pytorch/torch/csrc/jit/runtime/operator.cpp
Jie 2b79bab029 [CUDA_FUSER] Fork CUDA fuser (#33527)
Summary:
Separating CUDA fuser from CPU fuser.

1. New node in IR - prim::CudaFusionGroup:
   This enables the cuda fuser to co-exist along side the old fuser. Allows us
   to incrementally build and expand cuda fuser.

2. copied FuseGraph optimization passes to CudaFuserGraph:
   We will re-factor & reuse Chunk/Concat in the old fuser logic, which is
   handled in the optimization pass at this moment. Unfortunately many code in
   the pass is tightly binded with the legacy fuser, which makes code sharing
   difficult.
   The CudaFusionGraph will support only a subset of operations comparing to
   legacy fuser (CUDA only). It is registered as a custom pass post fusion via
     ```torch._C._jit_register_cuda_fuser()```
   To have it in effect, you should also turn off fusion on GPU via
     ```torch._C._jit_override_can_fuse_on_gpu(False)```

3. We don't have codegen in this PR yet (WIP). Currently we just fall back to
   the old fuser.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33527

Differential Revision: D20171598

Pulled By: ZolotukhinM

fbshipit-source-id: 9a3c0f06f46da7eaa80ae7551c04869f5b03ef71
2020-03-04 20:25:08 -08:00

