177 lines
5.3 KiB
Python
177 lines
5.3 KiB
Python
# Copyright (c) 2019 NVIDIA CORPORATION. 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 datetime
|
|
import logging
|
|
import os
|
|
import shutil
|
|
import sys
|
|
import time
|
|
|
|
import dllogger
|
|
import torch.utils.collect_env
|
|
|
|
import utils
|
|
|
|
|
|
class AverageMeter:
|
|
"""
|
|
Computes and stores the average and current value
|
|
"""
|
|
def __init__(self, warmup=0, keep=False):
|
|
self.reset()
|
|
self.warmup = warmup
|
|
self.keep = keep
|
|
|
|
def reset(self):
|
|
self.val = 0
|
|
self.avg = 0
|
|
self.sum = 0
|
|
self.count = 0
|
|
self.iters = 0
|
|
self.vals = []
|
|
|
|
def update(self, val, n=1):
|
|
self.iters += 1
|
|
self.val = val
|
|
|
|
if self.iters > self.warmup:
|
|
self.sum += val * n
|
|
self.count += n
|
|
self.avg = self.sum / self.count
|
|
if self.keep:
|
|
self.vals.append(val)
|
|
|
|
|
|
def log_env_info():
|
|
"""
|
|
Prints information about execution environment.
|
|
"""
|
|
logging.info('Collecting environment information...')
|
|
env_info = torch.utils.collect_env.get_pretty_env_info()
|
|
logging.info(f'{env_info}')
|
|
|
|
|
|
def benchmark(test_perplexity=None, target_perplexity=None,
|
|
test_throughput=None, target_throughput=None):
|
|
def test(achieved, target, name, higher_better=True):
|
|
passed = True
|
|
if target is not None and achieved is not None:
|
|
logging.info(f'{name} achieved: {achieved:.2f} '
|
|
f'target: {target:.2f}')
|
|
if higher_better:
|
|
result = (achieved >= target)
|
|
else:
|
|
result = (achieved <= target)
|
|
|
|
if result:
|
|
logging.info(f'{name} test passed')
|
|
else:
|
|
logging.info(f'{name} test failed')
|
|
passed = False
|
|
return passed
|
|
|
|
passed = True
|
|
passed &= test(test_perplexity, target_perplexity, 'Perplexity', False)
|
|
passed &= test(test_throughput, target_throughput, 'Throughput')
|
|
return passed
|
|
|
|
|
|
def setup_logging(log_all_ranks=True, filename=os.devnull, filemode='w'):
|
|
"""
|
|
Configures logging.
|
|
By default logs from all workers are printed to the console, entries are
|
|
prefixed with "N: " where N is the rank of the worker. Logs printed to the
|
|
console don't include timestaps.
|
|
Full logs with timestamps are saved to the log_file file.
|
|
"""
|
|
class RankFilter(logging.Filter):
|
|
def __init__(self, rank, log_all_ranks):
|
|
self.rank = rank
|
|
self.log_all_ranks = log_all_ranks
|
|
|
|
def filter(self, record):
|
|
record.rank = self.rank
|
|
if self.log_all_ranks:
|
|
return True
|
|
else:
|
|
return (self.rank == 0)
|
|
|
|
rank = utils.distributed.get_rank()
|
|
rank_filter = RankFilter(rank, log_all_ranks)
|
|
|
|
if log_all_ranks:
|
|
logging_format = "%(asctime)s - %(levelname)s - %(rank)s - %(message)s"
|
|
else:
|
|
logging_format = "%(asctime)s - %(levelname)s - %(message)s"
|
|
if rank != 0:
|
|
filename = os.devnull
|
|
|
|
logging.basicConfig(level=logging.DEBUG,
|
|
format=logging_format,
|
|
datefmt="%Y-%m-%d %H:%M:%S",
|
|
filename=filename,
|
|
filemode=filemode)
|
|
console = logging.StreamHandler(sys.stdout)
|
|
console.setLevel(logging.INFO)
|
|
if log_all_ranks:
|
|
formatter = logging.Formatter('%(rank)s: %(message)s')
|
|
else:
|
|
formatter = logging.Formatter('%(message)s')
|
|
console.setFormatter(formatter)
|
|
logging.getLogger('').addHandler(console)
|
|
logging.getLogger('').addFilter(rank_filter)
|
|
|
|
|
|
def setup_dllogger(enabled=True, filename=os.devnull):
|
|
rank = utils.distributed.get_rank()
|
|
|
|
if enabled and rank == 0:
|
|
backends = [
|
|
dllogger.JSONStreamBackend(
|
|
dllogger.Verbosity.VERBOSE,
|
|
filename,
|
|
),
|
|
]
|
|
dllogger.init(backends)
|
|
else:
|
|
dllogger.init([])
|
|
|
|
|
|
def create_exp_dir(dir_path, scripts_to_save=None, debug=False):
|
|
if debug:
|
|
return
|
|
|
|
os.makedirs(dir_path, exist_ok=True)
|
|
|
|
print('Experiment dir : {}'.format(dir_path))
|
|
if scripts_to_save is not None:
|
|
script_path = os.path.join(dir_path, 'scripts')
|
|
os.makedirs(script_path, exist_ok=True)
|
|
for script in scripts_to_save:
|
|
dst_file = os.path.join(dir_path, 'scripts', os.path.basename(script))
|
|
shutil.copyfile(script, dst_file)
|
|
|
|
|
|
def build_work_dir_name(work_dir, dataset, append_dataset, append_time):
|
|
if append_dataset:
|
|
work_dir = '{}-{}'.format(work_dir, dataset)
|
|
|
|
if append_time:
|
|
now = int(time.time())
|
|
now_max = utils.distributed.all_reduce_item(now, op='max')
|
|
now_str = datetime.datetime.fromtimestamp(now_max).strftime('%Y%m%d-%H%M%S')
|
|
|
|
work_dir = os.path.join(work_dir, now_str)
|
|
return work_dir
|