pytorch/torch/csrc/distributed/rpc/rref_impl.cpp
Shihao Xu 3d0279862d Consolidate builtin/python_udf RPC to return ivalue::Future like torchscript RPC does (#35154)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35154

This is for issue https://github.com/pytorch/pytorch/issues/34999.

close https://github.com/pytorch/pytorch/issues/34999.

https://github.com/pytorch/pytorch/issues/34997 need more work.

This will make a few work items easier, like 1) Dist autograd profiler, 2) JIT annotation for Future.

Test Plan:
```
buck test mode/dev-nosan //caffe2/test/distributed/rpc:rpc_fork

buck test mode/dev-nosan //caffe2/test/distributed/rpc:rpc_fork -- test_rref_forward_chain --stress-runs 100

buck build mode/dev-nosan //caffe2/test/distributed/rpc:rpc_fork && \
buck-out/gen/caffe2/test/distributed/rpc/rpc_fork\#binary.par \
-r test_call_method_on_rref
```

buck test mode/dev-nosan //caffe2/test/distributed/rpc:rpc_fork -- 'test_rref_proxy_class \(fb\.test_rpc_fork\.RpcTestWithFork\)' --stress-runs 100

test_rref_proxy_reuse
test_handle_send_exceptions

```
buck test mode/dev-nosan //caffe2/test/distributed/rpc/jit:rpc_fork

buck build mode/dev-nosan //caffe2/test/distributed/rpc/jit:rpc_fork && \
buck-out/gen/caffe2/test/distributed/rpc/jit/rpc_fork\#binary.par \
-r test_script_call_python_return_future
```

Differential Revision: D7722184

fbshipit-source-id: bd92b855bfea4913d6672700590c57622fa86e0e
2020-05-08 21:28:56 -07:00

228 lines
7.3 KiB
C++

#include <torch/csrc/distributed/rpc/rref_impl.h>
#include <torch/csrc/distributed/autograd/rpc_messages/rpc_with_autograd.h>
#include <torch/csrc/distributed/autograd/utils.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->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_));
}
////////////////////////// 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 UserRRef instance, "
<< "RRefId = " << rrefId_ << ", ForkId = " << forkId_ << " : "
<< ex.what();
} catch (...) {
LOG(ERROR) << "Error occurred when deleting UserRRef instance, "
<< "RRefId = " << rrefId_ << ", ForkId = " << forkId_ << " : "
<< "unknown error";
}
}
}
void UserRRef::release_resources() {
tryDel();
}
const ForkId& UserRRef::forkId() const {
return forkId_;
}
IValue UserRRef::toHere() {
// see Note [Best-Effort Check on Deleted UserRRefs]
TORCH_CHECK(
!deletedOnOwner_,
"User RRef with RRefId=",
rrefId(),
" and ForkId=",
forkId(),
" has been deleted. Cannot call to_here() on it after deletion.");
TORCH_CHECK(
!type_->is_module(),
"User RRef with RRefId=",
rrefId(),
" and ForkId=",
forkId(),
" is an RRef to a ScriptModule. "
"It can't be sent through RPC "
"from owner, ",
ownerName(),
", to user, ",
RpcAgent::getCurrentRpcAgent()->getWorkerInfo().name_,
".");
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 */);
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_,
"User RRef with RRefId=",
rrefId(),
" and ForkId=",
forkId(),
" has been deleted. Cannot call fork an UserRRef after deletion.");
return RRef::fork();
}
////////////////////////// OwnerRRef /////////////////////////////////////
const IValue& OwnerRRef::getValue() const {
future_->wait();
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(const std::string& error) {
future_->setErrorIfNeeded(error);
}
} // namespace rpc
} // namespace distributed
} // namespace torch