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integer_value_refinement.cpp
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integer_value_refinement.cpp
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#include <ATen/core/jit_type.h>
#include <torch/csrc/jit/ir/ir.h>
#include <torch/csrc/jit/jit_log.h>
#include <torch/csrc/jit/passes/integer_value_refinement.h>
#include <torch/csrc/jit/passes/value_refinement_utils.h>
#include <torch/csrc/utils/memory.h>
#include <utility>
namespace torch {
namespace jit {
using IntegerRefinement = std::unordered_map<Value*, int64_t>;
// see [value refinement algorithm] for full explanation.
// When a comparison like `cond = x == 4` or `cond = x != 4` is made,
// `cond` value carries information (refinements) about the value of `x`.
// in an example like:
// if x == 1:
// ...
// we can substitute all uses of x dominated by the true block
// with 1.
struct IntegerValueRefiner {
IntegerValueRefiner(std::shared_ptr<Graph> graph)
: graph_(std::move(graph)) {}
bool run() {
if (!blockHasIntComparisons(graph_->block())) {
return false;
}
IntegerRefinement refinements;
RefineIntegerValues(graph_->block(), std::move(refinements));
return changed_;
}
bool blockHasIntComparisons(Block* b) {
for (Node* n : b->nodes()) {
if (n->matches("aten::eq(int a, int b) -> bool") ||
n->matches("aten::ne(int a, int b) -> bool")) {
for (size_t const_index : {0, 1}) {
auto non_const_index = 1 - const_index;
if (n->inputs().at(const_index)->node()->kind() == prim::Constant &&
n->inputs().at(non_const_index)->uses().size() > 1) {
return true;
}
}
}
for (Block* block : n->blocks()) {
if (blockHasIntComparisons(block)) {
return true;
}
}
}
return false;
}
void removeIfNodeOutputsWithRefinements(
Node* if_node,
IntegerRefinement& true_block_refinements,
IntegerRefinement& false_block_refinements) {
// we are looking for cases where we can replace both block outputs with the
// same value, which opens up further optimization opportunities. The pass
// will already handle if both outputs are refined to the same constant.
// Here, we look for cases where one block output has been refined in the
// other block to be equal to the same constant value as the other other
// block output:
// graph(%y.1 : int):
// %one_constant : int = prim::Constant[value=1]()
// %3 : bool = aten::eq(%y.1, %one_constant)
// %15 : int = prim::If(%3)
// block0():
// -> (%one_constant)
// block1():
// -> (%y.1)
// return (%15)
// %15 can always be safely replaced with %y.1
// this is an important case for symbolic shape analysis
for (size_t block_index : {0, 1}) {
Block* if_block = if_node->blocks().at(block_index);
Block* other_if_block = if_node->blocks().at(1 - block_index);
for (size_t i = 0; i < if_node->outputs().size(); ++i) {
Value* block_output = if_block->outputs().at(i);
if (!block_output->type()->cast<IntType>()) {
continue;
}
// Value must be in scope for both blocks
// in example above, %y.1 cannot be defined in block1
if (!if_node->isDominatedBy(block_output->node())) {
continue;
}
// one constant value one not - we are looking for the pattern
// where y.1 is refined to the existing block output %one_constant
auto other_output = other_if_block->outputs().at(i);
auto other_const_value = other_output->type()->cast<IntType>()
? constant_as<int64_t>(other_output)
: c10::nullopt;
if (!other_const_value ||
block_output->node()->kind() == prim::Constant) {
continue;
}
// here, we are looking in refinements in the other block of our
// current output. in the example, we are looking for refinements of
// %y.1 in `block0`, and we are checking that %y.1 is refined
// to the constant value of %one_constant
const auto& other_block_refinements =
block_index == 0 ? false_block_refinements : true_block_refinements;
if (!other_block_refinements.count(block_output)) {
continue;
}
if (other_block_refinements.at(block_output) == *other_const_value) {
if_node->outputs().at(i)->replaceAllUsesWith(block_output);
changed_ = true;
}
}
}
}
// iteratively look through the block `b` for refinements or Value uses that
// can be refined, `block_refinements` are the refinements present starting at
// this block (and for all blocks dominated by this block).
