import atexit
import os
import signal
import sys
import threading
import time
from argparse import ArgumentParser
from collections import OrderedDict, Callable
from typing import Optional
import psutil
import six
from .binding.joblib_bind import PatchedJoblib
from .backend_api.services import tasks, projects
from .backend_api.session.session import Session
from .backend_interface.model import Model as BackendModel
from .backend_interface.task import Task as _Task
from .backend_interface.task.args import _Arguments
from .backend_interface.task.development.worker import DevWorker
from .backend_interface.task.repo import ScriptInfo
from .backend_interface.util import get_single_result, exact_match_regex, make_message
from .config import config, PROC_MASTER_ID_ENV_VAR, DEV_TASK_NO_REUSE
from .config import running_remotely, get_remote_task_id
from .config.cache import SessionCache
from .debugging.log import LoggerRoot
from .errors import UsageError
from .logger import Logger
from .model import InputModel, OutputModel, ARCHIVED_TAG
from .task_parameters import TaskParameters
from .binding.artifacts import Artifacts, Artifact
from .binding.environ_bind import EnvironmentBind, PatchOsFork
from .binding.absl_bind import PatchAbsl
from .utilities.args import argparser_parseargs_called, get_argparser_last_args, \
argparser_update_currenttask
from .binding.frameworks.pytorch_bind import PatchPyTorchModelIO
from .binding.frameworks.tensorflow_bind import TensorflowBinding
from .binding.frameworks.xgboost_bind import PatchXGBoostModelIO
from .binding.matplotlib_bind import PatchedMatplotlib
from .utilities.resource_monitor import ResourceMonitor
from .utilities.seed import make_deterministic
from .utilities.dicts import ReadOnlyDict
class Task(_Task):
"""
Task (experiment) object represents the current running experiments and connects all the different parts into \
a fully reproducible experiment
Common usage is calling :func:`Task.init` to initialize the main task.
The main task is development / remote execution mode-aware, and supports connecting various SDK objects
such as Models etc. In development mode, the main task supports task reuse (see :func:`Task.init` for more
information in development mode features).
Any subsequent call to :func:`Task.init` will return the already-initialized main task
and will not create a new main task.
Sub-tasks, meaning tasks which are not the main task and are not development / remote execution mode aware, can be
created using :func:`Task.create`. These tasks do no support task reuse and any call
to :func:`Task.create` will always create a new task.
You can also query existing tasks in the system by calling :func:`Task.get_task`.
**Usage:** :func:`Task.init` or :func:`Task.get_task`
"""
TaskTypes = _Task.TaskTypes
NotSet = object()
__create_protection = object()
__main_task = None
__exit_hook = None
__forked_proc_main_pid = None
__task_id_reuse_time_window_in_hours = float(config.get('development.task_reuse_time_window_in_hours', 24.0))
__store_diff_on_train = config.get('development.store_uncommitted_code_diff_on_train', False)
__detect_repo_async = config.get('development.vcs_repo_detect_async', False)
class _ConnectedParametersType(object):
argparse = "argument_parser"
dictionary = "dictionary"
task_parameters = "task_parameters"
@classmethod
def _options(cls):
return {
var for var, val in vars(cls).items()
if isinstance(val, six.string_types)
}
def __init__(self, private=None, **kwargs):
"""
Do not construct Task manually!
**Please use Task.init() or Task.get_task(id=, project=, name=)**
"""
if private is not Task.__create_protection:
raise UsageError(
'Task object cannot be instantiated externally, use Task.current_task() or Task.get_task(...)')
self._repo_detect_lock = threading.RLock()
super(Task, self).__init__(**kwargs)
self._arguments = _Arguments(self)
self._logger = None
self._last_input_model_id = None
self._connected_output_model = None
self._dev_worker = None
self._connected_parameter_type = None
self._detect_repo_async_thread = None
self._resource_monitor = None
self._artifacts_manager = Artifacts(self)
# register atexit, so that we mark the task as stopped
self._at_exit_called = False
@classmethod
def current_task(cls):
# type: () -> Task
"""
Return the Current Task object for the main execution task (task context).
:return: Task() object or None
"""
return cls.__main_task
@classmethod
def init(
cls,
project_name=None,
task_name=None,
task_type=TaskTypes.training,
reuse_last_task_id=True,
output_uri=None,
auto_connect_arg_parser=True,
auto_connect_frameworks=True,
auto_resource_monitoring=True,
):
"""
Return the Task object for the main execution task (task context).
:param project_name: project to create the task in (if project doesn't exist, it will be created)
:param task_name: task name to be created (in development mode, not when running remotely)
:param task_type: task type to be created, Default: TaskTypes.training
Options are: 'testing', 'training' or 'train', 'inference'
:param reuse_last_task_id: start with the previously used task id (stored in the data cache folder).
if False every time we call the function we create a new task with the same name
Notice! The reused task will be reset. (when running remotely, the usual behaviour applies)
If reuse_last_task_id is of type string, it will assume this is the task_id to reuse!
Note: A closed or published task will not be reused, and a new task will be created.
:param output_uri: Default location for output models (currently support folder/S3/GS/Azure ).
notice: sub-folders (task_id) is created in the destination folder for all outputs.
Usage example: /mnt/share/folder, s3://bucket/folder , gs://bucket-name/folder,
azure://company.blob.core.windows.net/folder/
Note: When using cloud storage, make sure you install the accompany packages.
For example: trains[s3], trains[gs], trains[azure]
:param auto_connect_arg_parser: Automatically grab the ArgParser and connect it with the task.
if set to false, you can manually connect the ArgParser with task.connect(parser)
:param auto_connect_frameworks: If true automatically patch MatplotLib, Keras callbacks, and TensorBoard/X to
serialize plots, graphs and model location to trains backend (in addition to original output destination)
:param auto_resource_monitoring: If true, machine vitals will be sent along side the task scalars,
Resources graphs will appear under the title ':resource monitor:' in the scalars tab.
