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Support pipeline retrying failing tasks/steps

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This commit is contained in:
allegroai 2022-09-06 20:52:50 +03:00
parent 5228b799c1
commit 447714eaa4
1 changed files with 66 additions and 17 deletions
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83
clearml/automation/controller.py
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@ -11,7 +11,7 @@ from logging import getLogger
from multiprocessing import Process, Queue
from multiprocessing.pool import ThreadPool
from threading import Thread, Event, RLock, current_thread
from time import time
from time import time, sleep
from typing import Sequence, Optional, Mapping, Callable, Any, List, Dict, Union, Tuple
from attr import attrib, attrs
@ -59,6 +59,7 @@ class PipelineController(object):
_report_plot_execution_details = dict(title='Pipeline Details', series='Execution Details')
_evaluated_return_values = {} # TID: pipeline_name
_add_to_evaluated_return_values = {} # TID: bool
_retries_left = {} # Node.name: int
valid_job_status = ["failed", "cached", "completed", "aborted", "queued", "running", "skipped", "pending"]
@ -132,6 +133,7 @@ class PipelineController(object):
auto_version_bump=True, # type: bool
abort_on_failure=False, # type: bool
add_run_number=True, # type: bool
retry_on_failure=None # type: Optional[int]
):
# type: (...) -> None
"""
@ -157,6 +159,8 @@ class PipelineController(object):
and mark the pipeline as failed.
:param add_run_number: If True (default), add the run number of the pipeline to the pipeline name.
Example, the second time we launch the pipeline "best pipeline", we rename it to "best pipeline #2"
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
"""
self._nodes = {}
self._running_nodes = []
@ -222,6 +226,7 @@ class PipelineController(object):
self._monitored_nodes = {} # type: Dict[str, dict]
self._abort_running_steps_on_failure = abort_on_failure
self._retry_on_failure = retry_on_failure
# add direct link to the pipeline page
if self._pipeline_as_sub_project and self._task:
@ -276,6 +281,7 @@ class PipelineController(object):
post_execute_callback=None, # type: Optional[Callable[[PipelineController, PipelineController.Node], None]] # noqa
cache_executed_step=False, # type: bool
base_task_factory=None, # type: Optional[Callable[[PipelineController.Node], Task]]
retry_on_failure=None # type: int
):
# type: (...) -> bool
"""
@ -394,7 +400,8 @@ class PipelineController(object):
If `clone_base_task` is False there is no cloning, hence the base_task is used.
:param base_task_factory: Optional, instead of providing a pre-existing Task,
provide a Callable function to create the Task (returns Task object)
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
:return: True if successful
"""
@ -458,6 +465,7 @@ class PipelineController(object):
monitor_artifacts=monitor_artifacts or [],
monitor_models=monitor_models or [],
)
self._retries_left[name] = retry_on_failure or self._retry_on_failure or 0
if self._task and not self._task.running_locally():
self.update_execution_plot()
@ -493,6 +501,7 @@ class PipelineController(object):
pre_execute_callback=None, # type: Optional[Callable[[PipelineController, PipelineController.Node, dict], bool]] # noqa
post_execute_callback=None, # type: Optional[Callable[[PipelineController, PipelineController.Node], None]] # noqa
cache_executed_step=False, # type: bool
retry_on_failure=None # type: Optional[int]
):
# type: (...) -> bool
"""
@ -626,6 +635,8 @@ class PipelineController(object):
Default: False, a new cloned copy of base_task is always used.
Notice: If the git repo reference does not have a specific commit ID, the Task will never be used.
