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Revert D30279364: [codemod][lint][fbcode/c*] Enable BLACK by default
Test Plan: revert-hammer
Differential Revision:
D30279364 (b004307252)
Original commit changeset: c1ed77dfe43a
fbshipit-source-id: eab50857675c51e0088391af06ec0ecb14e2347e
This commit is contained in:
Shen Li
committed by
Facebook GitHub Bot
Facebook GitHub Bot
parent
ed0b8a3e83
commit
1022443168
@ -1,10 +1,8 @@
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# this file contains a simple parser that parses report
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# from cuda-memcheck
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class ParseError(Exception):
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"""Whenever the simple parser is unable to parse the report, this exception will be raised"""
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pass
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@ -79,25 +77,25 @@ def parse(message):
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========= ERROR SUMMARY: 4 errors
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"""
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errors = []
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HEAD = "========="
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HEAD = '========='
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headlen = len(HEAD)
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started = False
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in_message = False
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message_lines = []
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lines = message.splitlines()
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for l in lines:
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if l == HEAD + " CUDA-MEMCHECK":
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if l == HEAD + ' CUDA-MEMCHECK':
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started = True
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continue
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if not started or not l.startswith(HEAD):
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continue
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l = l[headlen + 1 :]
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if l.startswith("ERROR SUMMARY:"):
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l = l[headlen + 1:]
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if l.startswith('ERROR SUMMARY:'):
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return Report(l, errors)
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if not in_message:
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in_message = True
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message_lines = [l]
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elif l == "":
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elif l == '':
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errors.append(Error(message_lines))
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in_message = False
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else:
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@ -12,59 +12,37 @@ Example usage:
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Note that running cuda-memcheck could be very slow.
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"""
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import argparse
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import asyncio
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import multiprocessing
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import os
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import subprocess
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import sys
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import cuda_memcheck_common as cmc
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import torch
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import multiprocessing
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import argparse
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import subprocess
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import tqdm
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import os
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import sys
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import cuda_memcheck_common as cmc
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ALL_TESTS = []
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GPUS = torch.cuda.device_count()
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# parse arguments
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parser = argparse.ArgumentParser(description="Run isolated cuda-memcheck on unit tests")
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parser.add_argument(
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"filename", help="the python file for a test, such as test_torch.py"
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)
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parser.add_argument(
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"timeout",
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type=int,
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help="kill the test if it does not terminate in a certain amount of seconds",
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)
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parser.add_argument(
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"--strict",
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action="store_true",
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help="Whether to show cublas/cudnn errors. These errors are ignored by default because"
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"cublas/cudnn does not run error-free under cuda-memcheck, and ignoring these errors",
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)
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parser.add_argument(
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"--nproc",
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type=int,
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default=multiprocessing.cpu_count(),
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help="Number of processes running tests, default to number of cores in the system",
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)
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parser.add_argument(
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"--gpus",
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default="all",
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help='GPU assignments for each process, it could be "all", or : separated list like "1,2:3,4:5,6"',
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)
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parser.add_argument(
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"--ci",
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action="store_true",
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help="Whether this script is executed in CI. When executed inside a CI, this script fails when "
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"an error is detected. Also, it will not show tqdm progress bar, but directly print the error"
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"to stdout instead.",
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)
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parser.add_argument("--nohang", action="store_true", help="Treat timeout as success")
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parser.add_argument("--split", type=int, default=1, help="Split the job into pieces")
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parser.add_argument(
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"--rank", type=int, default=0, help="Which piece this process should pick"
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)
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parser.add_argument('filename', help="the python file for a test, such as test_torch.py")
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parser.add_argument('timeout', type=int, help='kill the test if it does not terminate in a certain amount of seconds')
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parser.add_argument('--strict', action='store_true',
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help='Whether to show cublas/cudnn errors. These errors are ignored by default because'
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'cublas/cudnn does not run error-free under cuda-memcheck, and ignoring these errors')
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parser.add_argument('--nproc', type=int, default=multiprocessing.cpu_count(),
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help='Number of processes running tests, default to number of cores in the system')
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parser.add_argument('--gpus', default='all',
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help='GPU assignments for each process, it could be "all", or : separated list like "1,2:3,4:5,6"')
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parser.add_argument('--ci', action='store_true',
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help='Whether this script is executed in CI. When executed inside a CI, this script fails when '
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'an error is detected. Also, it will not show tqdm progress bar, but directly print the error'
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'to stdout instead.')
