pytorch/torch/csrc/distributed/rpc/rref_impl.cpp
Pritam Damania f1624b82b5 Preserve python backtrace in autograd engine errors. (#43684)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/43684

This PR attempts to address #42560 by capturing the appropriate
exception_ptr in the autograd engine and passing it over to the Future.

As part of this change, there is a significant change the Future API where we
now only accept an exception_ptr as part of setError.

For the example in #42560, the exception trace would now look like:

```
> Traceback (most recent call last):
>   File "test_autograd.py", line 6914, in test_preserve_backtrace
>     Foo.apply(t).sum().backward()
>   File "torch/tensor.py", line 214, in backward
>     torch.autograd.backward(self, gradient, retain_graph, create_graph)
>   File "torch/autograd/__init__.py", line 127, in backward
>     allow_unreachable=True)  # allow_unreachable flag
>   File "torch/autograd/function.py", line 87, in apply
>     return self._forward_cls.backward(self, *args)
>   File "test_autograd.py", line 6910, in backward
>     raise ValueError("something")
> ValueError: something
```
ghstack-source-id: 111109637

Test Plan: waitforbuildbot

Reviewed By: albanD

Differential Revision: D23365408

fbshipit-source-id: 1470c4776ec8053ea92a6ee1663460a3bae6edc5
2020-09-01 01:28:47 -07:00

