watcher.py 3.0 KB
Newer Older
1
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
2
#
3 4 5
# 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
6
#
7
#     http://www.apache.org/licenses/LICENSE-2.0
8
#
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
# 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.

from ..utils.nvsmi import get_gpu_process, get_gpu_util, get_gpu_info
import time
import os

from threading import Thread


class Watcher(object):
    def __init__(self, ctx):
        self.ctx = ctx

K
kuizhiqing 已提交
26
        self.interval = 30
27 28 29 30 31 32

        self.gpu_util = []

        # gpu log file
        self.gpus = self.ctx.args.devices or self.ctx.node.device.labels
        if len(self.gpus) > 0:
33 34 35
            fn = os.path.join(
                self.ctx.args.log_dir, "{}.gpu.log".format(self.ctx.args.job_id)
            )
36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82
            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:
K
kuizhiqing 已提交
83
            self.ctx.logger.warning("save gpu info failed")
84 85 86 87 88 89 90 91

    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:
K
kuizhiqing 已提交
92
            self.ctx.logger.warning("save gpu log failed")
93 94 95

    def stop(self):
        if hasattr(self, "proc"):
K
kuizhiqing 已提交
96 97 98
            # daemon without join
            # self.proc.join()
            pass