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Edit docstrings (#1005)
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@ -2088,8 +2088,8 @@ class Task(IdObjectBase, AccessMixin, SetupUploadMixin):
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Get the Task's configuration object section as a blob of text
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Use only for automation (externally), otherwise use `Task.connect_configuration`.
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:return: The Task's configurations as a
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dict (config name as key) and text blob as value (unconstrained text string)
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:return: The Task's configurations as a dict (config name as key) and text blob as value (unconstrained text
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string)
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"""
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if not Session.check_min_api_version('2.9'):
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raise ValueError(
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@ -2269,8 +2269,8 @@ class Task(IdObjectBase, AccessMixin, SetupUploadMixin):
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Notice: Must be called before `Task.init` !
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:param force: Set force using `pip freeze` flag on/off
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:param requirements_file: Optional pass requirements.txt file to use
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(instead of `pip freeze` or automatic analysis)
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:param requirements_file: Optional pass requirements.txt file to use (instead of `pip freeze` or automatic
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analysis)
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"""
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cls._force_use_pip_freeze = requirements_file if requirements_file else bool(force)
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263
clearml/task.py
263
clearml/task.py
@ -303,153 +303,134 @@ class Task(_Task):
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:param tags: Add a list of tags (str) to the created Task. For example: tags=['512x512', 'yolov3']
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:param bool reuse_last_task_id: Force a new Task (experiment) with a previously used Task ID,
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and the same project and Task name.
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and the same project and Task name. If the previously executed Task has artifacts or models, it will not be
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reused (overwritten), and a new Task will be created. When a Task is reused, the previous execution outputs
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are deleted, including console outputs and logs. The values are:
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.. note::
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If the previously executed Task has artifacts or models, it will not be reused (overwritten)
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and a new Task will be created.
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When a Task is reused, the previous execution outputs are deleted, including console outputs and logs.
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- ``True`` - Reuse the last Task ID. (default)
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- ``False`` - Force a new Task (experiment).
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- A string - You can also specify a Task ID (string) to be reused, instead of the cached ID based on the project/name combination.
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:param bool continue_last_task: Continue the execution of a previously executed Task (experiment). When
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continuing the executing of a previously executed Task,
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all previous artifacts / models / logs remain intact.
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New logs will continue iteration/step based on the previous-execution maximum iteration value.
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For example, The last train/loss scalar reported was iteration 100, the next report will be iteration 101.
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The values are:
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- ``True`` - Reuse the last Task ID. (default)
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- ``False`` - Force a new Task (experiment).
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- A string - You can also specify a Task ID (string) to be reused, instead of the cached ID based on the project/name combination.
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- ``True`` - Continue the last Task ID. Specified explicitly by reuse_last_task_id or implicitly with the same logic as reuse_last_task_id
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- ``False`` - Overwrite the execution of previous Task (default).
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- A string - You can also specify a Task ID (string) to be continued. This is equivalent to `continue_last_task=True` and `reuse_last_task_id=a_task_id_string`.
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- An integer - Specify initial iteration offset (override the auto automatic last_iteration_offset). Pass 0, to disable the automatic last_iteration_offset or specify a different initial offset. You can specify a Task ID to be used with `reuse_last_task_id='task_id_here'`
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:param bool continue_last_task: Continue the execution of a previously executed Task (experiment)
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.. note::
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When continuing the executing of a previously executed Task,
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all previous artifacts / models/ logs are intact.
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New logs will continue iteration/step based on the previous-execution maximum iteration value.
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For example:
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The last train/loss scalar reported was iteration 100, the next report will be iteration 101.
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The values are:
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- ``True`` - Continue the last Task ID. Specified explicitly by reuse_last_task_id or implicitly with the same logic as reuse_last_task_id
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- ``False`` - Overwrite the execution of previous Task (default).
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- A string - You can also specify a Task ID (string) to be continued. This is equivalent to `continue_last_task=True` and `reuse_last_task_id=a_task_id_string`.
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- An integer - Specify initial iteration offset (override the auto automatic last_iteration_offset). Pass 0, to disable the automatic last_iteration_offset or specify a different initial offset. You can specify a Task ID to be used with `reuse_last_task_id='task_id_here'`
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:param str output_uri: The default location for output models and other artifacts.
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If True, the default files_server will be used for model storage.
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In the default location, ClearML creates a subfolder for the output.