276 lines
9.2 KiB
C++

#include <torch/csrc/distributed/rpc/rref_impl.h>
#include <ATen/record_function.h>
#include <fmt/format.h>
#include <torch/csrc/distributed/autograd/rpc_messages/rpc_with_autograd.h>
#include <torch/csrc/distributed/autograd/utils.h>
#include <torch/csrc/distributed/rpc/profiler/remote_profiler_manager.h>
#include <torch/csrc/distributed/rpc/rref_context.h>
#include <torch/csrc/distributed/rpc/rref_proto.h>
#include <torch/csrc/distributed/rpc/utils.h>
namespace {
// If the type is subtype of named type, return its qualifiedname, otherwise
// return its type str.
std::string getTypeStr(const c10::TypePtr& type) {
switch (type->kind()) {
case c10::TypeKind::FunctionType:
return type->cast<c10::FunctionType>()->name()->qualifiedName();
case c10::TypeKind::TupleType:
return type->cast<c10::TupleType>()->name()->qualifiedName();
case c10::TypeKind::ClassType:
return type->cast<c10::ClassType>()->name()->qualifiedName();
case c10::TypeKind::InterfaceType:
return type->cast<c10::InterfaceType>()->name()->qualifiedName();
default:
return type->annotation_str();
}
}
} // namespace
namespace torch {
namespace distributed {
namespace rpc {
std::atomic<local_id_t> RRefContext::nextLocalId_{0};
////////////////////////// RRefForkData /////////////////////////////////
RRefForkData::RRefForkData(
worker_id_t ownerId,
const RRefId& rrefId,
const ForkId& forkId,
worker_id_t parent,
std::string typeStr)
: ownerId_(ownerId),
rrefId_(rrefId),
forkId_(forkId),
parent_(parent),
typeStr_(std::move(typeStr)) {}
////////////////////////////// RRef /////////////////////////////////////
RRef::RRef(worker_id_t ownerId, const RRefId& rrefId, TypePtr type)
: RRefInterface(),
ownerId_(ownerId),
rrefId_(rrefId),
type_(std::move(type)) {}
RRefForkData RRef::fork() const {
auto& ctx = RRefContext::getInstance();
return RRefForkData(
ownerId_,
rrefId_,
ctx.genGloballyUniqueId(),
ctx.getWorkerId(),
getTypeStr(type_));
}
void RRef::handleError(
RPCErrorType errorType,
const FutureMessage& futMessage) {
static std::unordered_map<
RPCErrorType,
std::function<void(const FutureMessage& fm)>,
std::hash<int>>
errorHandlers = {
{RPCErrorType::TIMEOUT,
[this](const FutureMessage& /* unused */) { setTimedOut(); }},
{RPCErrorType::INTENTIONAL_FAILURE,
[this](const FutureMessage& /* unused */) { setTimedOut(); }},
{RPCErrorType::UNKNOWN_ERROR, [](const FutureMessage& fm) {
// Default error handler
RRefContext::handleException(fm);
}}};
errorHandlers.find(errorType)->second(futMessage);
}
////////////////////////// UserRRef /////////////////////////////////////
UserRRef::UserRRef(
worker_id_t ownerId,
const RRefId& rrefId,
const ForkId& forkId,
TypePtr type)
: RRef(ownerId, rrefId, std::move(type)),
forkId_(forkId),
confirmedByOwner_(false) {
// Do nothing,
// (1) If this UserRRef is a fork of an existing RRef, RRefContext will send
// a RREF_FORK_REQUEST message to the owner.
// (2) If this the creator UserRRef, ScriptRemoteCall or PythonRemoteCall will
// properly notify the owner.
}
void UserRRef::tryDel() {
std::lock_guard<std::mutex> lockGuard(deletedOnOwnerMutex_);
if (!deletedOnOwner_) {
try {
RRefContext::getInstance().delUser(ownerId_, rrefId_, forkId_);
deletedOnOwner_ = true;
} catch (const std::exception& ex) {
LOG(ERROR) << "Error occurred when deleting" << *this << " : "
<< ex.what();
} catch (...) {
LOG(ERROR) << "Error occurred when deleting" << *this << " : "
<< "unknown error";
}
}
}
void UserRRef::release_resources() {
tryDel();
}
const ForkId& UserRRef::forkId() const {
return forkId_;
}
IValue UserRRef::toHere(const float timeoutSeconds) const {
TORCH_CHECK(
!getTimedOut(),
"RRef creation via rpc.remote() timed out, and it "
"is possible that the RRef on the owner node does not exist.");
// see Note [Best-Effort Check on Deleted UserRRefs]
TORCH_CHECK(
!deletedOnOwner_,
*this,
" has been deleted. Cannot call to_here() on it after deletion.");
auto toHereKey = std::string("");
if (torch::autograd::profiler::profilerEnabled()) {
toHereKey = fmt::format(
"to_here#({})->({})",
RpcAgent::getCurrentRpcAgent()->getWorkerInfo().name_,
RpcAgent::getCurrentRpcAgent()->getWorkerInfo(ownerId_).name_);
auto& remoteProfilerManager =
torch::distributed::rpc::RemoteProfilerManager::getInstance();
remoteProfilerManager.setCurrentKey(toHereKey);
}
RECORD_USER_SCOPE(toHereKey);
TORCH_CHECK(
!type_->is_module(),
*this,
" is an RRef to a ScriptModule. "
"It can't be sent through RPC "
"from owner, ",
ownerWorkerInfo(),
", to user, ",
RpcAgent::getCurrentRpcAgent()->getWorkerInfo(),
".");
auto agent = RpcAgent::getCurrentRpcAgent();
// ScriptRRefFetchCall message always carries autograd context id even if
// the message itself does not contain any tensor, because the response would
// potentially contain tensors.
Message msgToSend;
if (isPyObj()) {
msgToSend = PythonRRefFetchCall(ownerId_, rrefId()).toMessage();
} else {
msgToSend = ScriptRRefFetchCall(ownerId_, rrefId()).toMessage();
}
auto futureResponse = autograd::sendMessageWithAutograd(
*agent,
agent->getWorkerInfo(ownerId_),
std::move(msgToSend),
true /* forceGradRecording */,
timeoutSeconds);
// TODO: we should ideally be able to interrupt this blocking wait if we check
// getTimedOut() and it is true
// (https://github.com/pytorch/pytorch/issues/39411).
const Message& message = futureResponse->wait();
MessageType msgType = message.type();
auto response = deserializeResponse(message, msgType);
TORCH_INTERNAL_ASSERT(
msgType == MessageType::SCRIPT_RREF_FETCH_RET ||
msgType == MessageType::PYTHON_RREF_FETCH_RET,
"Message type should either be SCRIPT_RREF_FETCH_RET "
"or PYTHON_RREF_FETCH_RET");
RpcCommandBase& rpc = *response;
auto& rrefFetchRet = static_cast<RRefFetchRet&>(rpc);
if (isPyObj()) {
// wrap python serialized vector of ivalues into tuple, this
// made the C++ toHere interface to return single IValue
return ivalue::Tuple::create(rrefFetchRet.values());
} else {
return rrefFetchRet.values().front();
}
}
RRefForkData UserRRef::fork() const {
// Note [Best-Effort Check on Deleted UserRRefs]
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// This check does not guarantee correctness, as there could be another thread
// trying to delete this UserRRef concurrently. Passing this check does not
// mean this RRef will be alive throughout this function. This is just our
// best-effort attempt to raise proper error messages. The behavior of using
// deleted UserRRefs is undefined.
//
// The reason for not implementing strict checks are:
// 1. This would need to acquire lock on deletedOnOwnerMutex_, which would
// introduce unnecessary overhead for most normal use cases.
// 2. This would introduce a lot of complexities to get the behavior correct.
// Assume we acquired the lock here, and there is another thread X block
// waiting in tryDel() on the lock. Exiting this fork function would
// unblock thread X. However, while X proceeds with deleting this UserRRef,
// the call site of fork() might have added the UserRRef to
// pendingChildren_ map, but up to this point, nothing prevents X from
// deleting this RRef even if it shouldn't do so due to the state change
// in pendingChildren_. We might be able to get it right for now by locking
// and checking pendingChildren_ in X, but the gain does not seem to
// worth the complexity.
TORCH_CHECK(
!deletedOnOwner_,
*this,
" has been deleted. Cannot call fork an UserRRef after deletion.");
return RRef::fork();
}
////////////////////////// OwnerRRef /////////////////////////////////////
const IValue& OwnerRRef::getValue() const {
TORCH_CHECK(
!getTimedOut(),
"RRef creation via rpc.remote() timed out, and it "
"is possible that the RRef on the owner node does not exist.");
future_->wait();
if (future_->hasError()) {
(void)future_->value(); // Throws the error.
}
return future_->constValue();
}
bool OwnerRRef::hasValue() const {
return future_->completed();
}
std::shared_ptr<JitFuture> OwnerRRef::getFuture() {
return future_;
}
void OwnerRRef::setValue(IValue&& value) {
future_->markCompleted(value);
}
void OwnerRRef::setError(std::exception_ptr eptr) {
future_->setErrorIfNeeded(std::move(eptr));
}
std::ostream& operator<<(std::ostream& os, const RRef& rref) {
if (rref.isOwner()) {
return os << "OwnerRRef("
<< "rref_id=" << rref.rrefId() << ")";
} else {
return os << "UserRRef("
<< "rref_id=" << rref.rrefId()
<< ", fork_id=" << static_cast<const UserRRef*>(&rref)->forkId()
<< ")";
}
}
} // namespace rpc
} // namespace distributed
} // namespace torch