:return: Task() object
"""
def verify_defaults_match():
validate = [
('project name', project_name, cls.__main_task.get_project_name()),
('task name', task_name, cls.__main_task.name),
('task type', str(task_type), str(cls.__main_task.task_type)),
]
for field, default, current in validate:
if default is not None and default != current:
raise UsageError(
"Current task already created "
"and requested {field} '{default}' does not match current {field} '{current}'".format(
field=field,
default=default,
current=current,
)
)
if cls.__main_task is not None:
# if this is a subprocess, regardless of what the init was called for,
# we have to fix the main task hooks and stdout bindings
if cls.__forked_proc_main_pid != os.getpid() and PROC_MASTER_ID_ENV_VAR.get() != os.getpid():
if task_type is None:
task_type = cls.__main_task.task_type
# make sure we only do it once per process
cls.__forked_proc_main_pid = os.getpid()
# make sure we do not wait for the repo detect thread
cls.__main_task._detect_repo_async_thread = None
# remove the logger from the previous process
logger = cls.__main_task.get_logger()
logger.set_flush_period(None)
# create a new logger (to catch stdout/err)
cls.__main_task._logger = None
cls.__main_task._reporter = None
cls.__main_task.get_logger()
# unregister signal hooks, they cause subprocess to hang
cls.__main_task.__register_at_exit(cls.__main_task._at_exit)
cls.__main_task.__register_at_exit(None, only_remove_signal_and_exception_hooks=True)
if not running_remotely():
verify_defaults_match()
return cls.__main_task
# check that we are not a child process, in that case do nothing.
# we should not get here unless this is Windows platform, all others support fork
if PROC_MASTER_ID_ENV_VAR.get() and PROC_MASTER_ID_ENV_VAR.get() != os.getpid():
class _TaskStub(object):
def __call__(self, *args, **kwargs):
return self
def __getattr__(self, attr):
return self
def __setattr__(self, attr, val):
pass
return _TaskStub()
# set us as master process
PROC_MASTER_ID_ENV_VAR.set(os.getpid())
if task_type is None:
# Backwards compatibility: if called from Task.current_task and task_type
# was not specified, keep legacy default value of TaskTypes.training
task_type = cls.TaskTypes.training
elif isinstance(task_type, six.string_types):
task_type_lookup = {'testing': cls.TaskTypes.testing, 'inference': cls.TaskTypes.testing,
'train': cls.TaskTypes.training, 'training': cls.TaskTypes.training,}
if task_type not in task_type_lookup:
raise ValueError("Task type '{}' not supported, options are: {}".format(task_type,
list(task_type_lookup.keys())))
task_type = task_type_lookup[task_type]
try:
if not running_remotely():
task = cls._create_dev_task(
project_name,
task_name,
task_type,
reuse_last_task_id,
)
if output_uri:
task.output_uri = output_uri
else:
task = cls(
private=cls.__create_protection,
task_id=get_remote_task_id(),
log_to_backend=False,
)
except Exception:
raise
else:
Task.__main_task = task
# register the main task for at exit hooks (there should only be one)
task.__register_at_exit(task._at_exit)
# patch OS forking
PatchOsFork.patch_fork()
if auto_connect_frameworks:
PatchedJoblib.update_current_task(task)
PatchedMatplotlib.update_current_task(Task.__main_task)
PatchAbsl.update_current_task(Task.__main_task)
TensorflowBinding.update_current_task(task)
PatchPyTorchModelIO.update_current_task(task)
PatchXGBoostModelIO.update_current_task(task)
if auto_resource_monitoring:
task._resource_monitor = ResourceMonitor(task)
task._resource_monitor.start()
# make sure all random generators are initialized with new seed
make_deterministic(task.get_random_seed())
if auto_connect_arg_parser:
EnvironmentBind.update_current_task(Task.__main_task)
# Patch ArgParser to be aware of the current task
argparser_update_currenttask(Task.__main_task)
# Check if parse args already called. If so, sync task parameters with parser
if argparser_parseargs_called():
parser, parsed_args = get_argparser_last_args()
task._connect_argparse(parser=parser, parsed_args=parsed_args)
# Make sure we start the logger, it will patch the main logging object and pipe all output
# if we are running locally and using development mode worker, we will pipe all stdout to logger.
# The logger will automatically take care of all patching (we just need to make sure to initialize it)
logger = task.get_logger()
# show the debug metrics page in the log, it is very convenient
logger.report_text(
'TRAINS results page: {}/projects/{}/experiments/{}/output/log'.format(
task._get_app_server(),
task.project if task.project is not None else '*',
task.id,
),
)
# Make sure we start the dev worker if required, otherwise it will only be started when we write
# something to the log.
task._dev_mode_task_start()
return task
@classmethod
def create(
cls,
task_name=None,
project_name=None,
task_type=TaskTypes.training,
):
"""
Create a new Task object, regardless of the main execution task (Task.init).
Notice: This function will always create a new task, whether running in development or remote execution mode.
:param task_name: task name to be created
:param project_name: Project to create the task in.
If project is None, and the main execution task is initialized (Task.init), its project will be used.
If project is provided but doesn't exist, it will be created.
