This adds a non-blocking mode to queue_pop. This allows for workers to poll if work is ready without blocking the main loop. This is useful for the case where you want to have a GPU have maximum utilization when something only periodically is sent on the queue.
We also expose a `torch.distributed.QueueEmptyError` so users can catch the error and handle it accordingly.
Test plan:
```
pytest test/distributed/test_store.py -k queue -v -s -x
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/151485
Approved by: https://github.com/fduwjj, https://github.com/tianfengfrank
This adds queue operations as described in https://github.com/pytorch/pytorch/issues/150943.
This works by adding two new operations `queue_push` and `queue_pop`. The semantics are designed to be blocking with a timeout. Pushing will always succeed as the queue is infinite size. Popping will first call `wait` until the key is ready and then pop the value from the queue.
This implements queues for only: HashStore, TCPStore w/ libuv. FileStore and the legacy backends are not supported.
`wait` and `check` work for queue operations though queue_push will only wake up the first waiter rather than all of them.
This also has a few cleanups to error types/documentation in related code.
Example trace:
```
[I409 16:51:43.963833529 TCPStoreLibUvBackend.cpp:829] [c10d - trace] validate magic:1015412686 address:[localhost]:55816
[I409 16:51:43.963845838 TCPStoreLibUvBackend.cpp:842] [c10d - trace] ping nonce:2840795 address:[localhost]:55816
[I409 16:51:43.963902914 TCPStoreLibUvBackend.cpp:911] [c10d - trace] add key:init/ val:1 address:[localhost]:55816
[I409 16:51:43.963939389 TCPStoreLibUvBackend.cpp:977] [c10d - trace] wait key_count:1 keys[0]:init/ address:[localhost]:55816
[I409 16:51:43.963974842 TCPStoreLibUvBackend.cpp:893] [c10d - trace] get key:init/ address:[localhost]:55816
[I409 16:51:43.964071909 TCPStoreLibUvBackend.cpp:1121] [c10d - trace] queue_push key:/test_prefix/test_queue_support address:[localhost]:55816
[I409 16:51:43.964080221 TCPStoreLibUvBackend.cpp:940] [c10d - trace] check key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964108584 TCPStoreLibUvBackend.cpp:1121] [c10d - trace] queue_push key:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964123207 TCPStoreLibUvBackend.cpp:1121] [c10d - trace] queue_push key:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964128194 TCPStoreLibUvBackend.cpp:940] [c10d - trace] check key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964156347 TCPStoreLibUvBackend.cpp:977] [c10d - trace] wait key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964187493 TCPStoreLibUvBackend.cpp:977] [c10d - trace] wait key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964217709 TCPStoreLibUvBackend.cpp:1133] [c10d - trace] queue_pop key:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964324300 TCPStoreLibUvBackend.cpp:977] [c10d - trace] wait key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964354495 TCPStoreLibUvBackend.cpp:1133] [c10d - trace] queue_pop key:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964416299 TCPStoreLibUvBackend.cpp:940] [c10d - trace] check key_count:1 keys[0]:/test_prefix/foo address:[localhost]:55816
[I409 16:51:43.964458733 TCPStoreLibUvBackend.cpp:977] [c10d - trace] wait key_count:1 keys[0]:/test_prefix/non_existant address:[localhost]:55816
[W409 16:51:43.974516585 socket.cpp:460] [c10d] waitForInput: poll for socket SocketImpl(fd=75, addr=[localhost]:55816, remote=[localhost]:46641) returned 0, likely a timeout
[W409 16:51:43.974559169 socket.cpp:485] [c10d] waitForInput: socket SocketImpl(fd=75, addr=[localhost]:55816, remote=[localhost]:46641) timed out after 10ms
[I409 16:51:43.974600451 TCPStoreLibUvBackend.cpp:1101] [c10d - trace] cancel_wait address:[localhost]:55816
```
Test plan:
```
$ pytest test/distributed/test_store.py -k queue -v -s
test/distributed/test_store.py::FileStoreTest::test_queues SKIPPED [0.4351s] (Store does not support queues)
test/distributed/test_store.py::HashStoreTest::test_queues PASSED [0.0009s]
test/distributed/test_store.py::PrefixFileStoreTest::test_queues SKIPPED [0.0006s] (Store does not support queues)
test/distributed/test_store.py::TCPStoreTest::test_queues SKIPPED [0.0012s] (Store does not support queues)
test/distributed/test_store.py::LibUvTCPStoreTest::test_queues PASSED [0.0014s]
test/distributed/test_store.py::PrefixTCPStoreTest::test_queues PASSED [0.0014s]
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150969
Approved by: https://github.com/XilunWu, https://github.com/fduwjj
This adds a new `clone()` method to Store which will return a new Store instance that can be used from a different thread.