352 lines
11 KiB
C++

#include <ATen/ATen.h>
#include <ATen/core/alias_info.h>
#include <torch/csrc/jit/runtime/operator.h>
#include <torch/csrc/jit/frontend/edit_distance.h>
#include <queue>
#include <utility>
#include <vector>
namespace torch {
namespace jit {
namespace {
using OperatorMap =
std::unordered_map<Symbol, std::vector<std::shared_ptr<Operator>>>;
struct OperatorRegistry {
private:
std::mutex lock;
OperatorMap operators;
// list of operators whose schema have not yet been parsed, and must
// be registered before any call to lookup an operator
std::vector<std::shared_ptr<Operator>> to_register;
// Those two maps are used to implement lookupByLiteral, which is needed for
// the n->match(...) calls. Basically, every function schema is assigned a
// unique string you can use to match it. However, parsing those strings or
// comparing and hashing them character by character would be very slow, so we
// use a trick here! Every string literal in your program is guaranteed to
// have static storage duration and so its address won't change at runtime.
// This allows us to memoize answers for every pointer, which is done by the
// operators_by_sig_literal map. Still, this map is initially empty, and so we
// still need to do the complete string matching at the first time, which is
// implemented by performing a lookup in the operators_by_sig map.
std::unordered_map<std::string, std::shared_ptr<Operator>> operators_by_sig;
std::unordered_map<const char*, std::shared_ptr<Operator>>
operators_by_sig_literal;
// XXX - caller must be holding lock
void registerPendingOperators() {
for (const auto& op : to_register) {
Symbol sym = Symbol::fromQualString(op->schema().name());
operators[sym].push_back(op);
operators_by_sig[canonicalSchemaString(op->schema())] = op;
}
to_register.clear();
}
public:
void registerOperator(Operator&& op) {
std::lock_guard<std::mutex> guard(lock);
to_register.push_back(std::make_shared<Operator>(std::move(op)));
}
const std::shared_ptr<Operator>& lookupByLiteral(const char* name) {
std::lock_guard<std::mutex> guard(lock);
registerPendingOperators();
auto it = operators_by_sig_literal.find(name);
if (it == operators_by_sig_literal.end()) {
auto op_ptr_it =
operators_by_sig.find(canonicalSchemaString(parseSchema(name)));
// Handy debugging code that dumps all operators we know about on mismatch
#if 0
if (op_ptr_it == operators_by_sig.end()) {
for (auto & entry : operators_by_sig) {
std::cout << entry.first << std::endl;
}
}
#endif
TORCH_CHECK(
op_ptr_it != operators_by_sig.end(),
"Couldn't find an operator for ",
name,
". Do you have to update a set of hardcoded JIT ops?");
it = operators_by_sig_literal.emplace_hint(it, name, op_ptr_it->second);
}
return it->second;
}
const std::vector<std::shared_ptr<Operator>>& getOperators(Symbol name) {
std::lock_guard<std::mutex> guard(lock);
registerPendingOperators();
static std::vector<std::shared_ptr<Operator>> empty;
auto it = operators.find(name);
if (it != operators.end())
return it->second;
return empty;
}
std::vector<Symbol> findSimilarOperators(Symbol input_op) {
std::lock_guard<std::mutex> guard(lock);
registerPendingOperators();
using EntryPair = std::pair<int64_t, Symbol>;
auto cmp = [](const EntryPair& lhs, const EntryPair& rhs) {
return lhs.first > rhs.first;
};
std::priority_queue<EntryPair, std::vector<EntryPair>, decltype(cmp)>
rankings(cmp);
static constexpr size_t MAX_EDIT_DIST = 2u;
for (const auto& op : operators) {
auto edit_dist = script::ComputeEditDistance(
input_op.toQualString(), op.first.toQualString(), MAX_EDIT_DIST);
if (edit_dist <= MAX_EDIT_DIST) {
rankings.emplace(edit_dist, op.first);
}
}
std::vector<Symbol> ret;
while (!rankings.empty()) {
ret.push_back(rankings.top().second);
rankings.pop();
}
return ret;
}
const std::vector<std::shared_ptr<Operator>> getAllOperators() {
std::lock_guard<std::mutex> guard(lock);
registerPendingOperators();
std::vector<std::shared_ptr<Operator>> values;
values.clear();
for (auto & kv : operators) {
values.insert(values.end(), kv.second.begin(), kv.second.end());
}
return values;
}
};
OperatorRegistry& getRegistry() {
static OperatorRegistry r;
return r;
}
bool printerHasSpecialCaseFor(Symbol sym) {
using namespace at;
// WARNING: by adding a value to this set, you are asserting
// that you have also added special handling of this symbol to
// the python_print.cpp. Not adding handling will cause import and export
// of modules with this new operator to fail. This is only required
// for operators without schema. Prefer registering your operator with
// schema to editing this list here. These cases should only be things
// that require special handling because they do not fit normal schema
const static std::unordered_set<Symbol> handled = {
prim::Constant,
prim::Uninitialized,
prim::fork,
prim::ListConstruct,
prim::DictConstruct,
prim::ListUnpack,
prim::Print,
prim::PythonOp,
prim::TupleConstruct,
prim::TupleIndex,
prim::TupleSlice,
prim::TupleUnpack,
prim::CreateObject,
prim::GetAttr,
prim::SetAttr,
prim::CallFunction,
prim::isinstance,
prim::unchecked_cast,
prim::tolist,
prim::rpc_async,
};