:param task_type: Task type to be created. (default: "training")
Optional Task types are: "training" / "testing" / "dataset_import" / "annotation" / "annotation_manual"
:return: Task() object
"""
if not project_name:
if not cls.__main_task:
raise ValueError("Please provide project_name, no global task context found "
"(Task.current_task hasn't been called)")
project_name = cls.__main_task.get_project_name()
try:
task = cls(
private=cls.__create_protection,
project_name=project_name,
task_name=task_name,
task_type=task_type,
log_to_backend=False,
force_create=True,
)
except Exception:
raise
return task
@classmethod
def _reset_current_task_obj(cls):
if not cls.__main_task:
return
task = cls.__main_task
cls.__main_task = None
if task._dev_worker:
task._dev_worker.unregister()
task._dev_worker = None
@classmethod
def _create_dev_task(cls, default_project_name, default_task_name, default_task_type, reuse_last_task_id):
if not default_project_name or not default_task_name:
# get project name and task name from repository name and entry_point
result, _ = ScriptInfo.get(create_requirements=False, check_uncommitted=False)
if not default_project_name:
# noinspection PyBroadException
try:
parts = result.script['repository'].split('/')
default_project_name = (parts[-1] or parts[-2]).replace('.git', '') or 'Untitled'
except Exception:
default_project_name = 'Untitled'
if not default_task_name:
# noinspection PyBroadException
try:
default_task_name = os.path.splitext(os.path.basename(result.script['entry_point']))[0]
except Exception:
pass
# if we force no task reuse from os environment
if DEV_TASK_NO_REUSE.get() or not reuse_last_task_id:
default_task = None
else:
# if we have a previous session to use, get the task id from it
default_task = cls.__get_last_used_task_id(
default_project_name,
default_task_name,
default_task_type.value,
)
closed_old_task = False
default_task_id = None
in_dev_mode = not running_remotely()
if in_dev_mode:
if isinstance(reuse_last_task_id, str) and reuse_last_task_id:
default_task_id = reuse_last_task_id
elif not reuse_last_task_id or not cls.__task_is_relevant(default_task):
default_task_id = None
else:
default_task_id = default_task.get('id') if default_task else None
if default_task_id:
try:
task = cls(
private=cls.__create_protection,
task_id=default_task_id,
log_to_backend=True,
)
task_tags = task.data.system_tags if hasattr(task.data, 'system_tags') else task.data.tags
if ((str(task.status) in (str(tasks.TaskStatusEnum.published), str(tasks.TaskStatusEnum.closed)))
or task.output_model_id or (ARCHIVED_TAG in task_tags)
or (cls._development_tag not in task_tags)):
# If the task is published or closed, we shouldn't reset it so we can't use it in dev mode
# If the task is archived, or already has an output model,
# we shouldn't use it in development mode either
default_task_id = None
task = None
else:
# reset the task, so we can update it
task.reset(set_started_on_success=False, force=False)
# set development tags
task.set_system_tags([cls._development_tag])
# clear task parameters, they are not cleared by the Task reset
task.set_parameters({}, __update=False)
# clear the comment, it is not cleared on reset
task.set_comment(make_message('Auto-generated at %(time)s by %(user)s@%(host)s'))
# clear the input model (and task model design/labels)
task.set_input_model(model_id='', update_task_design=False, update_task_labels=False)
task.set_model_config(config_text='')
task.set_model_label_enumeration({})
task.set_artifacts([])
task._set_storage_uri(None)
except (Exception, ValueError):
# we failed reusing task, create a new one
default_task_id = None
# create a new task
if not default_task_id:
task = cls(
private=cls.__create_protection,
project_name=default_project_name,
task_name=default_task_name,
task_type=default_task_type,
log_to_backend=True,
)
if in_dev_mode:
# update this session, for later use
cls.__update_last_used_task_id(default_project_name, default_task_name, default_task_type.value, task.id)
# mark the task as started
task.started()
# force update of base logger to this current task (this is the main logger task)
task._setup_log(replace_existing=True)
logger = task.get_logger()
if closed_old_task:
logger.report_text('TRAINS Task: Closing old development task id={}'.format(default_task.get('id')))
# print warning, reusing/creating a task
if default_task_id:
logger.report_text('TRAINS Task: overwriting (reusing) task id=%s' % task.id)
else:
logger.report_text('TRAINS Task: created new task id=%s' % task.id)
# update current repository and put warning into logs
if in_dev_mode and cls.__detect_repo_async:
task._detect_repo_async_thread = threading.Thread(target=task._update_repository)
task._detect_repo_async_thread.daemon = True
task._detect_repo_async_thread.start()
else:
task._update_repository()
# make sure everything is in sync
task.reload()
# make sure we see something in the UI
thread = threading.Thread(target=LoggerRoot.flush)
thread.daemon = True
thread.start()
return task
@classmethod
def get_task(cls, task_id=None, project_name=None, task_name=None):
"""
Returns Task object based on either, task_id (system uuid) or task name
:param task_id: unique task id string (if exists other parameters are ignored)
:param project_name: project name (str) the task belongs to
:param task_name: task name (str) in within the selected project
:return: Task() object
"""
return cls.__get_task(task_id=task_id, project_name=project_name, task_name=task_name)
@property
def output_uri(self):
return self.storage_uri
@output_uri.setter
def output_uri(self, value):
# check if we have the correct packages / configuration
if value and value != self.storage_uri:
from .storage.helper import StorageHelper
helper = StorageHelper.get(value)
if not helper:
raise ValueError("Could not get access credentials for '{}' "
", check configuration file ~/trains.conf".format(value))
helper.check_write_permissions(value)
self.storage_uri = value
@property
def artifacts(self):
"""
read-only dictionary of Task artifacts (name, artifact)
:return: dict
"""
if not Session.check_min_api_version('2.3'):
return ReadOnlyDict()
if not self.data.execution or not self.data.execution.artifacts:
return ReadOnlyDict()
return ReadOnlyDict([(a.key, Artifact(a)) for a in self.data.execution.artifacts])
def set_comment(self, comment):
"""
Set a comment text to the task.