This is intended to better support multiple threads with stores such as when ProcessGroupNCCL needs a store to do error propagation.
Related issue: https://github.com/pytorch/pytorch/issues/150943
Test plan:
```
pytest test/distributed/test_store.py -k PythonStore
pytest test/distributed/test_store.py -k clone
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150966
Approved by: https://github.com/fduwjj
We have a plethora of error types for various errors raised from c10d. These include `RuntimeError`, `TimeoutError`, `SocketError`, `DistBackendError` etc.
This results in messy code during error handling somewhat like this:
```
if "NCCL" in exception_str:
...
if "Timed out initializing process group in store based barrier on rank" in exception_str:
...
if "The client socket has timed out after" in exception_str:
...
if "Broken pipe" in exception_str:
...
if "Connection reset by peer" in exception_str:
...
```
To address this issue, in this PR I've ensured added these error types:
1. **DistError** - the base type of all distributed errors
2. **DistBackendError** - this already existed and referred to PG backend errors
3. **DistStoreError** - for errors originating from the store
4. **DistNetworkError** - for general network errors coming from the socket library
Pull Request resolved: https://github.com/pytorch/pytorch/pull/108191
Approved by: https://github.com/H-Huang
We have a plethora of error types for various errors raised from c10d. These include `RuntimeError`, `TimeoutError`, `SocketError`, `DistBackendError` etc.
This results in messy code during error handling somewhat like this:
```
if "NCCL" in exception_str:
...
if "Timed out initializing process group in store based barrier on rank" in exception_str:
...
if "The client socket has timed out after" in exception_str:
...
if "Broken pipe" in exception_str:
...
if "Connection reset by peer" in exception_str:
...
```
To address this issue, in this PR I've ensured added these error types:
1. **DistError** - the base type of all distributed errors
2. **DistBackendError** - this already existed and referred to PG backend errors
3. **DistStoreError** - for errors originating from the store
4. **DistNetworkError** - for general network errors coming from the socket library
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107651
Approved by: https://github.com/H-Huang
…c10d
Fixes a broken header filters from #90699 and applies a few more clang-tidy fixes that are relevant from c10 and c10d. The header filter pattern was actually broken and the clang-tidy include pattern was redundant. Also fixed a few bugs in torch/distributed/c10d
Pull Request resolved: https://github.com/pytorch/pytorch/pull/91178
Approved by: https://github.com/ezyang
Headers under torch/csrc/distributed may be referened with relative path, e.g., "<c10d/...>". However, relative path cannot be gracefully handled by Meta internal build when the NCCL PG is hipified to support AMD/RCCL because the "hipified" header files are generated in other directories. Moreover, using absolute path for header inclusion is the state-of-the-art in most components in Pytorch. Thus, this patch refactors all header paths in torch/csrc/distributed to be absolute.
See D39835774 for more details about Meta internal complication.
**How to test**: commit 9e5d199 removes -I./torch/csrc/distributed in compile options. Thus use it to verify we don't miss any relative path use of torch/csrc/distributed headers.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/85780
Approved by: https://github.com/kumpera, https://github.com/huydhn
Headers under torch/csrc/distributed may be referened with relative path, e.g., "<c10d/...>". However, relative path cannot be gracefully handled by Meta internal build when the NCCL PG is hipified to support AMD/RCCL because the "hipified" header files are generated in other directories. Moreover, using absolute path for header inclusion is the state-of-the-art in most components in Pytorch. Thus, this patch refactors all header paths in torch/csrc/distributed to be absolute.
See D39835774 for more details about Meta internal complication.
**How to test**: commit 9e5d199 removes -I./torch/csrc/distributed in compile options. Thus use it to verify we don't miss any relative path use of torch/csrc/distributed headers.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/85780
Approved by: https://github.com/kumpera
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60543
Since now c10d is part of libtorch, it would also be nice if the sources lived all in one place.
ghstack-source-id: 132306292
Test Plan: It builds
Reviewed By: cbalioglu
Differential Revision: D29062002
fbshipit-source-id: d9e1301e9d73e1643fa0f0119cd2d618f1ad52e6