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The subfolder structure is the following:
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<output destination name> / <project name> / <task name>.<Task ID>
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:param str output_uri: The default location for output models and other artifacts. If True, the default
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files_server will be used for model storage. In the default location, ClearML creates a subfolder for the
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output. The subfolder structure is the following: `<output destination name> / <project name> / <task name>.<Task ID>`.
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Note that for cloud storage, you must install the **ClearML** package for your cloud storage type,
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and then configure your storage credentials. For detailed information, see "Storage" in the ClearML
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Documentation.
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The following are examples of ``output_uri`` values for the supported locations:
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- A shared folder: ``/mnt/share/folder``
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- S3: ``s3://bucket/folder``
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- Google Cloud Storage: ``gs://bucket-name/folder``
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- Azure Storage: ``azure://company.blob.core.windows.net/folder/``
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- Default file server: True
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.. important::
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For cloud storage, you must install the **ClearML** package for your cloud storage type,
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and then configure your storage credentials. For detailed information, see
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`ClearML Python Client Extras <./references/clearml_extras_storage/>`_ in the "ClearML Python Client
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Reference" section.
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- A shared folder: ``/mnt/share/folder``
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- S3: ``s3://bucket/folder``
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- Google Cloud Storage: ``gs://bucket-name/folder``
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- Azure Storage: ``azure://company.blob.core.windows.net/folder/``
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- Default file server: True
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:param auto_connect_arg_parser: Automatically connect an argparse object to the Task. Supported argument
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parser packages are: argparse, click, python-fire, jsonargparse.
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parser packages are: argparse, click, python-fire, jsonargparse. The values are:
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The values are:
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- ``True`` - Automatically connect. (default)
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- ``False`` - Do not automatically connect.
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of connected
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arguments. The dictionary keys are argparse variable names and the values are booleans.
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The ``False`` value excludes the specified argument from the Task's parameter section.
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Keys missing from the dictionary default to ``True``, you can change it to be ``False`` by adding
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``*`` key as ``False`` to the dictionary.
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An empty dictionary defaults to ``False``.
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- ``True`` - Automatically connect. (default)
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- ``False`` - Do not automatically connect.
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of connected
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arguments. The dictionary keys are argparse variable names and the values are booleans.
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The ``False`` value excludes the specified argument from the Task's parameter section.
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Keys missing from the dictionary default to ``True``, you can change it to be ``False`` by adding
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``*`` key as ``False`` to the dictionary.
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An empty dictionary defaults to ``False``.
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For example:
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For example:
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.. code-block:: py
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.. code-block:: py
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auto_connect_arg_parser={"do_not_include_me": False, }
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auto_connect_arg_parser={"do_not_include_me": False, }
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.. code-block:: py
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.. code-block:: py
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auto_connect_arg_parser={"only_include_me": True, "*": False}
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auto_connect_arg_parser={"only_include_me": True, "*": False}
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.. note::
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.. note::
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To manually connect an argparse, use :meth:`Task.connect`.
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:param auto_connect_frameworks: Automatically connect frameworks This includes patching MatplotLib, XGBoost,
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scikit-learn, Keras callbacks, and TensorBoard/X to serialize plots, graphs, and the model location to
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the **ClearML Server** (backend), in addition to original output destination.
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The values are:
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- ``True`` - Automatically connect (default)
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- ``False`` - Do not automatically connect
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of connected
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frameworks. The dictionary keys are frameworks and the values are booleans, other dictionaries used for
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finer control or wildcard strings.
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In case of wildcard strings, the local path of a model file has to match at least one wildcard to be
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saved/loaded by ClearML. Example: {'pytorch' : '*.pt', 'tensorflow': ['*.h5', '*']}
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Keys missing from the dictionary default to ``True``, and an empty dictionary defaults to ``False``.
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Supported keys for finer control: {'tensorboard': {'report_hparams': bool}} # whether to report TensorBoard hyperparameters
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- ``True`` - Automatically connect (default)
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- ``False`` - Do not automatically connect
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of connected
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frameworks. The dictionary keys are frameworks and the values are booleans, other dictionaries used for
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finer control or wildcard strings.
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In case of wildcard strings, the local path of a model file has to match at least one wildcard to be
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saved/loaded by ClearML. Example: {'pytorch' : '*.pt', 'tensorflow': ['*.h5', '*']}
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Keys missing from the dictionary default to ``True``, and an empty dictionary defaults to ``False``.