In remote, this is a no-op.
:param comment: The comment of the task
:type comment: str
"""
if not running_remotely() or not self.is_main_task():
self._edit(comment=comment)
self.reload()
def add_tags(self, tags):
"""
Add tags to this task. Old tags are not deleted
In remote, this is a no-op.
:param tags: An iterable or space separated string of new tags (string) to add.
:type tags: str or iterable of str
"""
if not running_remotely() or not self.is_main_task():
if isinstance(tags, six.string_types):
tags = tags.split(" ")
self.data.tags.extend(tags)
self._edit(tags=list(set(self.data.tags)))
def connect(self, mutable):
"""
Connect an object to a task (see introduction to Task connect design)
:param mutable: can be any object Task supports integrating with:
- argparse : for argument passing
- dict : for argument passing
- TaskParameters : for argument passing
- model : for initial model warmup or model update/snapshot uploads
:return: connect_task() return value if supported
:raise: raise exception on unsupported objects
"""
dispatch = OrderedDict((
(OutputModel, self._connect_output_model),
(InputModel, self._connect_input_model),
(ArgumentParser, self._connect_argparse),
(dict, self._connect_dictionary),
(TaskParameters, self._connect_task_parameters),
))
for mutable_type, method in dispatch.items():
if isinstance(mutable, mutable_type):
return method(mutable)
raise Exception('Unsupported mutable type %s: no connect function found' % type(mutable).__name__)
def get_logger(self):
# type: () -> Logger
"""
get a logger object for reporting, for this task context.
All reports (metrics, text etc.) related to this task are accessible in the web UI
:return: Logger object
"""
return self._get_logger()
def mark_started(self):
"""
Manually Mark the task as started (will happen automatically)
"""
# UI won't let us see metrics if we're not started
self.started()
self.reload()
def mark_stopped(self):
"""
Manually Mark the task as stopped (also used in self._at_exit)
"""
# flush any outstanding logs
self.flush(wait_for_uploads=True)
# mark task as stopped
self.stopped()
def flush(self, wait_for_uploads=False):
"""
flush any outstanding reports or console logs
:param wait_for_uploads: if True the flush will exit only after all outstanding uploads are completed
"""
# make sure model upload is done
if BackendModel.get_num_results() > 0 and wait_for_uploads:
BackendModel.wait_for_results()
# flush any outstanding logs
if self._logger:
# noinspection PyProtectedMember
self._logger._flush_stdout_handler()
if self._reporter:
self.reporter.flush()
LoggerRoot.flush()
return True
def reset(self, set_started_on_success=False, force=False):
"""
Reset the task. Task will be reloaded following a successful reset.
Notice: when running remotely the task will not be reset (as it will clear all logs and metrics)
:param set_started_on_success: automatically set started if reset was successful
:param force: force task reset even if running remotely
"""
if not running_remotely() or not self.is_main_task() or force:
super(Task, self).reset(set_started_on_success=set_started_on_success)
def close(self):
"""
Close the current Task. Enables to manually shutdown the task.
Should only be called if you are absolutely sure there is no need for the Task.
"""
self._at_exit()
self._at_exit_called = False
# unregister atexit callbacks and signal hooks, if we are the main task
if self.is_main_task():
self.__register_at_exit(None)
def register_artifact(self, name, artifact, metadata=None):
"""
Add artifact for the current Task, used mostly for Data Audition.
Currently supported artifacts object types: pandas.DataFrame
:param str name: name of the artifacts. Notice! it will override previous artifacts if name already exists.
:param pandas.DataFrame artifact: artifact object, supported artifacts object types: pandas.DataFrame
:param dict metadata: dictionary of key value to store with the artifact (visible in the UI)
"""
self._artifacts_manager.register_artifact(name=name, artifact=artifact, metadata=metadata)
def unregister_artifact(self, name):
"""
Remove artifact from the watch list. Notice this will not remove the artifacts from the Task.
It will only stop monitoring the artifact,
the last snapshot of the artifact will be taken immediately in the background.
"""
self._artifacts_manager.unregister_artifact(name=name)
def get_registered_artifacts(self):
"""
dictionary of Task registered artifacts (name, artifact object)
Notice these objects can be modified, changes will be uploaded automatically
:return: dict
"""
return self._artifacts_manager.registered_artifacts
def upload_artifact(self, name, artifact_object, metadata=None, delete_after_upload=False):
"""
Add static artifact to Task. Artifact file/object will be uploaded in the background
Raise ValueError if artifact_object is not supported
:param str name: Artifact name. Notice! it will override previous artifact if name already exists
:param object artifact_object: Artifact object to upload. Currently supports:
- string / pathlib2.Path are treated as path to artifact file to upload
If wildcard or a folder is passed, zip file containing the local files will be created and uploaded
- dict will be stored as .json file and uploaded
- pandas.DataFrame will be stored as .csv.gz (compressed CSV file) and uploaded
- numpy.ndarray will be stored as .npz and uploaded
- PIL.Image will be stored to .png file and uploaded
:param dict metadata: Simple key/value dictionary to store on the artifact
:param bool delete_after_upload: If True local artifact will be deleted
(only applies if artifact_object is a local file)
:return: True if artifact will be uploaded
"""
return self._artifacts_manager.upload_artifact(name=name, artifact_object=artifact_object,
metadata=metadata, delete_after_upload=delete_after_upload)
def is_current_task(self):
"""
Check if this task is the main task (returned by Task.init())
NOTE: This call is deprecated. Please use Task.is_main_task()
If Task.init() was never called, this method will *not* create
it, making this test cheaper than Task.init() == task
:return: True if this task is the current task
"""
return self.is_main_task()
def is_main_task(self):
"""
Check if this task is the main task (returned by Task.init())
If Task.init() was never called, this method will *not* create
it, making this test cheaper than Task.init() == task
:return: True if this task is the current task
"""
return self is self.__main_task
def set_model_config(self, config_text=None, config_dict=None):
"""
Set Task model configuration text/dict (before creating an output model)
When an output model is created it will inherit these properties
:param config_text: model configuration (unconstrained text string). usually the content of a configuration file.
