emitted a new Value for this
// attribute, just use that.
if (local_remaps.count(inp)) {
n->replaceInput(inp_idx, local_remaps[inp]);
continue;
}
WithInsertPoint guard(b->param_node()->next());
replaceTracedAttrInputOnNode(
n, inp_idx, prefix, self, local_remaps, unresolved_tracedattrs);
} // for (Value *inp : n->inputs())
} // for (Node *n : b->nodes())
return unresolved_tracedattrs;
}
void replaceTracedAttrInputOnNode(
Node* n,
size_t inp_idx,
const c10::QualifiedName& prefix,
Value* self,
std::unordered_map<Value*, Value*>& local_remaps,
std::vector<Value*>& unresolved_tracedattrs) {
auto inp = n->inputs()[inp_idx];
auto inp_node = inp->node();
auto prefix_atoms = prefix.atoms();
if (inp_node->kind() == prim::TracedAttr) {
auto attr_qualname = c10::QualifiedName(inp_node->s(attr::scope));
if (prefix.isPrefixOf(attr_qualname)) {
// Prefix case: the attribute resides in this scope or a
// sub-scope. Continually emit GetAttr nodes until we've reached
// the proper attribute.
auto attr_atoms = attr_qualname.atoms();
Value* replaced_value = self;
for (const auto i : c10::irange(attr_atoms.size())) {
if (i < prefix_atoms.size()) {
TORCH_INTERNAL_ASSERT(attr_atoms[i] == prefix_atoms[i]);
} else {
replaced_value = n->owningBlock()->owningGraph()->insertGetAttr(
replaced_value, attr_atoms[i]);
} // if (i < prefix_atoms.size())
} // for(const auto i : c10::irange(attr_atoms.size()))
n->replaceInput(inp_idx, replaced_value);
local_remaps[inp] = replaced_value;
} else {
// Non-prefix case: this is a use of an attribute somewhere
// higher in the Module hierarchy. Add a captured input to
// the block for this attribute and add to the vector of
// Value*'s for the caller to handle.
Value* remapped = n->owningBlock()->addInput()->copyMetadata(inp);
n->replaceInput(inp_idx, remapped);
unresolved_tracedattrs.push_back(inp);
local_remaps[inp] = remapped;
} // if (prefix.isPrefixOf(attr_qualname))
} // if (inp_node->kind() == prim::TracedAttr)
}
// The previous pass should have deleted all uses of TracedAttr
// nodes. Let's explicitly delete them here.
void destroyTracedAttrNodes(const std::shared_ptr<Graph>& graph) {
for (auto& kv : attr_qualname_to_value) {
kv.second->node()->destroy();
}
}
// For each prim::TracedAttr, record the `scope` value mapped
// to the Value* in the graph for that attribute.
std::unordered_map<std::string, Value*> attr_qualname_to_value;
};
// Iterate through all the nodes in program order and--for each use--
// if the Value referenced is not in a scope that dominates the node,
// add block and Node outputs to lift it into a scope in which
// it dominates the Use.
struct MakeDefsDominateUses {
MakeDefsDominateUses() = default;
void run(Block* b) {
processNode(b->param_node(), b);
for (Node* n : b->nodes()) {
processNode(n, b);
}
processNode(b->return_node(), b);
}
private:
void processNode(Node* n, Block* b) {
for (size_t i = 0; i < n->inputs().size(); ++i) {
Value* inp = n->inputs()[i];
// Already lifted to this level by a previously processed Use, switch to
// remapped value
if (remap.count(inp)) {
n->replaceInput(i, remap[inp]);
inp = remap[inp];
}
// This conditional isn't strictly necessary, but saves a lot of
// computation in the common case that we're using a local value.
if (inp->node()->owningBlock() != b) {
// Find the common ancestor block between this node and the node that
// produced this input. For this input Use to be valid, the Value's
// def must be present in this common ancestor node.
Block* common_ancestor = n->findCommonAncestorBlockWith(inp->node());
Value* v_itr = inp;
Block* b_itr = inp->node()->owningBlock();
// Starting from the initial def for this input, iterate to
// wider and wider blocks, adding Block outputs and Node outputs
// along the way. Then, log the lifted values in the remap table
// so we can make subsequent Uses refer to the lifted value, if
// the domination condition is met.