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
:return: True if successful
"""
# always store callback functions (even when running remotely)
@ -718,6 +729,7 @@ class PipelineController(object):
monitor_models=monitor_models,
job_code_section=job_code_section,
)
self._retries_left[name] = retry_on_failure or self._retry_on_failure or 0
return True
@ -1975,8 +1987,15 @@ class PipelineController(object):
if not node.job:
continue
if node.job.is_stopped(aborted_nonresponsive_as_running=True):
completed_jobs.append(j)
node_failed = node.job.is_failed()
if node_failed and self._retries_left.get(node.name) and self._retries_left[node.name] > 0:
self._task.get_logger().report_text("Node '{}' failed. Retrying...".format(node.name))
node.job = None
node.executed = None
self._running_nodes.remove(j)
self._retries_left[node.name] -= 1
continue
completed_jobs.append(j)
node.executed = node.job.task_id() if not node_failed else False
if j in launched_nodes:
launched_nodes.remove(j)
@ -2526,6 +2545,7 @@ class PipelineDecorator(PipelineController):
target_project=None, # type: Optional[str]
abort_on_failure=False, # type: bool
add_run_number=True, # type: bool
retry_on_failure=None # type: Optional[int]
):
# type: (...) -> ()
"""
@ -2547,6 +2567,8 @@ class PipelineDecorator(PipelineController):
and mark the pipeline as failed.
:param add_run_number: If True (default), add the run number of the pipeline to the pipeline name.
Example, the second time we launch the pipeline "best pipeline", we rename it to "best pipeline #2"
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
"""
super(PipelineDecorator, self).__init__(
name=name,
@ -2557,6 +2579,7 @@ class PipelineDecorator(PipelineController):
target_project=target_project,
abort_on_failure=abort_on_failure,
add_run_number=add_run_number,
retry_on_failure=retry_on_failure
)
# if we are in eager execution, make sure parent class knows it
@ -2610,12 +2633,11 @@ class PipelineDecorator(PipelineController):
if not node.job:
continue
if node.job.is_stopped(aborted_nonresponsive_as_running=True):
completed_jobs.append(j)
node_failed = node.job.is_failed()
completed_jobs.append(j)
node.executed = node.job.task_id() if not node_failed else False
if j in launched_nodes:
launched_nodes.remove(j)
# check if we need to stop all running steps
if node_failed and self._abort_running_steps_on_failure and not node.continue_on_fail:
nodes_failed_stop_pipeline.append(node.name)
@ -2865,7 +2887,8 @@ class PipelineDecorator(PipelineController):
helper_functions=None, # type: Optional[Sequence[Callable]]
monitor_metrics=None, # type: Optional[List[Union[Tuple[str, str], Tuple[(str, str), (str, str)]]]]
monitor_artifacts=None, # type: Optional[List[Union[str, Tuple[str, str]]]]
monitor_models=None # type: Optional[List[Union[str, Tuple[str, str]]]]
monitor_models=None, # type: Optional[List[Union[str, Tuple[str, str]]]]
retry_on_failure=None # type: Optional[int]
):
# type: (...) -> Callable
"""
@ -2939,6 +2962,8 @@ class PipelineDecorator(PipelineController):
where the first string is the model name as it appears on the component Task,
and the second is the target model name to put on the Pipeline Task
Example: [('model_weights', 'final_model_weights'), ]
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
:return: function wrapper
"""
@ -3088,10 +3113,12 @@ class PipelineDecorator(PipelineController):
# get node and park is as launched
cls._singleton._launched_step_names.add(_node_name)
_node = cls._singleton._nodes[_node_name]
cls._retries_left[_node_name] = \
retry_on_failure or (cls._singleton._retry_on_failure if cls._singleton else 0) or 0
# The actual launch is a bit slow, we run it in the background
launch_thread = Thread(
target=cls._component_launch,
target=cls._component_launch_with_failover,
args=(_node_name, _node, kwargs_artifacts, kwargs, current_thread().ident))
def results_reference(return_name):
@ -3101,15 +3128,11 @@ class PipelineDecorator(PipelineController):
launch_thread.join()
except: # noqa
pass
# wait until job is completed
if not _node.job:
if not _node.executed:
raise ValueError("Job was not created and is also not cached/executed")
return "{}.{}".format(_node.executed, return_name)
# wait in seconds
_node.job.wait(pool_period=5. if cls._debug_execute_step_process else 20.,
aborted_nonresponsive_as_running=True)
if _node.job.is_failed() and not _node.continue_on_fail:
raise ValueError(
'Pipeline step "{}", Task ID={} failed'.format(_node.name, _node.job.task_id()))
@ -3124,11 +3147,10 @@ class PipelineDecorator(PipelineController):
launch_thread.join()
except: # noqa
pass
# wait until job is completed
_node.job.wait(pool_period=5. if cls._debug_execute_step_process else 20.)
