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paddlepaddle--paddle/python/paddle/distributed/launch/controllers/watcher.py
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2026-07-13 12:40:42 +08:00

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3.2 KiB
Python

# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import time
from threading import Thread
import paddle
from ..utils.nvsmi import get_gpu_info, get_gpu_process, get_gpu_util
class Watcher:
def __init__(self, ctx):
self.ctx = ctx
self.interval = 5
self.gpu_util = []
if not self.ctx.args.enable_gpu_log:
return
if paddle.is_compiled_with_rocm():
return
# gpu log file
self.gpus = self.ctx.args.devices or self.ctx.node.device.labels
if len(self.gpus) > 0:
fn = os.path.join(
self.ctx.args.log_dir, f"{self.ctx.args.job_id}.gpu.log"
)
os.makedirs(os.path.dirname(fn), exist_ok=True)
self.gpu_fd = open(fn, 'w')
else:
return
# start
self.proc = Thread(target=self.watch)
self.proc.daemon = True
self.proc.start()
def watch(self):
if not len(self.gpus) > 0:
return
self._print_gpu_info()
util_key = "index,utilization_gpu,memory_total,memory_used,memory_free,timestamp"
self.gpu_fd.write(util_key)
self.gpu_fd.write('\n')
while not self.ctx.status.is_done():
self._save_gpu_log(util_key)
time.sleep(self.interval)
if hasattr(self, "gpu_fd"):
self.gpu_fd.close()
def _print_gpu_info(self):
try:
info_key = "index,uuid,driver_version,name,gpu_serial,display_active,display_mode"
self.gpu_fd.write(info_key)
self.gpu_fd.write('\n')
for line in get_gpu_info(self.gpus):
self.gpu_fd.write(line.str(info_key))
self.gpu_fd.write('\n')
self.gpu_fd.write('\n')
process_key = "pid,process_name,gpu_uuid,gpu_name,used_memory"
self.gpu_fd.write(process_key)
self.gpu_fd.write('\n')
for line in get_gpu_process(self.gpus):
self.gpu_fd.write(line.str(process_key))
self.gpu_fd.write('\n')
self.gpu_fd.write('\n')
self.gpu_fd.flush()
except Exception as e:
self.ctx.logger.warning(f"save gpu info failed: {e!s}")
def _save_gpu_log(self, util_key):
try:
for line in get_gpu_util(self.gpus):
self.gpu_fd.write(line.str(util_key))
self.gpu_fd.write('\n')
self.gpu_fd.flush()
except Exception as e:
self.ctx.logger.warning(f"save gpu log failed: {e!s}")
def stop(self):
if hasattr(self, "proc"):
# daemon without join
# self.proc.join()
pass