FM / distributed

/usr/local/lib64/python3.6/site-packages/torch/distributed/

/usr/local/lib64/python3.6/site-packages/torch/distributed

Name	Size	Mode	Actions
algorithms/	-	0755	rm
autograd/	-	0755	rm
elastic/	-	0755	rm
launcher/	-	0755	rm
nn/	-	0755	rm
optim/	-	0755	rm
pipeline/	-	0755	rm
rpc/	-	0755	rm
_sharded_tensor/	-	0755	rm
_sharding_spec/	-	0755	rm
__pycache__/	-	0755	rm
argparse_util.py	3889	0644	edit dl rm
constants.py	422	0644	edit dl rm
distributed_c10d.py	122590	0644	edit dl rm
launch.py	6805	0644	edit dl rm
remote_device.py	4609	0644	edit dl rm
rendezvous.py	8635	0644	edit dl rm
run.py	26563	0644	edit dl rm
__init__.py	1810	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/distributed/__init__.py (1810B)

import os
import sys
from enum import Enum

import torch

def is_available() -> bool:
    """
    Returns ``True`` if the distributed package is available. Otherwise,
    ``torch.distributed`` does not expose any other APIs. Currently,
    ``torch.distributed`` is available on Linux, MacOS and Windows. Set
    ``USE_DISTRIBUTED=1`` to enable it when building PyTorch from source.
    Currently, the default value is ``USE_DISTRIBUTED=1`` for Linux and Windows,
    ``USE_DISTRIBUTED=0`` for MacOS.
    """
    return hasattr(torch._C, "_c10d_init")

if is_available() and not torch._C._c10d_init():
    raise RuntimeError("Failed to initialize torch.distributed")

if is_available():
    from torch._C._distributed_c10d import (
        Store,
        FileStore,
        TCPStore,
        ProcessGroup,
        PrefixStore,
        Reducer,
        Logger,
        BuiltinCommHookType,
        GradBucket,
        _DEFAULT_FIRST_BUCKET_BYTES,
        _register_comm_hook,
        _register_builtin_comm_hook,
        _broadcast_coalesced,
        _compute_bucket_assignment_by_size,
        _verify_model_across_ranks,
        _test_python_store,
        _DistributedDebugLevel,
        _get_debug_mode,
    )

if sys.platform != "win32":
        from torch._C._distributed_c10d import (
            HashStore,
            _round_robin_process_groups,
        )

from .distributed_c10d import *  # noqa: F403

# Variables prefixed with underscore are not auto imported
    # See the comment in `distributed_c10d.py` above `_backend` on why we expose
    # this.

from .distributed_c10d import (
        _backend,
        _all_gather_base,
        _reduce_scatter_base,
        _create_process_group_wrapper,
        _rank_not_in_group,
    )

from .remote_device import _remote_device

import os import sys from enum import Enum import torch def is_available() -> bool: """ Returns ``True`` if the distributed package is available. Otherwise, ``torch.distributed`` does not expose any other APIs. Currently, ``torch.distributed`` is available on Linux, MacOS and Windows. Set ``USE_DISTRIBUTED=1`` to enable it when building PyTorch from source. Currently, the default value is ``USE_DISTRIBUTED=1`` for Linux and Windows, ``USE_DISTRIBUTED=0`` for MacOS. """ return hasattr(torch._C, "_c10d_init") if is_available() and not torch._C._c10d_init(): raise RuntimeError("Failed to initialize torch.distributed") if is_available(): from torch._C._distributed_c10d import ( Store, FileStore, TCPStore, ProcessGroup, PrefixStore, Reducer, Logger, BuiltinCommHookType, GradBucket, _DEFAULT_FIRST_BUCKET_BYTES, _register_comm_hook, _register_builtin_comm_hook, _broadcast_coalesced, _compute_bucket_assignment_by_size, _verify_model_across_ranks, _test_python_store, _DistributedDebugLevel, _get_debug_mode, ) if sys.platform != "win32": from torch._C._distributed_c10d import ( HashStore, _round_robin_process_groups, ) from .distributed_c10d import * # noqa: F403 # Variables prefixed with underscore are not auto imported # See the comment in `distributed_c10d.py` above `_backend` on why we expose # this. from .distributed_c10d import ( _backend, _all_gather_base, _reduce_scatter_base, _create_process_group_wrapper, _rank_not_in_group, ) from .remote_device import _remote_device