if _node.job.is_failed():
if (_node.job.is_failed() and not _node.continue_on_fail) or _node.job.is_aborted():
raise ValueError(
'Pipeline step "{}", Task ID={} failed'.format(_node.name, _node.job.task_id()))
'Pipeline step "{}", Task ID={} failed'.format(_node.name, _node.job.task_id())
)
_node.executed = _node.job.task_id()
@ -3174,7 +3196,8 @@ class PipelineDecorator(PipelineController):
multi_instance_support=False, # type: bool
add_run_number=True, # type: bool
args_map=None, # type: dict[str, List[str]]
start_controller_locally=False # type: bool
start_controller_locally=False, # type: bool
retry_on_failure=None # type: Optional[int]
):
# type: (...) -> Callable
"""
@ -3221,9 +3244,14 @@ class PipelineDecorator(PipelineController):
- paramB: sectionB/paramB
- paramC: sectionB/paramC
- paramD: Args/paramD
:param relaunch_on_instance_failure: (Deprecated) If True, check if the machine a pipeline step ran on
was terminated. In case it was, the step will be relaunched. As of now, only AWS instances are supported.
Default: False
:param start_controller_locally: If True, start the controller on the local machine. The steps will run
remotely if `PipelineDecorator.run_locally` or `PipelineDecorator.debug_pipeline` are not called.
Default: False
:param retry_on_failure: In case of node failure, retry the node the number of times
indicated by this parameter.
"""
def decorator_wrap(func):
@ -3260,6 +3288,7 @@ class PipelineDecorator(PipelineController):
target_project=target_project,
abort_on_failure=abort_on_failure,
add_run_number=add_run_number,
retry_on_failure=retry_on_failure
)
ret_val = func(**pipeline_kwargs)
LazyEvalWrapper.trigger_all_remote_references()
@ -3301,6 +3330,7 @@ class PipelineDecorator(PipelineController):
target_project=target_project,
abort_on_failure=abort_on_failure,
add_run_number=add_run_number,
retry_on_failure=retry_on_failure
)
a_pipeline._args_map = args_map or {}
@ -3325,7 +3355,6 @@ class PipelineDecorator(PipelineController):
a_pipeline._task._set_runtime_properties(
dict(multi_pipeline_counter=str(cls._multi_pipeline_call_counter)))
# serialize / deserialize state only if we are running locally
a_pipeline._start(wait=False)
# sync arguments back (post deserialization and casting back)
@ -3445,6 +3474,26 @@ class PipelineDecorator(PipelineController):
"""
return cls._wait_for_multi_pipelines()
@classmethod
def _component_launch_with_failover(cls, node_name, node, kwargs_artifacts, kwargs, tid):
cls._component_launch(node_name, node, kwargs_artifacts, kwargs, tid)
while True:
if node.job:
node.job.wait(pool_period=5. if cls._debug_execute_step_process else 20.,
aborted_nonresponsive_as_running=True)
else:
sleep(2)
continue
if node.job.is_failed() and cls._retries_left.get(node_name) and cls._retries_left[node_name] > 0:
if cls._singleton and cls._singleton._task:
cls._singleton._task.get_logger().report_text("Node '{}' failed. Retrying...".format(node_name))
node.job = None
node.executed = None
cls._component_launch(node_name, node, kwargs_artifacts, kwargs, tid)
cls._retries_left[node_name] -= 1
else:
break
@classmethod
def _component_launch(cls, node_name, node, kwargs_artifacts, kwargs, tid):
_node_name = node_name