[Enhancement] Enable timeout in dist training (#877)

* Adding missing pre-commit requirement to tests.txt

* Added support for setting a timeout for distributed learning

* Adding documentation about how to change the runtime timeout into the distributed manual.

* Fixed type in documentation to correctly specify an integer

* Removing type-cast after checking the correct type already before

* Update mmengine/dist/utils.py

Adding an explicit `is not None` to the check

Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>

* Removing explicit type check and replacing it with more pythonic way of assuming it is the right type and handling the exception if the type doesn't match.

* Removing pre-commit from test requirements again

* Simplified the code according to suggestions from PR

* Update distributed.md

---------

Co-authored-by: Mashiro <57566630+HAOCHENYE@users.noreply.github.com>
Co-authored-by: Zaida Zhou <58739961+zhouzaida@users.noreply.github.com>

docs/en/advanced_tutorials/distributed.md

@@ -23,6 +23,17 @@ We will detail on these APIs in the following chapters.
 
 - [init_dist](mmengine.dist.init_dist): Launch function of distributed training. Currently it supports 3 launchers including pytorch, slurm and MPI. It also setup the given communication backends, defaults to NCCL.
 
+  If you need to change the runtime timeout (default=30 minutes) for distributed operations that take very long, you can specify a different timeout in your `env_cfg` configuration passing in [Runner](mmengine.runner.Runner) like this:
+
+  ```python
+  env_cfg = dict(
+      cudnn_benchmark=True,
+      mp_cfg=dict(mp_start_method='fork', opencv_num_threads=0),
+      dist_cfg=dict(backend='nccl', timeout=10800), # Sets the timeout to 3h (10800 seconds)
+  )
+  runner = Runner(xxx, env_cfg=env_cfg)
+  ```
+
 ## Query and control
 
 The query and control functions are all argument free.

mmengine/dist/utils.py

 # Copyright (c) OpenMMLab. All rights reserved.
+import datetime
 import functools
 import os
 import subprocess
@@ -50,6 +51,19 @@ def init_dist(launcher, backend='nccl', **kwargs) -> None:
             'gloo' and 'mpi'. Defaults to 'nccl'.
         **kwargs: keyword arguments are passed to ``init_process_group``.
     """
+    timeout = kwargs.get('timeout', None)
+    if timeout is not None:
+        # If a timeout (in seconds) is specified, it must be converted
+        # to a timedelta object before forwarding the call to
+        # the respective backend, because they expect a timedelta object.
+        try:
+            kwargs['timeout'] = datetime.timedelta(seconds=timeout)
+        except TypeError as exception:
+            raise TypeError(
+                f'Timeout for distributed training must be provided as '
+                f"timeout in seconds, but we've received the type "
+                f'{type(timeout)}. Please specify the timeout like this: '
+                f"dist_cfg=dict(backend='nccl', timeout=1800)") from exception
     if mp.get_start_method(allow_none=True) is None:
         mp.set_start_method('spawn')
     if launcher == 'pytorch':

mmengine/runner/runner.py

@@ -625,7 +625,7 @@ class Runner:
                     mp_start_method='fork',
                     opencv_num_threads=0
                 ),
-                dist_cfg=dict(backend='nccl'),
+                dist_cfg=dict(backend='nccl', timeout=1800),
                 resource_limit=4096
             )