IntegerRefinement RefineIntegerValues(
Block* b,
IntegerRefinement block_refinements) {
active_refinements_.push_back(&block_refinements);
for (Node* n : b->nodes()) {
if (n->matches("aten::eq(int a, int b) -> bool") ||
n->matches("aten::ne(int a, int b) -> bool")) {
for (size_t const_index : {0, 1}) {
if (auto ival = constant_as<int64_t>(n->inputs().at(const_index))) {
IntegerRefinement refine;
refine[n->inputs().at(1 - const_index)] = *ival;
info_[n->output()] = n->kind() == aten::eq
? BooleanRefinementMapping::TrueRefinements(std::move(refine))
: BooleanRefinementMapping::FalseRefinements(std::move(refine));
}
}
}
for (size_t input = 0; input < n->inputs().size(); ++input) {
Value* input_v = n->inputs().at(input);
if (!input_v->type()->cast<IntType>()) {
continue;
}
if (auto refine = tryFindRefinement(input_v)) {
WithInsertPoint guard(n);
auto refine_constant =
graph_->insertConstant(static_cast<int64_t>(*refine));
n->replaceInputWith(input_v, refine_constant);
changed_ = true;
}
}
if (n->kind() == prim::If) {
IfView if_n(n);
bool has_cond_ref = info_.count(if_n.cond()) != 0;
IntegerRefinement empty;
auto true_block_refinements = RefineIntegerValues(
if_n.thenBlock(),
has_cond_ref ? info_[if_n.cond()].true_refine() : empty);
auto false_block_refinements = RefineIntegerValues(
if_n.elseBlock(),
has_cond_ref ? info_[if_n.cond()].false_refine() : empty);
removeIfNodeOutputsWithRefinements(
n, true_block_refinements, false_block_refinements);
joinIfRefinements(
n,
throwing_blocks_,
block_refinements,
true_block_refinements,
false_block_refinements,
info_);
} else {
handleCommonRefinentOperators(n, throwing_blocks_, info_);
}
}
// iterating over all nodes in the block will not iterate over
// block outputs, so we need to add handling of them.
// %3 : int = prim::Constant[value=3]()
// %4 : bool = aten::eq(%y.1, %3)
// %a : int = prim::If(%4)
// block0():
// -> (%y.1)
// Here, we can replace y.1 with 3
for (size_t i = 0; i < b->outputs().size(); ++i) {
Value* output_v = b->outputs().at(i);
if (!output_v->type()->cast<IntType>()) {
continue;
}
if (auto refine = tryFindRefinement(output_v)) {
WithInsertPoint guard(b);
auto refine_constant =
graph_->insertConstant(static_cast<int64_t>(*refine));
b->replaceOutput(i, refine_constant);
changed_ = true;
}
}
active_refinements_.pop_back();
return block_refinements;
};
c10::optional<int64_t> tryFindRefinement(Value* v) {
for (const auto& ref : active_refinements_) {
auto maybe_refinement = ref->find(v);
if (maybe_refinement != ref->end()) {
return maybe_refinement->second;
}
}
return c10::nullopt;
}
std::shared_ptr<Graph> graph_;
// A stack of active refinements, one for each block
std::vector<IntegerRefinement*> active_refinements_;
// A map from Boolean Value * -> associated refinements
std::unordered_map<Value*, BooleanRefinementMapping> info_;
std::unordered_set<Block*> throwing_blocks_;
bool changed_ = false;
};
bool RefineIntegerValues(const std::shared_ptr<Graph>& graph) {
return IntegerValueRefiner(graph).run();
}
} // namespace jit
} // namespace torch