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Supported keys for finer control: {'tensorboard': {'report_hparams': bool}} # whether to report TensorBoard hyperparameters
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For example:
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For example:
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.. code-block:: py
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.. code-block:: py
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auto_connect_frameworks={
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'matplotlib': True, 'tensorflow': ['*.hdf5, 'something_else*], 'tensorboard': True,
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'pytorch': ['*.pt'], 'xgboost': True, 'scikit': True, 'fastai': True,
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'lightgbm': True, 'hydra': True, 'detect_repository': True, 'tfdefines': True,
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'joblib': True, 'megengine': True, 'catboost': True, 'gradio': True
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}
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auto_connect_frameworks={
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'matplotlib': True, 'tensorflow': ['*.hdf5, 'something_else*], 'tensorboard': True,
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'pytorch': ['*.pt'], 'xgboost': True, 'scikit': True, 'fastai': True,
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'lightgbm': True, 'hydra': True, 'detect_repository': True, 'tfdefines': True,
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'joblib': True, 'megengine': True, 'catboost': True, 'gradio': True
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}
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.. code-block:: py
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.. code-block:: py
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auto_connect_frameworks={'tensorboard': {'report_hparams': False}}
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auto_connect_frameworks={'tensorboard': {'report_hparams': False}}
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:param bool auto_resource_monitoring: Automatically create machine resource monitoring plots
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These plots appear in the **ClearML Web-App (UI)**, **RESULTS** tab, **SCALARS** sub-tab,
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with a title of **:resource monitor:**. The values are:
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with a title of **:resource monitor:**.
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The values are:
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- ``True`` - Automatically create resource monitoring plots. (default)
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- ``False`` - Do not automatically create.
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- Class Type - Create ResourceMonitor object of the specified class type.
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- ``True`` - Automatically create resource monitoring plots. (default)
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- ``False`` - Do not automatically create.
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- Class Type - Create ResourceMonitor object of the specified class type.
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:param auto_connect_streams: Control the automatic logging of stdout and stderr. The values are:
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:param auto_connect_streams: Control the automatic logging of stdout and stderr.
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The values are:
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- ``True`` - Automatically connect (default)
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- ``False`` - Do not automatically connect
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of stdout and
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stderr. The dictionary keys are 'stdout' , 'stderr' and 'logging', the values are booleans.
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Keys missing from the dictionary default to ``False``, and an empty dictionary defaults to ``False``.
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Notice, the default behaviour is logging stdout/stderr. The `logging` module is logged as a by product
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of the stderr logging
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- ``True`` - Automatically connect (default)
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- ``False`` - Do not automatically connect
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- A dictionary - In addition to a boolean, you can use a dictionary for fined grained control of stdout and
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stderr. The dictionary keys are 'stdout' , 'stderr' and 'logging', the values are booleans.
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Keys missing from the dictionary default to ``False``, and an empty dictionary defaults to ``False``.
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Notice, the default behaviour is logging stdout/stderr. The `logging` module is logged as a by product
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of the stderr logging
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For example:
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For example:
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.. code-block:: py
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.. code-block:: py
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auto_connect_streams={'stdout': True, 'stderr': True, 'logging': False}
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auto_connect_streams={'stdout': True, 'stderr': True, 'logging': False}
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:param deferred_init: (default: False) Wait for Task to be fully initialized (regular behaviour).
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** BETA feature! use with care **
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** BETA feature! use with care **.
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If set to True, `Task.init` function returns immediately and all initialization / communication
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to the clearml-server is running in a background thread. The returned object is
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a full proxy to the regular Task object, hence everything will be working as expected.
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Default behaviour can be controlled with: ``CLEARML_DEFERRED_TASK_INIT=1``
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Default behaviour can be controlled with: ``CLEARML_DEFERRED_TASK_INIT=1``. Notes:
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Notes:
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- Any access to the returned proxy `Task` object will essentially wait for the `Task.init`
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to be completed. For example: `print(task.name)` will wait for `Task.init` to complete in the
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background and then return the `name` property of the task original object
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- Before `Task.init` completes in the background, auto-magic logging (console/metric) might be missed
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- If running via an agent, this argument is ignored, and Task init is called synchronously (default)
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- Any access to the returned proxy `Task` object will essentially wait for the `Task.init` to be completed.
