Summary: Today, on a segfault on a single trainer , we end up keeping the gpu on all ranks blocked for 5 minutes due to elastic agents barrier timeouts
Test Plan: Rely on existing test to validate . Looking to get some feedback on adding UTs
Differential Revision: D44929488
Pull Request resolved: https://github.com/pytorch/pytorch/pull/99051
Approved by: https://github.com/kurman, https://github.com/kiukchung
Summary:
Calls to this function without an argument will get a stack trace at
import time. This is expensive, we can just skip it by passing in a value.
Test Plan: Wait for tests
Differential Revision: D44244345
Pull Request resolved: https://github.com/pytorch/pytorch/pull/97274
Approved by: https://github.com/kiukchung
Preferring dash over underscore in command-line options. Add `--command-arg-name` to the argument parser. The old arguments with underscores `--command_arg_name` are kept for backward compatibility.
Both dashes and underscores are used in the PyTorch codebase. Some argument parsers only have dashes or only have underscores in arguments. For example, the `torchrun` utility for distributed training only accepts underscore arguments (e.g., `--master_port`). The dashes are more common in other command-line tools. And it looks to be the default choice in the Python standard library:
`argparse.BooleanOptionalAction`: 4a9dff0e5a/Lib/argparse.py (L893-L895)
```python
class BooleanOptionalAction(Action):
def __init__(...):
if option_string.startswith('--'):
option_string = '--no-' + option_string[2:]
_option_strings.append(option_string)
```
It adds `--no-argname`, not `--no_argname`. Also typing `_` need to press the shift or the caps-lock key than `-`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94505
Approved by: https://github.com/ezyang, https://github.com/seemethere
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73982
Currently there is no way for users using torchelastic to override NCCL_ASYNC_ERROR_HANDLING=0. This PR enables this.
Test Plan:
Added unittests
Manual testing
```
$ torchx run fb.dist.ddp -- --img torchx_examples -m print_env_vars.py --env NCCL_ASYNC_ERROR_HANDLING=0
```
Validated the NCCL_ASYNC_ERROR_HANDLING in the process running `print_env_vars.py` is indeed `0`.
Reviewed By: mannatsingh, aivanou
Differential Revision: D34765786
fbshipit-source-id: 3f9f6d3b61e7d265adf689d387e020ab534c9259
(cherry picked from commit 2b787b46c6d37f049fe39eb64eecedf68799e75c)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66182
closes https://github.com/pytorch/pytorch/issues/63174
Does a few things:
1. adds hostname to the error report
2. moves the "root cause" section to the end (presumably since the logs are being "tailed" we want the root cause to appear at the end)
3. moves redundant error info logging to debug
4. makes the border max 60 char in length and justifies left for the header
NOTE: YOU HAVE TO annotate your main function with torch.distributed.elastic.multiprocessing.errors.record, otherwise no traceback is printed (this is because python exception propagation does NOT work out of the both for IPC - hence the extra record annotation).
Test Plan:
Sample
```
============================================================
run_script_path FAILED
------------------------------------------------------------
Failures:
<NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
time : 2021-10-05_17:37:22
host : devvm4955.prn0.facebook.com
rank : 0 (local_rank: 0)
exitcode : 1 (pid: 3296201)
error_file: /home/kiuk/tmp/elastic/none_3_lsytqe/attempt_0/0/error.json
traceback :
Traceback (most recent call last):
File "/tmp/jetter.xr3_x6qq/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 372, in wrapper
return f(*args, **kwargs)
File "main.py", line 28, in main
raise RuntimeError(args.throws)
RuntimeError: foobar
============================================================
```
Reviewed By: cbalioglu, aivanou
Differential Revision: D31416492
fbshipit-source-id: 0aeaf6e634e23ce0ea7f6a03b12c8a9ac57246e9
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61602
The diff introduces signal handlers and SignalException that is raised when the agent process receives SIGTERM or SIGINT.
When any of these signals received, the termination handler will raise the `SignalException`. The exception will then be processed by the main agent loop. The `shutdown(signum)` will be invoked, that would propagate the received signal to the child processes. The default 30 seconds timeout introduced: if child processes will not be able gracefully terminate during this timeout, the agent process would kill the processes via SIGKILL.
Test Plan: unittests, sandcastle
Reviewed By: cbalioglu
Differential Revision: D29671783
fbshipit-source-id: 3dbca2125676dc18d417cc3e3bb0301fdd42737a
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/61294
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60925
* Make `torch.distributed.launch` restarts to 0
* Remove unnecessary `-use_env` warning, move `-use_env` warnings
* Move `-use_env` warnings to `torch.distributed.launch`
* Make default log level WARNING
* Add new doc section around transitioning to `torch.distributed.run`
* Make `torch.distributed.launch` not use error-propagation
* Set default events handler to `null` that does not print events to console
* Add reference from `torch.distributed.launch` to `torch.distributed.run`
* Set correct preexec function that sends SIGTERM to child processes when parent dies
Issues resolved:
https://github.com/pytorch/pytorch/issues/60716https://github.com/pytorch/pytorch/issues/60754
Test Plan:
sandcastle
python -m torch.distributed.launch --nproc_per_node 2 main.py -> uses 0 restarts
python -m torch.distributed.run --nproc_per_node 2 main.py -> uses default for torchelastic, 0 restarts
python -m torch.distributed.launch --nproc_per_node=4 --use_env --no_python main.py -> produces error
python -m torch.distributed.launch --nproc_per_node=4 --use_env main.py -> no warning
python -m torch.distributed.launch --nproc_per_node=4 --no_python main.py ->warning
Output of running torch.distributed.launch without --use_env:
$path/torch/distributed/launch.py:173: FutureWarning: The module torch.distributed.launch is deprecated
and will be removed in future. Use torch.distributed.run.