If `config_text` is not None, `config_dict` must not be provided.
:param config_dict: model configuration parameters dictionary.
If `config_dict` is not None, `config_text` must not be provided.
"""
design = OutputModel._resolve_config(config_text=config_text, config_dict=config_dict)
super(Task, self)._set_model_design(design=design)
def get_model_config_text(self):
"""
Get Task model configuration text (before creating an output model)
When an output model is created it will inherit these properties
:return: model config_text (unconstrained text string). usually the content of a configuration file.
If `config_text` is not None, `config_dict` must not be provided.
"""
return super(Task, self).get_model_design()
def get_model_config_dict(self):
"""
Get Task model configuration dictionary (before creating an output model)
When an output model is created it will inherit these properties
:return: model config_text (unconstrained text string). usually the content of a configuration file.
If `config_text` is not None, `config_dict` must not be provided.
"""
config_text = self.get_model_config_text()
return OutputModel._text_to_config_dict(config_text)
def set_model_label_enumeration(self, enumeration=None):
"""
Set Task output label enumeration (before creating an output model)
When an output model is created it will inherit these properties
:param enumeration: dictionary of string to integer, enumerating the model output to labels
example: {'background': 0 , 'person': 1}
"""
super(Task, self).set_model_label_enumeration(enumeration=enumeration)
def get_last_iteration(self):
"""
Return the last reported iteration (i.e. the maximum iteration the task reported a metric for)
Notice, this is not a cached call, it will ask the backend for the answer (no local caching)
:return: last reported iteration number (integer)
"""
self.reload()
return self.data.last_iteration
def set_last_iteration(self, last_iteration):
"""
Forcefully set the last reported iteration
(i.e. the maximum iteration the task reported a metric for)
:param last_iteration: last reported iteration number
:type last_iteration: integer
"""
self.data.last_iteration = int(last_iteration)
self._edit(last_iteration=self.data.last_iteration)
def get_last_scalar_metrics(self):
"""
Extract the last scalar metrics, ordered by title & series in a nested dictionary
:return: dict. Example: {'title': {'series': {'last': 0.5, 'min': 0.1, 'max': 0.9}}}
"""
self.reload()
metrics = self.data.last_metrics
scalar_metrics = dict()
for i in metrics.values():
for j in i.values():
scalar_metrics.setdefault(j['metric'], {}).setdefault(
j['variant'], {'last': j['value'], 'min': j['min_value'], 'max': j['max_value']})
return scalar_metrics
@classmethod
def set_credentials(cls, host=None, key=None, secret=None):
"""
Set new default TRAINS-server host and credentials
These configurations will be overridden by wither OS environment variables or trains.conf configuration file
Notice! credentials needs to be set *prior* to Task initialization
:param host: host url, example: host='http://localhost:8008'
:type host: str
:param key: user key/secret pair, example: key='thisisakey123'
:type key: str
:param secret: user key/secret pair, example: secret='thisisseceret123'
:type secret: str
"""
if host:
Session.default_host = host
if key:
Session.default_key = key
if secret:
Session.default_secret = secret
def _get_logger(self, flush_period=NotSet):
# type: (Optional[float]) -> Logger
"""
get a logger object for reporting based on the task
:param flush_period: The period of the logger flush.
If None of any other False value, will not flush periodically.
If a logger was created before, this will be the new period and
the old one will be discarded.
:return: Logger object
"""
pass
if not self._logger:
# force update of base logger to this current task (this is the main logger task)
self._setup_log(replace_existing=self.is_main_task())
# Get a logger object
self._logger = Logger(private_task=self)
# make sure we set our reported to async mode
# we make sure we flush it in self._at_exit
self.reporter.async_enable = True
# if we just created the logger, set default flush period
if not flush_period or flush_period is self.NotSet:
flush_period = DevWorker.report_period
if isinstance(flush_period, (int, float)):
flush_period = int(abs(flush_period))
if flush_period is None or isinstance(flush_period, int):
self._logger.set_flush_period(flush_period)
return self._logger
def _connect_output_model(self, model):
assert isinstance(model, OutputModel)
model.connect(self)
def _save_output_model(self, model):
"""
Save a reference to the connected output model.
:param model: The connected output model
"""
self._connected_output_model = model
def _reconnect_output_model(self):
"""
If there is a saved connected output model, connect it again.
This is needed if the input model is connected after the output model
is connected, an then we will have to get the model design from the
input model by reconnecting.