while (b_itr != common_ancestor) {
b_itr->registerOutput(v_itr);
Value* remapped =
b_itr->owningNode()->addOutput()->setType(v_itr->type());
v_itr = remapped;
b_itr = b_itr->owningNode()->owningBlock();
}
// From now on, references to `inp` will be replaced with
// references to `v_iter`, the lifted Value
remap[inp] = v_itr;
n->replaceInput(i, remap[inp]);
}
}
if (isEligibleNode(n)) {
run(n->blocks()[0]);
}
}
// This holds the mapping between a Value* we would see in a Use
// and the lifted value, if present. We use this to ensure that
// Uses refer to a Value* that is in a dominating scope.
using RemappingTable = std::unordered_map<Value*, Value*>;
RemappingTable remap;
};
// For all blocks except graph->block(), convert multiple block
// returns to a TupleConstruct. This is required for turning the
// blocks into Methods. (and in the case that self is nullptr,
// it is required to properly inline the blocks).
void convertReturnsToTuples(Block* b) {
for (Node* n : b->nodes()) {
if (n->kind() == prim::TracedFork) {
convertReturnsToTuples(n->blocks()[0]);
} else if (n->kind() == prim::TracedModuleForward) {
TORCH_INTERNAL_ASSERT(n->blocks().size() == 1);
convertReturnsToTuples(n->blocks()[0]);
Graph* g = b->owningGraph();
Block* sub_block = n->blocks()[0];
if (sub_block->outputs().size() > 1) {
{
// Make block returns go through a Tuple
WithInsertPoint guard(sub_block->return_node());
Node* return_tup =
g->insertNode(g->createTuple(sub_block->outputs()));
while (sub_block->outputs().size()) {
sub_block->eraseOutput(0);
}
sub_block->registerOutput(return_tup->output());
}
// Make node outputs a single tuple;
std::vector<TypePtr> types;
for (size_t i = 0; i < n->outputs().size(); ++i) {
types.push_back(n->output(i)->type());
}
Value* tup_output = n->addOutput()->setType(TupleType::create(types));
Node* tup_unpack = g->createTupleUnpack(tup_output)->insertAfter(n);
for (size_t i = 0; i < tup_unpack->outputs().size(); ++i) {
auto rev_idx = tup_unpack->outputs().size() - i - 1;
n->output(rev_idx)->replaceAllUsesWith(tup_unpack->output(rev_idx));
n->eraseOutput(rev_idx);
}
} else if (sub_block->outputs().size() == 0) {
WithInsertPoint guard(sub_block->return_node());
sub_block->registerOutput(g->insertNode(g->createNone())->output());
n->addOutput()->setType(NoneType::get());
}
}
}
}
// Lambda lift Values (i.e. add Graph inputs for the purpose of
// referencing values that dominate the block) and convert
// the block to a Graph. blocks()[0] on each TracedModuleForward then
// appears as a Graph attribute attr::Subgraph
void lambdaLiftBlocksAndConvertToGraph(Block* b) {
for (Node* n : b->nodes()) {
if (isEligibleNode(n)) {
lambdaLiftBlocksAndConvertToGraph(n->blocks()[0]);
auto graph = std::make_shared<Graph>();
std::unordered_map<Value*, Value*> remaps;
graph->block()->cloneFrom(n->blocks()[0], [&](Value* v) {
if (!remaps.count(v)) {
remaps[v] = graph->addInput()->copyMetadata(v);
n->addInput(v);
}
return remaps[v];
});
LintGraph(graph);
n->g_(attr::Subgraph, graph);
n->eraseBlock(0);
}
}
}
// Find a unique name to add this method as
// We try {method_name}, {method_name}1, {method_name}2, ...
std::string mangleMethodName(
const std::string& method_name,
const ClassTypePtr& mod_type) {
for (size_t method_idx = 0;; method_idx++) {
auto mangled = method_name;
if (method_idx != 0) {
mangled += c10::to_string(method_idx);
}
bool found = false;
for (Function* fn : mod_type->methods()) {
if (fn->name() == mangled) {
found = true;
break;
}
}
if (!found) {
return mangled;
}
}
TORCH_INTERNAL_ASSERT(false);
}
// Register the attr::Subgraph Graph values as Functions in the
// class compilation unit and register that Function as a method
// on the corresponding Module in the Module hierarchy. Note that we
// unique the methods by naming them forward, forward1, forward2...
