import atexit import os import re import signal import sys import threading import time from argparse import ArgumentParser from collections import OrderedDict, Callable import psutil import six from pathlib2 import Path 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 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 PatchSummaryToEventTransformer, PatchTensorFlowEager, \ PatchKerasModelIO, PatchTensorflowModelIO 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 NotSet = object() 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 __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): """ 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 (in development mode, not when running remotely) :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(): # 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 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) PatchSummaryToEventTransformer.update_current_task(task) PatchTensorFlowEager.update_current_task(task) PatchKerasModelIO.update_current_task(task) PatchTensorflowModelIO.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.console( '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([]) 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.console('TRAINS Task: Closing old development task id={}'.format(default_task.get('id'))) # print warning, reusing/creating a task if default_task_id: logger.console('TRAINS Task: overwriting (reusing) task id=%s' % task.id) else: logger.console('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 @staticmethod def get_task(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 Task.__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) helper.check_write_permissions(value) self.storage_uri = value @property def artifacts(self): """ dictionary of Task artifacts (name, artifact) :return: dict """ return self._artifacts_manager.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, flush_period=NotSet): """ 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 """ 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 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 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() 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 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 - dict will be stored as .json, - numpy.ndarray will be stored as .npz, - 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) @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 _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.warning('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.get_logger().warn( "### 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._detect_repo_async_thread.join(timeout=timeout) 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().console(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: # 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.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 self.reporter.stop() if print_done_waiting: self.log.info('Finished uploading') else: 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() self._logger.set_flush_period(None) # this is so in theory we can close a main task and start a new one 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'] ) ) task = get_single_result(entity='task', query=task_name, results=res.response.tasks) 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