"""
if self._connected_output_model:
self.connect(self._connected_output_model)
def _connect_input_model(self, model):
assert isinstance(model, InputModel)
# we only allow for an input model to be connected once
# at least until we support multiple input models
# notice that we do not check the task's input model because we allow task reuse and overwrite
# add into comment that we are using this model
comment = self.comment or ''
if not comment.endswith('\n'):
comment += '\n'
comment += 'Using model id: {}'.format(model.id)
self.set_comment(comment)
if self._last_input_model_id and self._last_input_model_id != model.id:
self.log.info('Task connect, second input model is not supported, adding into comment section')
return
self._last_input_model_id = model.id
model.connect(self)
def _try_set_connected_parameter_type(self, option):
# """ Raise an error if current value is not None and not equal to the provided option value """
# value = self._connected_parameter_type
# if not value or value == option:
# self._connected_parameter_type = option
# return option
#
# def title(option):
# return " ".join(map(str.capitalize, option.split("_")))
#
# raise ValueError(
# "Task already connected to {}. "
# "Task can be connected to only one the following argument options: {}".format(
# title(value),
# ' / '.join(map(title, self._ConnectedParametersType._options())))
# )
# added support for multiple type connections through _Arguments
return option
def _connect_argparse(self, parser, args=None, namespace=None, parsed_args=None):
# do not allow argparser to connect to jupyter notebook
# noinspection PyBroadException
try:
if 'IPython' in sys.modules:
from IPython import get_ipython
ip = get_ipython()
if ip is not None and 'IPKernelApp' in ip.config:
return
except Exception:
pass
self._try_set_connected_parameter_type(self._ConnectedParametersType.argparse)
if self.is_main_task():
argparser_update_currenttask(self)
if (parser is None or parsed_args is None) and argparser_parseargs_called():
_parser, _parsed_args = get_argparser_last_args()
if parser is None:
parser = _parser
if parsed_args is None and parser == _parser:
parsed_args = _parsed_args
if running_remotely() and self.is_main_task():
# This hack prevents Argparse from crashing when running remotely with different set of parameters
sys.argv = sys.argv[:1]
self._arguments.copy_to_parser(parser, parsed_args)
else:
self._arguments.copy_defaults_from_argparse(parser, args=args, namespace=namespace, parsed_args=parsed_args)
def _connect_dictionary(self, dictionary):
self._try_set_connected_parameter_type(self._ConnectedParametersType.dictionary)
if running_remotely() and self.is_main_task():
dictionary = self._arguments.copy_to_dict(dictionary)
else:
dictionary = self._arguments.copy_from_dict(dictionary)
return dictionary
def _connect_task_parameters(self, attr_class):
self._try_set_connected_parameter_type(self._ConnectedParametersType.task_parameters)
if running_remotely() and self.is_main_task():
attr_class.update_from_dict(self.get_parameters())
else:
self.set_parameters(attr_class.to_dict())
def _validate(self, check_output_dest_credentials=False):
if running_remotely():
super(Task, self)._validate(check_output_dest_credentials=False)
def _output_model_updated(self):
""" Called when a connected output model is updated """
if running_remotely() or not self.is_main_task():
return
# Make sure we know we've started, just in case we didn't so far
self._dev_mode_task_start(model_updated=True)
# Store uncommitted code changes
self._store_uncommitted_code_changes()
def _store_uncommitted_code_changes(self):
if running_remotely() or not self.is_main_task():
return
if not self.__store_diff_on_train:
# Feature turned off
return
return
def _dev_mode_task_start(self, model_updated=False):
""" Called when we suspect the task has started running """
self._dev_mode_setup_worker(model_updated=model_updated)
def _dev_mode_stop_task(self, stop_reason):
# make sure we do not get called (by a daemon thread) after at_exit
if self._at_exit_called:
return
self.log.warning(
"### TASK STOPPED - USER ABORTED - {} ###".format(
stop_reason.upper().replace('_', ' ')
)
)
self.flush(wait_for_uploads=True)
self.stopped()
if self._dev_worker:
self._dev_worker.unregister()
# NOTICE! This will end the entire execution tree!
if self.__exit_hook:
self.__exit_hook.remote_user_aborted = True
self._kill_all_child_processes(send_kill=False)
time.sleep(2.0)
self._kill_all_child_processes(send_kill=True)
# noinspection PyProtectedMember
os._exit(1)
@staticmethod
def _kill_all_child_processes(send_kill=False):
# get current process if pid not provided
include_parent = True
pid = os.getpid()
try:
parent = psutil.Process(pid)
except psutil.Error:
# could not find parent process id
return
for child in parent.children(recursive=True):
if send_kill:
child.kill()
else:
child.terminate()
# kill ourselves
if send_kill:
parent.kill()
else:
parent.terminate()
def _dev_mode_setup_worker(self, model_updated=False):
if running_remotely() or not self.is_main_task():
return
if self._dev_worker:
return self._dev_worker
self._dev_worker = DevWorker()
self._dev_worker.register(self)
logger = self.get_logger()
flush_period = logger.get_flush_period()
if not flush_period or flush_period > self._dev_worker.report_period:
logger.set_flush_period(self._dev_worker.report_period)
def _wait_for_repo_detection(self, timeout=None):
# wait for detection repo sync
if self._detect_repo_async_thread:
with self._repo_detect_lock:
if self._detect_repo_async_thread:
try:
if self._detect_repo_async_thread.is_alive():
self.log.info('Waiting for repository detection and full package requirement analysis')
self._detect_repo_async_thread.join(timeout=timeout)
# because join has no return value
if self._detect_repo_async_thread.is_alive():
self.log.info('Repository and package analysis timed out ({} sec), '
'giving up'.format(timeout))
else:
self.log.info('Finished repository detection and package analysis')
self._detect_repo_async_thread = None
except Exception:
pass
def _summary_artifacts(self):
# signal artifacts upload, and stop daemon
self._artifacts_manager.stop(wait=True)
# print artifacts summary
self.get_logger().report_text(self._artifacts_manager.summary)
def _at_exit(self):
"""
Will happen automatically once we exit code, i.e. atexit
:return:
"""
# protect sub-process at_exit
if self._at_exit_called:
return
is_sub_process = PROC_MASTER_ID_ENV_VAR.get() and PROC_MASTER_ID_ENV_VAR.get() != os.getpid()
# noinspection PyBroadException
try:
# from here do not get into watch dog
self._at_exit_called = True
wait_for_uploads = True
# first thing mark task as stopped, so we will not end up with "running" on lost tasks
# if we are running remotely, the daemon will take care of it
task_status = None
if not running_remotely() and self.is_main_task():
# check if we crashed, ot the signal is not interrupt (manual break)
task_status = ('stopped', )
if self.__exit_hook:
if (self.__exit_hook.exception and not isinstance(self.__exit_hook.exception, KeyboardInterrupt)) \
or (not self.__exit_hook.remote_user_aborted and self.__exit_hook.signal not in (None, 2)):
task_status = ('failed', 'Exception')
wait_for_uploads = False
else:
wait_for_uploads = (self.__exit_hook.remote_user_aborted or self.__exit_hook.signal is None)
if not self.__exit_hook.remote_user_aborted and self.__exit_hook.signal is None and \
not self.__exit_hook.exception:
task_status = ('completed', )
else:
task_status = ('stopped', )
# wait for repository detection (if we didn't crash)
if not is_sub_process and wait_for_uploads and self._logger:
# we should print summary here
self._summary_artifacts()
# make sure that if we crashed the thread we are not waiting forever
self._wait_for_repo_detection(timeout=10.)
