Files
mesa/.gitlab-ci/lava/utils/lava_log_hints.py
Deborah Brouwer 72c182f873 ci/lava: Detect a6xx gpu recovery failures
Sporadically a6xx gpu will fail to recover causing the lava job
a660_vk_full to loop on error messages for three hours before timing
out.

A few sporadic error messages may still be recoverable, but when multiple
errors occur over a short period, successful recovery is unlikely. Parse
the logs to look for repeated error messages within a short time period.
If found, cancel the lava job and rerun it.

Also add unit tests for this behaviour.

cc: mesa-stable

Reported-by: Valentine Burley <valentine.burley@gmail.com>
Acked-by: Daniel Stone <daniel.stone@collabora.com>
Reviewed-by: Guilherme Gallo <guilherme.gallo@collabora.com>
Signed-off-by: Deborah Brouwer <deborah.brouwer@collabora.com>
Part-of: <https://gitlab.freedesktop.org/mesa/mesa/-/merge_requests/30032>
2024-07-19 23:41:13 +00:00

107 lines
4.1 KiB
Python

from __future__ import annotations
import re
from datetime import datetime, timedelta
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, Optional, Sequence
if TYPE_CHECKING:
from lava.utils import LogFollower
from lava.exceptions import MesaCIKnownIssueException
from lava.utils.console_format import CONSOLE_LOG
from lava.utils.constants import (
KNOWN_ISSUE_R8152_MAX_CONSECUTIVE_COUNTER,
LOG_DEBUG_FEEDBACK_NOISE,
KNOWN_ISSUE_R8152_PATTERNS,
A6XX_GPU_RECOVERY_WATCH_PERIOD_MIN,
A6XX_GPU_RECOVERY_FAILURE_MESSAGE,
A6XX_GPU_RECOVERY_FAILURE_MAX_COUNT,
)
from lava.utils.log_section import LogSectionType
def search_known_issue_patterns(patterns: Sequence[str], line: str) -> str:
for pattern in patterns:
if re.search(pattern, line):
return pattern
return ""
@dataclass
class LAVALogHints:
log_follower: LogFollower
r8152_issue_consecutive_counter: int = field(default=0, init=False)
reboot_counter: int = field(default=0, init=False)
a6xx_gpu_recovery_fail_counter: int = field(default=0, init=False)
a6xx_gpu_first_fail_time: Optional[datetime] = field(default=None, init=False)
def raise_known_issue(self, message) -> None:
raise MesaCIKnownIssueException(
"Found known issue: "
f"{CONSOLE_LOG['FG_MAGENTA']}"
f"{message}"
f"{CONSOLE_LOG['RESET']}"
)
def detect_failure(self, new_lines: list[dict[str, Any]]):
for line in new_lines:
if line["msg"] == LOG_DEBUG_FEEDBACK_NOISE:
continue
self.detect_r8152_issue(line)
self.detect_forced_reboot(line)
self.detect_a6xx_gpu_recovery_failure(line)
def detect_r8152_issue(self, line):
if self.log_follower.phase in (
LogSectionType.LAVA_BOOT,
LogSectionType.TEST_CASE,
) and line["lvl"] in ("feedback", "target"):
if search_known_issue_patterns(KNOWN_ISSUE_R8152_PATTERNS, line["msg"]):
if (
self.r8152_issue_consecutive_counter
< KNOWN_ISSUE_R8152_MAX_CONSECUTIVE_COUNTER
):
self.r8152_issue_consecutive_counter += 1
return
self.raise_known_issue(
"Probable network issue failure encountered, retrying the job"
)
# Reset the status, as the `nfs... still trying` complaint was not detected
self.r8152_issue_consecutive_counter = 0
def detect_forced_reboot(self, line: dict[str, Any]) -> None:
if (
self.log_follower.phase == LogSectionType.TEST_CASE
and line["lvl"] == "feedback"
):
if re.search(r"^Reboot requested", line["msg"]):
self.reboot_counter += 1
if self.reboot_counter > 0:
self.raise_known_issue(
"Forced reboot detected during test phase, failing the job..."
)
# If the a6xx gpu repeatedly fails to recover over a short period of time,
# then successful recovery is unlikely so cancel the job preemptively.
def detect_a6xx_gpu_recovery_failure(self, line: dict[str, Any]) -> None:
if search_known_issue_patterns(A6XX_GPU_RECOVERY_FAILURE_MESSAGE, line["msg"]):
time_of_failure = datetime.fromisoformat(line["dt"])
self.a6xx_gpu_recovery_fail_counter += 1
if self.a6xx_gpu_first_fail_time is None:
self.a6xx_gpu_first_fail_time = time_of_failure
if self.a6xx_gpu_recovery_fail_counter == A6XX_GPU_RECOVERY_FAILURE_MAX_COUNT:
time_since_first_fail = time_of_failure - self.a6xx_gpu_first_fail_time
if time_since_first_fail <= timedelta(minutes=A6XX_GPU_RECOVERY_WATCH_PERIOD_MIN):
self.raise_known_issue(
"Repeated GPU recovery failure detected: cancelling the job"
)
else:
self.a6xx_gpu_first_fail_time = None
self.a6xx_gpu_recovery_fail_counter = 0