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For example: `print(task.name)` will wait for `Task.init` to complete in the
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background and then return the `name` property of the task original object
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- Before `Task.init` completes in the background, auto-magic logging (console/metric) might be missed
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- If running via an agent, this argument is ignored, and Task init is called synchronously (default)
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:return: The main execution Task (Task context)
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:rtype: Task
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@ -807,7 +788,7 @@ class Task(_Task):
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"""
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Manually create and populate a new Task (experiment) in the system.
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If the code does not already contain a call to ``Task.init``, pass add_task_init_call=True,
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and the code will be patched in remote execution (i.e. when executed by `clearml-agent`
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and the code will be patched in remote execution (i.e. when executed by `clearml-agent`)
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.. note::
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This method **always** creates a new Task.
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@ -974,15 +955,15 @@ class Task(_Task):
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:param dict task_filter: filter and order Tasks.
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See :class:`.backend_api.service.v?.tasks.GetAllRequest` for details; the ? needs to be replaced by the appropriate version.
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- ``parent`` - (str) filter by parent task-id matching
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- ``search_text`` - (str) free text search (in task fields comment/name/id)
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- ``status`` - List[str] List of valid statuses. Options are: "created", "queued", "in_progress", "stopped", "published", "publishing", "closed", "failed", "completed", "unknown"
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- ``type`` - List[str] List of valid task type. Options are: 'training', 'testing', 'inference', 'data_processing', 'application', 'monitor', 'controller', 'optimizer', 'service', 'qc'. 'custom'
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- ``user`` - List[str] Filter based on Task's user owner, provide list of valid user IDs.
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- ``order_by`` - List[str] List of field names to order by. When ``search_text`` is used. Use '-' prefix to specify descending order. Optional, recommended when using page. Example: ``order_by=['-last_update']``
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- ``_all_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in All `fields`. Example: dict(fields=['script.repository'], pattern='github.com/user')
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- ``_any_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in Any of the `fields`. Example: dict(fields=['comment', 'name'], pattern='my comment')
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- Examples - ``{'status': ['stopped'], 'order_by': ["-last_update"]}`` , ``{'order_by'=['-last_update'], '_all_'=dict(fields=['script.repository'], pattern='github.com/user'))``
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- ``parent`` - (str) filter by parent task-id matching
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- ``search_text`` - (str) free text search (in task fields comment/name/id)
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- ``status`` - List[str] List of valid statuses. Options are: "created", "queued", "in_progress", "stopped", "published", "publishing", "closed", "failed", "completed", "unknown"
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- ``type`` - List[str] List of valid task types. Options are: 'training', 'testing', 'inference', 'data_processing', 'application', 'monitor', 'controller', 'optimizer', 'service', 'qc'. 'custom'
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- ``user`` - List[str] Filter based on Task's user owner, provide list of valid user IDs.
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- ``order_by`` - List[str] List of field names to order by. When ``search_text`` is used. Use '-' prefix to specify descending order. Optional, recommended when using page. Example: ``order_by=['-last_update']``
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- ``_all_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in All `fields`. Example: dict(fields=['script.repository'], pattern='github.com/user')
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- ``_any_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in Any of the `fields`. Example: dict(fields=['comment', 'name'], pattern='my comment')
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- Examples - ``{'status': ['stopped'], 'order_by': ["-last_update"]}`` , ``{'order_by'=['-last_update'], '_all_'=dict(fields=['script.repository'], pattern='github.com/user'))``
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:return: The Tasks specified by the parameter combinations (see the parameters).
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:rtype: List[Task]
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@ -1016,8 +997,8 @@ class Task(_Task):
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``project_name`` (or all projects if ``project_name`` is ``None``).
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This method supports regular expressions for name matching. (Optional)
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:param str project_name: project name (str) the task belongs to (use None for all projects)
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:param str task_name: task name (str) in within the selected project
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Return any partial match of task_name, regular expressions matching is also supported
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:param str task_name: task name (str) within the selected project
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Return any partial match of task_name, regular expressions matching is also supported.
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If None is passed, returns all tasks within the project
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:param list tags: Filter based on the requested list of tags (strings)
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To exclude a tag add "-" prefix to the tag. Example: ["best", "-debug"]
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@ -1032,15 +1013,15 @@ class Task(_Task):
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:param dict task_filter: filter and order Tasks.
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See :class:`.backend_api.service.v?.tasks.GetAllRequest` for details; the ? needs to be replaced by the appropriate version.