# wait for uploads
print_done_waiting = False
if wait_for_uploads and (BackendModel.get_num_results() > 0 or
(self._reporter and self.reporter.get_num_results() > 0)):
self.log.info('Waiting to finish uploads')
print_done_waiting = True
# from here, do not send log in background thread
if wait_for_uploads:
self.flush(wait_for_uploads=True)
# wait until the reporter flush everything
if self._reporter:
self.reporter.stop()
if print_done_waiting:
self.log.info('Finished uploading')
elif self._logger:
self._logger._flush_stdout_handler()
if not is_sub_process:
# from here, do not check worker status
if self._dev_worker:
self._dev_worker.unregister()
# change task status
if not task_status:
pass
elif task_status[0] == 'failed':
self.mark_failed(status_reason=task_status[1])
elif task_status[0] == 'completed':
self.completed()
elif task_status[0] == 'stopped':
self.stopped()
# stop resource monitoring
if self._resource_monitor:
self._resource_monitor.stop()
if self._logger:
self._logger.set_flush_period(None)
# this is so in theory we can close a main task and start a new one
if self.is_main_task():
Task.__main_task = None
except Exception:
# make sure we do not interrupt the exit process
pass
@classmethod
def __register_at_exit(cls, exit_callback, only_remove_signal_and_exception_hooks=False):
class ExitHooks(object):
_orig_exit = None
_orig_exc_handler = None
remote_user_aborted = False
def __init__(self, callback):
self.exit_code = None
self.exception = None
self.signal = None
self._exit_callback = callback
self._org_handlers = {}
self._signal_recursion_protection_flag = False
self._except_recursion_protection_flag = False
def update_callback(self, callback):
if self._exit_callback and not six.PY2:
try:
atexit.unregister(self._exit_callback)
except Exception:
pass
self._exit_callback = callback
if callback:
self.hook()
else:
# un register int hook
if self._orig_exc_handler:
sys.excepthook = self._orig_exc_handler
self._orig_exc_handler = None
for s in self._org_handlers:
# noinspection PyBroadException
try:
signal.signal(s, self._org_handlers[s])
except Exception:
pass
self._org_handlers = {}
def hook(self):
if self._orig_exit is None:
self._orig_exit = sys.exit
sys.exit = self.exit
if self._orig_exc_handler is None:
self._orig_exc_handler = sys.excepthook
sys.excepthook = self.exc_handler
if self._exit_callback:
atexit.register(self._exit_callback)
if self._org_handlers:
if sys.platform == 'win32':
catch_signals = [signal.SIGINT, signal.SIGTERM, signal.SIGSEGV, signal.SIGABRT,
signal.SIGILL, signal.SIGFPE]
else:
catch_signals = [signal.SIGINT, signal.SIGTERM, signal.SIGSEGV, signal.SIGABRT,
signal.SIGILL, signal.SIGFPE, signal.SIGQUIT]
for s in catch_signals:
# noinspection PyBroadException
try:
self._org_handlers[s] = signal.getsignal(s)
signal.signal(s, self.signal_handler)
except Exception:
pass
def exit(self, code=0):
self.exit_code = code
self._orig_exit(code)
def exc_handler(self, exctype, value, traceback, *args, **kwargs):
if self._except_recursion_protection_flag:
return sys.__excepthook__(exctype, value, traceback, *args, **kwargs)
self._except_recursion_protection_flag = True
self.exception = value
if self._orig_exc_handler:
ret = self._orig_exc_handler(exctype, value, traceback, *args, **kwargs)
else:
ret = sys.__excepthook__(exctype, value, traceback, *args, **kwargs)
self._except_recursion_protection_flag = False
return ret
def signal_handler(self, sig, frame):
if self._signal_recursion_protection_flag:
# call original
org_handler = self._org_handlers.get(sig)
if isinstance(org_handler, Callable):
org_handler = org_handler(sig, frame)
return org_handler
self._signal_recursion_protection_flag = True
# call exit callback
self.signal = sig
if self._exit_callback:
# noinspection PyBroadException
try:
self._exit_callback()
except Exception:
pass
# call original signal handler
org_handler = self._org_handlers.get(sig)
if isinstance(org_handler, Callable):
# noinspection PyBroadException
try:
org_handler = org_handler(sig, frame)
except Exception:
org_handler = signal.SIG_DFL
# remove stdout logger, just in case
# noinspection PyBroadException
try:
Logger._remove_std_logger()
except Exception:
pass
self._signal_recursion_protection_flag = False
# return handler result
return org_handler
# we only remove the signals since this will hang subprocesses
if only_remove_signal_and_exception_hooks:
if not cls.__exit_hook:
return
if cls.__exit_hook._orig_exc_handler:
sys.excepthook = cls.__exit_hook._orig_exc_handler
cls.__exit_hook._orig_exc_handler = None
for s in cls.__exit_hook._org_handlers:
# noinspection PyBroadException
try:
signal.signal(s, cls.__exit_hook._org_handlers[s])
except Exception:
pass
cls.__exit_hook._org_handlers = {}
return
if cls.__exit_hook is None:
# noinspection PyBroadException
try:
cls.__exit_hook = ExitHooks(exit_callback)
cls.__exit_hook.hook()
except Exception:
cls.__exit_hook = None
else:
