def test_logger_name(self):
local_log = logging.get_logger()
name_override_log = logging.get_logger("foobar")
self.assertEqual("logging_test", log.name)
self.assertEqual("logging_test", self.clazz_log.name)
self.assertEqual("logging_test", local_log.name)
self.assertEqual("foobar", name_override_log.name)
import os
import sys
import uuid
from argparse import REMAINDER, ArgumentParser
from typing import Callable, List, Tuple, Union
import torch
from torch.distributed.argparse_util import check_env, env
from torch.distributed.elastic.multiprocessing import Std
from torch.distributed.elastic.multiprocessing.errors import record
from torch.distributed.elastic.rendezvous.utils import _parse_rendezvous_config
from torch.distributed.elastic.utils import macros
from torch.distributed.elastic.utils.logging import get_logger
from torch.distributed.launcher.api import LaunchConfig, elastic_launch
log = get_logger()
def get_args_parser() -> ArgumentParser:
"""Helper function parsing the command line options."""
parser = ArgumentParser(
description="Torch Distributed Elastic Training Launcher")
#
# Worker/node size related arguments.
#
parser.add_argument(
"--nnodes",
action=env,
import sys
import uuid
from dataclasses import dataclass, field
from typing import Any, Callable, Dict, List, Optional, Union, cast, Tuple
import torch.distributed.elastic.rendezvous.registry as rdzv_registry
from torch.distributed.elastic import events, metrics
from torch.distributed.elastic.agent.server.api import WorkerSpec, WorkerState # type: ignore[import]
from torch.distributed.elastic.agent.server.local_elastic_agent import LocalElasticAgent # type: ignore[import]
from torch.distributed.elastic.multiprocessing import Std
from torch.distributed.elastic.multiprocessing.errors import ChildFailedError, record
from torch.distributed.elastic.rendezvous import RendezvousParameters
from torch.distributed.elastic.rendezvous.utils import parse_rendezvous_endpoint
from torch.distributed.elastic.utils.logging import get_logger
logger = get_logger()
@dataclass
class LaunchConfig:
"""
min_nodes: Minimum amount of nodes that the user function will
be launched on. Elastic agent ensures that the user
function start only when the min_nodes amount enters
the rendezvous.
max_nodes: Maximum amount of nodes that the user function
will be launched on.
nproc_per_node: On each node the elastic agent will launch
this amount of workers that will execute user
defined function.
rdzv_backend: rdzv_backend to use in the rendezvous (zeus-adapter, etcd).
def test_get_logger_custom_name(self):
logger1 = get_logger("test.module")
self.assertEqual("test.module", logger1.name)
def test_get_logger_none(self):
logger1 = get_logger(None)
self.assertEqual(__name__, logger1.name)
def test_get_logger(self):
logger1 = get_logger()
self.assertEqual(__name__, logger1.name)
def test_get_logger_different(self):
logger1 = get_logger("name1")
logger2 = get_logger("name2")
self.assertNotEqual(logger1.name, logger2.name)
def setUp(self):
self.clazz_log = logging.get_logger()
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch.distributed.elastic.utils.logging as logging
log = logging.get_logger()
class LoggingTest(unittest.TestCase):
def setUp(self):
self.clazz_log = logging.get_logger()
def test_logger_name(self):
local_log = logging.get_logger()
name_override_log = logging.get_logger("foobar")
self.assertEqual("logging_test", log.name)
self.assertEqual("logging_test", self.clazz_log.name)
self.assertEqual("logging_test", local_log.name)
self.assertEqual("foobar", name_override_log.name)
def test_derive_module_name(self):
module_name = logging._derive_module_name(depth=1)
self.assertEqual("logging_test", module_name)
def setUp(self):
super().setUp()
self.clazz_log = logging.get_logger()