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parser.add_argument('--nohang', action='store_true', help='Treat timeout as success')
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parser.add_argument('--split', type=int, default=1, help='Split the job into pieces')
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parser.add_argument('--rank', type=int, default=0, help='Which piece this process should pick')
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args = parser.parse_args()
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# Filters that ignores cublas/cudnn errors
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@ -78,42 +56,32 @@ def is_ignored_only(output):
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return False
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count_ignored_errors = 0
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for e in report.errors:
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if (
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"libcublas" in "".join(e.stack)
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or "libcudnn" in "".join(e.stack)
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or "libcufft" in "".join(e.stack)
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):
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if 'libcublas' in ''.join(e.stack) or 'libcudnn' in ''.join(e.stack) or 'libcufft' in ''.join(e.stack):
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count_ignored_errors += 1
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return count_ignored_errors == report.num_errors
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# Set environment PYTORCH_CUDA_MEMCHECK=1 to allow skipping some tests
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os.environ["PYTORCH_CUDA_MEMCHECK"] = "1"
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os.environ['PYTORCH_CUDA_MEMCHECK'] = '1'
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# Discover tests:
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# To get a list of tests, run:
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# pytest --setup-only test/test_torch.py
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# and then parse the output
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proc = subprocess.Popen(
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["pytest", "--setup-only", args.filename],
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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)
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proc = subprocess.Popen(['pytest', '--setup-only', args.filename], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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stdout, stderr = proc.communicate()
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lines = stdout.decode().strip().splitlines()
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for line in lines:
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if "(fixtures used:" in line:
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if '(fixtures used:' in line:
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line = line.strip().split()[0]
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line = line[line.find("::") + 2 :]
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line = line.replace("::", ".")
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line = line[line.find('::') + 2:]
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line = line.replace('::', '.')
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ALL_TESTS.append(line)
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# Do a simple filtering:
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# if 'cpu' or 'CPU' is in the name and 'cuda' or 'CUDA' is not in the name, then skip it
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def is_cpu_only(name):
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name = name.lower()
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return ("cpu" in name) and not ("cuda" in name)
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return ('cpu' in name) and not ('cuda' in name)
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ALL_TESTS = [x for x in ALL_TESTS if not is_cpu_only(x)]
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@ -133,7 +101,7 @@ ALL_TESTS = ALL_TESTS[start:end]
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# or as specified by the user
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progress = 0
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if not args.ci:
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logfile = open("result.log", "w")
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logfile = open('result.log', 'w')
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progressbar = tqdm.tqdm(total=len(ALL_TESTS))
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else:
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logfile = sys.stdout
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@ -142,61 +110,53 @@ else:
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class ProgressbarStub:
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def update(self, *args):
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return
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progressbar = ProgressbarStub()
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async def run1(coroutine_id):
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global progress
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if args.gpus == "all":
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if args.gpus == 'all':
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gpuid = coroutine_id % GPUS
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else:
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gpu_assignments = args.gpus.split(":")
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assert args.nproc == len(
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gpu_assignments
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), "Please specify GPU assignmnent for each process, separated by :"
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gpu_assignments = args.gpus.split(':')
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assert args.nproc == len(gpu_assignments), 'Please specify GPU assignmnent for each process, separated by :'
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gpuid = gpu_assignments[coroutine_id]
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while progress < len(ALL_TESTS):
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test = ALL_TESTS[progress]
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progress += 1
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cmd = f"CUDA_VISIBLE_DEVICES={gpuid} cuda-memcheck --error-exitcode 1 python {args.filename} {test}"
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proc = await asyncio.create_subprocess_shell(
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cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
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)
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cmd = f'CUDA_VISIBLE_DEVICES={gpuid} cuda-memcheck --error-exitcode 1 python {args.filename} {test}'
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proc = await asyncio.create_subprocess_shell(cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE)
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try:
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stdout, stderr = await asyncio.wait_for(proc.communicate(), args.timeout)
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except asyncio.TimeoutError:
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print("Timeout:", test, file=logfile)
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print('Timeout:', test, file=logfile)
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proc.kill()
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if args.ci and not args.nohang:
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sys.exit("Hang detected on cuda-memcheck")
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else:
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if proc.returncode == 0:
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print("Success:", test, file=logfile)
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print('Success:', test, file=logfile)
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else:
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stdout = stdout.decode()
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stderr = stderr.decode()
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should_display = args.strict or not is_ignored_only(stdout)
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if should_display:
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print("Fail:", test, file=logfile)
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print('Fail:', test, file=logfile)
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print(stdout, file=logfile)
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print(stderr, file=logfile)
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if args.ci:
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sys.exit("Failure detected on cuda-memcheck")
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else:
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print("Ignored:", test, file=logfile)
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print('Ignored:', test, file=logfile)
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del proc
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progressbar.update(1)
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async def main():
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tasks = [asyncio.ensure_future(run1(i)) for i in range(args.nproc)]
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for t in tasks:
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await t
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if __name__ == "__main__":
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if __name__ == '__main__':
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loop = asyncio.get_event_loop()
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loop.run_until_complete(main())
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