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- ``parent`` - (str) filter by parent task-id matching
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- ``search_text`` - (str) free text search (in task fields comment/name/id)
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- ``status`` - List[str] List of valid statuses. Options are: "created", "queued", "in_progress", "stopped", "published", "publishing", "closed", "failed", "completed", "unknown"
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- ``type`` - List[Union[str, TaskTypes]] List of valid task type. Ooptions are: 'training', 'testing', 'inference', 'data_processing', 'application', 'monitor', 'controller', 'optimizer', 'service', 'qc'. 'custom'
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- ``user`` - List[str] Filter based on Task's user owner, provide list of valid user IDs.
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- ``order_by`` - List[str] List of field names to order by. When search_text is used. Use '-' prefix to specify descending order. Optional, recommended when using page. Example: ``order_by=['-last_update']``
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- ``_all_`` - dict(fields=[], pattern='') Match string ``pattern`` (regular expression) appearing in All `fields`. ``dict(fields=['script.repository'], pattern='github.com/user')``
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- ``_any_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in Any of the `fields`. `dict(fields=['comment', 'name'], pattern='my comment')`
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- Examples: ``{'status': ['stopped'], 'order_by': ["-last_update"]}``, ``{'order_by'=['-last_update'], '_all_'=dict(fields=['script.repository'], pattern='github.com/user')}``
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- ``parent`` - (str) filter by parent task-id matching
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- ``search_text`` - (str) free text search (in task fields comment/name/id)
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- ``status`` - List[str] List of valid statuses. Options are: "created", "queued", "in_progress", "stopped", "published", "publishing", "closed", "failed", "completed", "unknown"
|
||||
- ``type`` - List[Union[str, TaskTypes]] List of valid task types. Options are: 'training', 'testing', 'inference', 'data_processing', 'application', 'monitor', 'controller', 'optimizer', 'service', 'qc'. 'custom'
|
||||
- ``user`` - List[str] Filter based on Task's user owner, provide list of valid user IDs.
|
||||
- ``order_by`` - List[str] List of field names to order by. When search_text is used. Use '-' prefix to specify descending order. Optional, recommended when using page. Example: ``order_by=['-last_update']``
|
||||
- ``_all_`` - dict(fields=[], pattern='') Match string ``pattern`` (regular expression) appearing in All `fields`. ``dict(fields=['script.repository'], pattern='github.com/user')``
|
||||
- ``_any_`` - dict(fields=[], pattern='') Match string `pattern` (regular expression) appearing in Any of the `fields`. `dict(fields=['comment', 'name'], pattern='my comment')`
|
||||
- Examples: ``{'status': ['stopped'], 'order_by': ["-last_update"]}``, ``{'order_by'=['-last_update'], '_all_'=dict(fields=['script.repository'], pattern='github.com/user')}``
|
||||
|
||||
:return: The Tasks specified by the parameter combinations (see the parameters).
|
||||
"""
|
||||
@ -1228,8 +1209,7 @@ class Task(_Task):
|
||||
|
||||
.. note::
|
||||
A worker daemon must be listening at the queue for the worker to fetch the Task and execute it,
|
||||
see `Use Case Examples <../clearml_agent_ref/#use-case-examples>`_ on the "ClearML Agent
|
||||
Reference page.
|
||||
see `ClearML Agent <../clearml_agent>`_ in the ClearML Documentation.
|
||||
|
||||
:param Task/str task: The Task to enqueue. Specify a Task object or Task ID.
|
||||
:param str queue_name: The name of the queue. If not specified, then ``queue_id`` must be specified.
|
||||
@ -1391,7 +1371,7 @@ class Task(_Task):
|
||||
# type: (Union[Sequence[str], str]) -> None
|
||||
"""
|
||||
Add Tags to this task. Old tags are not deleted. When executing a Task (experiment) remotely,
|
||||
this method has no effect).
|
||||
this method has no effect.
|
||||
|
||||
:param tags: A list of tags which describe the Task to add.
|
||||
"""
|
||||
@ -1420,8 +1400,8 @@ class Task(_Task):
|
||||
:param str name: A section name associated with the connected object, if 'name' is None defaults to 'General'
|
||||
Currently, `name` is only supported for `dict` and `TaskParameter` objects, and should be omitted for the other supported types. (Optional)
|
||||
|
||||
For example, by setting `name='General'` the connected dictionary will be under the General section in the hyper-parameters section.