Note that --use_env is set by default in torch.distributed.run.
If your script expects `--local_rank` argument to be set, please
change it to read from `os.environ('LOCAL_RANK')` instead.
New section:
{F628923078}
{F628974089}
Reviewed By: cbalioglu
Differential Revision: D29559553
fbshipit-source-id: 03ed9ba638bf154354e1530ffc964688431edf6b
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/60925
* Make `torch.distributed.launch` restarts to 0
* Remove unnecessary `-use_env` warning, move `-use_env` warnings
* Move `-use_env` warnings to `torch.distributed.launch`
* Make default log level WARNING
* Add new doc section around transitioning to `torch.distributed.run`
* Make `torch.distributed.launch` not use error-propagation
* Set default events handler to `null` that does not print events to console
* Add reference from `torch.distributed.launch` to `torch.distributed.run`
* Set correct preexec function that sends SIGTERM to child processes when parent dies
Issues resolved:
https://github.com/pytorch/pytorch/issues/60716https://github.com/pytorch/pytorch/issues/60754
Test Plan:
sandcastle
python -m torch.distributed.launch --nproc_per_node 2 main.py -> uses 0 restarts
python -m torch.distributed.run --nproc_per_node 2 main.py -> uses default for torchelastic, 0 restarts
python -m torch.distributed.launch --nproc_per_node=4 --use_env --no_python main.py -> produces error
python -m torch.distributed.launch --nproc_per_node=4 --use_env main.py -> no warning
python -m torch.distributed.launch --nproc_per_node=4 --no_python main.py ->warning
Output of running torch.distributed.launch without --use_env:
$path/torch/distributed/launch.py:173: FutureWarning: The module torch.distributed.launch is deprecated
and will be removed in future. Use torch.distributed.run.
Note that --use_env is set by default in torch.distributed.run.
If your script expects `--local_rank` argument to be set, please
change it to read from `os.environ('LOCAL_RANK')` instead.
New section:
{F628923078}
{F628974089}
Reviewed By: kiukchung, cbalioglu
Differential Revision: D29413019
fbshipit-source-id: 323bfbad9d0e4aba3b10ddd7a243ca6e48169630
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56739
The diff makes several tiny changes:
* Add logs for each worker error file destination
* Make sure log_dir is propagated from the launcher
* Make ProcessFailure initialization error non-fatal.
Test Plan:
buck test mode/dev-nosan //caffe2/test/distributed/elastic/multiprocessing/errors:api_test
https://fburl.com/tupperware/0nizb9z8
Reviewed By: borovsky-d, wilson100hong
Differential Revision: D27952596
fbshipit-source-id: 69582bf4be47758def4008f2abf82d123294cd1a
Summary:
As this diff shows, currently there are a couple hundred instances of raw `noqa` in the codebase, which just ignore all errors on a given line. That isn't great, so this PR changes all existing instances of that antipattern to qualify the `noqa` with respect to a specific error code, and adds a lint to prevent more of this from happening in the future.
Interestingly, some of the examples the `noqa` lint catches are genuine attempts to qualify the `noqa` with a specific error code, such as these two:
```
test/jit/test_misc.py:27: print(f"{hello + ' ' + test}, I'm a {test}") # noqa E999
test/jit/test_misc.py:28: print(f"format blank") # noqa F541
```
However, those are still wrong because they are [missing a colon](https://flake8.pycqa.org/en/3.9.1/user/violations.html#in-line-ignoring-errors), which actually causes the error code to be completely ignored:
- If you change them to anything else, the warnings will still be suppressed.
- If you add the necessary colons then it is revealed that `E261` was also being suppressed, unintentionally:
```
test/jit/test_misc.py:27:57: E261 at least two spaces before inline comment
test/jit/test_misc.py:28:35: E261 at least two spaces before inline comment
```
I did try using [flake8-noqa](https://pypi.org/project/flake8-noqa/) instead of a custom `git grep` lint, but it didn't seem to work. This PR is definitely missing some of the functionality that flake8-noqa is supposed to provide, though, so if someone can figure out how to use it, we should do that instead.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56272
Test Plan:
CI should pass on the tip of this PR, and we know that the lint works because the following CI run (before this PR was finished) failed:
- https://github.com/pytorch/pytorch/runs/2365189927
Reviewed By: janeyx99
Differential Revision: D27830127
Pulled By: samestep
fbshipit-source-id: d6dcf4f945ebd18cd76c46a07f3b408296864fcb
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55687
The diff makes sure that users can transfer the following parameters:
* master_addr
* master_port
* node_rank
* use_env
The diff implement StaticTCPRendezvous that creates a store with listener on agent rank #0
The diff modifies caffe2/rendezvous: If the worker process launched with torchelastic agent, the worker processes will create a PrefixStore("worker/") from TCPStore without listener.
The diff adds macros functionality to torch/distributed/ealstic/utils that helps to resolve local_rank parameter.
Test Plan: buck test mode/dev-nosan //pytorch/elastic/torchelastic/distributed/test:launch_test
Reviewed By: cbalioglu, wilson100hong
Differential Revision: D27643206
fbshipit-source-id: 540fb26feac322cc3ec0a989fe53324755ccc4ea
Summary:
Fixes https://github.com/pytorch/pytorch/issues/54211
This was a little more annoying than expected, because the `exclude = ` key in `mypy.ini` is weird. I'll file an upstream issue about that.
I ignored one file, `torch/distributed/elastic/agent/server/api.py` that had ~8 errors that were hard to figure out. This can be done in a follow-up.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55712
Reviewed By: walterddr
Differential Revision: D27694976
Pulled By: malfet
fbshipit-source-id: 228d8be6af040343ce46595dabaca212e69ccc68