cls.__exit_hook.update_callback(exit_callback)
@classmethod
def __get_task(cls, task_id=None, project_name=None, task_name=None):
if task_id:
return cls(private=cls.__create_protection, task_id=task_id, log_to_backend=False)
res = cls._send(
cls._get_default_session(),
projects.GetAllRequest(
name=exact_match_regex(project_name)
)
)
project = get_single_result(entity='project', query=project_name, results=res.response.projects)
res = cls._send(
cls._get_default_session(),
tasks.GetAllRequest(
project=[project.id],
name=exact_match_regex(task_name),
only_fields=['id', 'name', 'last_update']
)
)
task = get_single_result(entity='task', query=task_name, results=res.response.tasks, raise_on_error=False)
return cls(
private=cls.__create_protection,
task_id=task.id,
log_to_backend=False,
)
@classmethod
def __get_hash_key(cls, *args):
def normalize(x):
return "<{}>".format(x) if x is not None else ""
return ":".join(map(normalize, args))
@classmethod
def __get_last_used_task_id(cls, default_project_name, default_task_name, default_task_type):
hash_key = cls.__get_hash_key(cls._get_api_server(), default_project_name, default_task_name, default_task_type)
# check if we have a cached task_id we can reuse
# it must be from within the last 24h and with the same project/name/type
task_sessions = SessionCache.load_dict(str(cls))
task_data = task_sessions.get(hash_key)
if task_data is None:
return None
try:
task_data['type'] = cls.TaskTypes(task_data['type'])
except (ValueError, KeyError):
LoggerRoot.get_base_logger().warning(
"Corrupted session cache entry: {}. "
"Unsupported task type: {}"
"Creating a new task.".format(hash_key, task_data['type']),
)
return None
return task_data
@classmethod
def __update_last_used_task_id(cls, default_project_name, default_task_name, default_task_type, task_id):
hash_key = cls.__get_hash_key(cls._get_api_server(), default_project_name, default_task_name, default_task_type)
task_id = str(task_id)
# update task session cache
task_sessions = SessionCache.load_dict(str(cls))
last_task_session = {'time': time.time(), 'project': default_project_name, 'name': default_task_name,
'type': default_task_type, 'id': task_id}
# remove stale sessions
for k in list(task_sessions.keys()):
if ((time.time() - task_sessions[k].get('time', 0)) >
60 * 60 * cls.__task_id_reuse_time_window_in_hours):
task_sessions.pop(k)
# update current session
task_sessions[hash_key] = last_task_session
# store
SessionCache.store_dict(str(cls), task_sessions)
@classmethod
def __task_timed_out(cls, task_data):
return \
task_data and \
task_data.get('id') and \
task_data.get('time') and \
(time.time() - task_data.get('time')) > (60 * 60 * cls.__task_id_reuse_time_window_in_hours)
@classmethod
def __get_task_api_obj(cls, task_id, only_fields=None):
if not task_id:
return None
all_tasks = cls._send(
cls._get_default_session(),
tasks.GetAllRequest(id=[task_id], only_fields=only_fields),
).response.tasks
# The task may not exist in environment changes
if not all_tasks:
return None
return all_tasks[0]
@classmethod
def __task_is_relevant(cls, task_data):
"""
Check that a cached task is relevant for reuse.
A task is relevant for reuse if:
1. It is not timed out i.e it was last use in the previous 24 hours.
2. It's name, project and type match the data in the server, so not
to override user changes made by using the UI.
:param task_data: A mapping from 'id', 'name', 'project', 'type' keys
to the task's values, as saved in the cache.
:return: True if the task is relevant for reuse, False if not.
"""
if not task_data:
return False
if cls.__task_timed_out(task_data):
return False
task_id = task_data.get('id')
if not task_id:
return False
task = cls.__get_task_api_obj(task_id, ('id', 'name', 'project', 'type'))
if task is None:
return False
project_name = None
if task.project:
project = cls._send(
cls._get_default_session(),
projects.GetByIdRequest(project=task.project)
).response.project
if project:
project_name = project.name
compares = (
(task.name, 'name'),
(project_name, 'project'),
(task.type, 'type'),
)
# compare after casting to string to avoid enum instance issues
# remember we might have replaced the api version by now, so enums are different
return all(str(server_data) == str(task_data.get(task_data_key)) for server_data, task_data_key in compares)
@classmethod
def __close_timed_out_task(cls, task_data):
if not task_data:
return False
task = cls.__get_task_api_obj(task_data.get('id'), ('id', 'status'))
if task is None:
return False
stopped_statuses = (
str(tasks.TaskStatusEnum.stopped),
str(tasks.TaskStatusEnum.published),
str(tasks.TaskStatusEnum.publishing),
str(tasks.TaskStatusEnum.closed),
str(tasks.TaskStatusEnum.failed),
str(tasks.TaskStatusEnum.completed),
)
if str(task.status) not in stopped_statuses:
cls._send(
cls._get_default_session(),
tasks.StoppedRequest(
task=task.id,
force=True,
status_message="Stopped timed out development task"
),
)
return True
return False