void createMethodCalls(const std::shared_ptr<Graph>& g) {
for (auto node_itr = g->nodes().begin(); node_itr != g->nodes().end();) {
Node* n = *node_itr++;
if (n->kind() == prim::TracedFork) {
createMethodCalls(n->g(attr::Subgraph));
} else if (n->kind() == prim::TracedModuleForward) {
WithInsertPoint ip(n);
ClassTypePtr callee_mod_type = n->input(0)->type()->expect<ClassType>();
createMethodCalls(n->g(attr::Subgraph));
auto mangled_method_name = mangleMethodName("forward", callee_mod_type);
auto qualname = c10::QualifiedName(
callee_mod_type->name().value(), mangled_method_name);
Function* f = callee_mod_type->compilation_unit()->create_function(
qualname, n->g(attr::Subgraph));
callee_mod_type->addMethod(f);
std::vector<NamedValue> nvs;
for (Value* i : n->inputs()) {
nvs.emplace_back(i->node()->sourceRange(), i);
}
auto schema = matchSchema(f->getSchema(), n->sourceRange(), *g, nvs, {});
Value* retval = g->insertMethodCall(f->qualname().name(), schema);
n->output()->replaceAllUsesWith(retval);
n->destroy();
}
}
}
void inlineScopeBlocks(Block* b) {
for (auto n_itr = b->nodes().begin(); n_itr != b->nodes().end();) {
Node* n = *n_itr++;
for (Block* sub_b : n->blocks()) {
inlineScopeBlocks(sub_b);
}
if (n->kind() == prim::TracedModuleForward) {
// Convert the block to a graph so we can inline it
auto graph = std::make_shared<Graph>();
std::unordered_map<Value*, Value*> remaps;
graph->block()->cloneFrom(n->blocks()[0], [&](Value* v) {
remaps[v] = graph->block()->addInput()->copyMetadata(v);
n->addInput(v);
return remaps[v];
});
WithInsertPoint insert_point(n);
AT_ASSERT(n->inputs().size() == graph->inputs().size());
auto new_outputs = insertGraph(*n->owningGraph(), *graph, n->inputs());
const auto& old_outputs = n->outputs();
AT_ASSERT(new_outputs.size() == old_outputs.size());
for (const auto i : c10::irange(old_outputs.size())) {
old_outputs[i]->replaceAllUsesWith(new_outputs[i]);
}
n->destroy();
}
}
}
void convertTracedForksToRealForks(const std::shared_ptr<Graph>& g) {
for (auto itr = g->nodes().begin(); itr != g->nodes().end();) {
Node* n = *itr++;
if (n->kind() == prim::TracedFork) {
WithInsertPoint guard(n);
Node* new_fork_node =
g->insertNode(g->create(prim::fork, n->outputs().size()))
->copyAttributes(*n);
for (Value* i : n->inputs()) {
new_fork_node->addInput(i);
}
for (size_t i = 0; i < new_fork_node->outputs().size(); ++i) {
new_fork_node->outputs()[i]->copyMetadata(n->outputs()[i]);
n->outputs()[i]->replaceAllUsesWith(new_fork_node->outputs()[i]);
}
n->destroy();
}
}
}
// Run a few clean-up passes to make the graph a bit cleaner.
void runCleanupPasses(const std::shared_ptr<Graph>& g) {
for (Node* n : g->nodes()) {
if (n->kind() == prim::TracedFork) {
auto subgraph = n->g(attr::Subgraph);
if (getInlineEverythingMode()) {
Inline(*subgraph);
}
convertTracedForksToRealForks(subgraph);
LowerSimpleTuples(subgraph);
EliminateDeadCode(subgraph);
LintGraph(subgraph);
}
}
if (getInlineEverythingMode()) {
Inline(*g);
}
convertTracedForksToRealForks(g);
LowerSimpleTuples(g);
EliminateDeadCode(g);
LintGraph(g);
}
void runCleanupPasses(Module* m) {
auto methods = m->get_methods();
for (auto module : m->children()) {
runCleanupPasses(&module);
}
for (auto& method : methods) {
runCleanupPasses(method.graph());
}
}
} // namespace
void FixupTraceScopeBlocks(std::shared_ptr<Graph>& graph, Module* self) {
if (self) {
ConvertTracedAttrReferences().run(graph);
} else {
for (Node* n : graph->nodes()) {
TORCH_INTERNAL_ASSERT(n->kind() != prim::TracedAttr);
}
}
MakeDefsDominateUses().run(graph->block());
convertReturnsToTuples(graph->block());
if (!self) {
// We have no Module, so we're just going to inline everything.
// This should give us a totally flat graph.
inlineScopeBlocks(graph->block());
// For TracedFork nodes
lambdaLiftBlocksAndConvertToGraph(graph->block());
runCleanupPasses(graph);
} else {
lambdaLiftBlocksAndConvertToGraph(graph->block());
createMethodCalls(graph);
runCleanupPasses(self);
// `graph` isn't referenced in `self` yet, so we need to run
// this separately
runCleanupPasses(graph);
}
}
} // namespace jit
} // namespace torch