|
||||
While by setting `name='Train'` the connected dictionary will be under the Train section in the hyper-parameters section.
|
||||
For example, by setting `name='General'` the connected dictionary will be under the General section in the hyperparameters section.
|
||||
While by setting `name='Train'` the connected dictionary will be under the Train section in the hyperparameters section.
|
||||
|
||||
:return: It will return the same object that was passed as the `mutable` argument to the method, except if the type of the object is dict.
|
||||
For dicts the :meth:`Task.connect` will return the dict decorated as a `ProxyDictPostWrite`.
|
||||
@ -1927,15 +1907,14 @@ class Task(_Task):
|
||||
before continuing.
|
||||
|
||||
:param str extension_name: File extension which indicates the format the artifact should be stored as.
|
||||
The following are supported, depending on the artifact type
|
||||
(default value applies when extension_name is None):
|
||||
The following are supported, depending on the artifact type (default value applies when extension_name is None):
|
||||
|
||||
- Any - ``.pkl`` if passed supersedes any other serialization type, and always pickles the object
|
||||
- dict - ``.json``, ``.yaml`` (default ``.json``)
|
||||
- pandas.DataFrame - ``.csv.gz``, ``.parquet``, ``.feather``, ``.pickle`` (default ``.csv.gz``)
|
||||
- numpy.ndarray - ``.npz``, ``.csv.gz`` (default ``.npz``)
|
||||
- PIL.Image - whatever extensions PIL supports (default ``.png``)
|
||||
- In case the ``serialization_function`` argument is set - any extension is supported
|
||||
- Any - ``.pkl`` if passed supersedes any other serialization type, and always pickles the object
|
||||
- dict - ``.json``, ``.yaml`` (default ``.json``)
|
||||
- pandas.DataFrame - ``.csv.gz``, ``.parquet``, ``.feather``, ``.pickle`` (default ``.csv.gz``)
|
||||
- numpy.ndarray - ``.npz``, ``.csv.gz`` (default ``.npz``)
|
||||
- PIL.Image - whatever extensions PIL supports (default ``.png``)
|
||||
- In case the ``serialization_function`` argument is set - any extension is supported
|
||||
|
||||
:param Callable[Any, Union[bytes, bytearray]] serialization_function: A serialization function that takes one
|
||||
parameter of any type which is the object to be serialized. The function should return
|
||||
@ -1948,8 +1927,8 @@ class Task(_Task):
|
||||
|
||||
:return: The status of the upload.
|
||||
|
||||
- ``True`` - Upload succeeded.
|
||||
- ``False`` - Upload failed.
|
||||
- ``True`` - Upload succeeded.
|
||||
- ``False`` - Upload failed.
|
||||
|
||||
:raise: If the artifact object type is not supported, raise a ``ValueError``.
|
||||
"""
|
||||
@ -1985,13 +1964,13 @@ class Task(_Task):
|
||||
:param str title: Debug sample's title, also called metric in the UI
|
||||
:param str series: Debug sample's series,
|
||||
corresponding to debug sample's file name in the UI, also known as variant
|
||||
:param int n_last_iterations: How many debug samples iterations to fetch in reverse chronological order.
|
||||
:param int n_last_iterations: How many debug sample iterations to fetch in reverse chronological order.
|
||||
Leave empty to get all debug samples.
|
||||
|
||||
:raise: TypeError if `n_last_iterations` is explicitly set to anything other than a positive integer value
|
||||
|
||||
:return: A list of `dict`s, each dictionary containing the debug sample's URL and other metadata.
|
||||
The URLs can be passed to :meth:`StorageManager.get_local_copy` to fetch local copies of debug samples.
|
||||
The URLs can be passed to StorageManager.get_local_copy to fetch local copies of debug samples.
|
||||
"""
|
||||
from .config.defs import MAX_SERIES_PER_METRIC
|
||||
|
||||
@ -2419,7 +2398,7 @@ class Task(_Task):
|
||||
"""
|
||||
Delete hyperparameters for this task.
|
||||
|
||||
:param iterables: Hyper parameter key iterables. Each an iterable whose possible values each represent
|
||||
:param iterables: Hyperparameter key iterables. Each an iterable whose possible values each represent
|
||||
a hyperparameter entry to delete, value formats are:
|
||||
|
||||
* A dictionary containing a 'section' and 'name' fields
|
||||
|
||||
Loading…
Reference in New Issue
Block a user