// WARNING: by adding a value to this set, you are asserting that your
// primitive is only ever added during optimization and does not need
// to be correctly printed for export (a process that happens before
// optimization passes run)
const static std::unordered_set<Symbol> unneeded = {
c10::onnx::Reshape, // only used in onnx
c10::onnx::Shape, // only used in onnx
prim::AutogradZero, // temporarily inserted by autograd
prim::AutogradAnyNonZero, // temporarily inserted by autograd
prim::AutogradAdd, // temporarily inserted by autograd
prim::ConstantChunk, // optimization pass adds it
prim::DifferentiableGraph, // optimization pass adds it
prim::BroadcastSizes, // optimization pass (fuser) adds it
prim::ChunkSizes, // optimization pass (fuser) adds it
prim::Drop, // used in interpreter only
prim::FusedConcat, // optimization pass adds it
prim::FusionGroup, // optimization pass adds it
prim::CudaFusionGroup, // optimization pass adds it
prim::Load, // used in interpreter only
prim::MMTreeReduce, // used as an optimization
prim::MMBatchSide, // used as an optimization
prim::Store, // used in interpreter only
prim::profile, // used in interpreter only
};
// These namespaces are required to have Python printers unless
// otherwise noted in unneeded.
const static std::unordered_set<Symbol> required_namespaces = {
c10::namespaces::prim,
c10::namespaces::aten,
c10::namespaces::onnx,
};
return handled.count(sym) || unneeded.count(sym) ||
!required_namespaces.count(sym.ns());
}
} // anonymous namespace
bool aliasAnalysisHasSpecialCaseFor(Symbol symbol) {
using namespace at;
// WARNING: by adding a case to this list, you are asserting that you have
// added a case for the unschematized node in AliasDb::analyze
const static std::unordered_set<Symbol> handled = {
prim::If,
prim::Loop,
prim::FusionGroup,
prim::CudaFusionGroup,
prim::DifferentiableGraph,
prim::Constant,
prim::Uninitialized,
prim::DictConstruct,
prim::ListConstruct,
prim::TupleConstruct,
prim::AutogradZero,
prim::FusedConcat,
prim::GradOf,
prim::MMTreeReduce,
prim::MMBatchSide,
prim::BroadcastSizes,
prim::ChunkSizes,
prim::Function,
prim::TupleUnpack,
prim::TupleIndex,
prim::TupleSlice,
prim::ListUnpack,
prim::PythonOp,
prim::ConstantChunk,
prim::BroadcastingChunk,
prim::fork,
prim::CreateObject,
prim::AutogradAdd,
prim::GetAttr,
prim::SetAttr,
prim::profile,
prim::Print,
prim::CallFunction,
prim::CallMethod,
aten::wait,
prim::isinstance,
prim::unchecked_cast,
prim::tolist,
prim::rpc_async,
};
// Operators that should not be used by alias analysis
const static std::unordered_set<Symbol> purposefully_not_handled = {
prim::Load,
prim::Store,
prim::Drop,
at::onnx::Reshape,
at::onnx::Shape,
prim::AutogradAdd,
};
return handled.count(symbol) || purposefully_not_handled.count(symbol);
}
void registerOperator(Operator&& op) {
if (op.schema().is_varret()) {
Symbol s = Symbol::fromQualString(op.schema().name());
if (!printerHasSpecialCaseFor(s)) {
AT_ERROR(
"Missing special case in python printer for non-schematized"
" operator ",
op.schema().name(),
". File a bug to add a case for this operator.\n");
}
if (!aliasAnalysisHasSpecialCaseFor(s) &&
op.aliasAnalysisKind() == AliasAnalysisKind::CONSERVATIVE) {
AT_ERROR(
"Missing special case in alias analysis for non-schematized"
" operator ",
op.schema().name(),
". File a bug to add a case for this operator.\n");
}
if (aliasAnalysisHasSpecialCaseFor(s) &&
op.aliasAnalysisKind() == AliasAnalysisKind::FROM_SCHEMA) {
AT_ERROR(
"The operator ",
op.schema().name(),
" is special cased and cannot use explicit alias analysis.");
}
}
getRegistry().registerOperator(std::move(op));
}
const std::vector<std::shared_ptr<Operator>> getAllOperators() {
return getRegistry().getAllOperators();
}
const std::vector<std::shared_ptr<Operator>>& getAllOperatorsFor(Symbol name) {
return getRegistry().getOperators(name);
}
std::shared_ptr<Operator> findOperatorFor(const c10::OperatorName& full_name) {
for (const auto& op : getRegistry().getOperators(Symbol::fromQualString(full_name.name))) {
if (op->schema().overload_name() == full_name.overload_name) {
return op;
}
}
return nullptr;
}
std::vector<Symbol> findSimilarOperators(Symbol input_op) {
return getRegistry().findSimilarOperators(input_op);
}
std::shared_ptr<Operator> getOperatorForLiteral(const char* signature) {
return getRegistry().lookupByLiteral(signature);
}
std::string canonicalSchemaString(const FunctionSchema& schema) {
std::ostringstream out;
out << schema.name();
out << "(";
bool seen_kwarg_only = false;
for (size_t i = 0; i < schema.arguments().size(); ++i) {
if (i > 0)
out << ", ";
if (schema.arguments()[i].kwarg_only() && !seen_kwarg_only) {
out << "*, ";
seen_kwarg_only = true;
}
const auto& arg = schema.arguments()[i];
out << arg.type()->str() << " " << arg.name();
}
out << ") -> ";
if (schema.returns().size() == 1) {
out << schema.returns().at(0).type()->str();
} else if (schema.returns().size() > 1) {
out << "(";
for (size_t i = 0; i < schema.returns().size(); ++i) {
if (i > 0)
out << ", ";
out << schema.returns()[i].type()->str();
}
out << ")";
}
return out.str();
}
} // namespace jit
} // namespace torch