topobench.utils.utils module#

Utility functions for the TopoBenchMarkX library.

class Any(*args, **kwargs)#

Bases: object

Special type indicating an unconstrained type.

  • Any is compatible with every type.

  • Any assumed to have all methods.

  • All values assumed to be instances of Any.

Note that all the above statements are true from the point of view of static type checkers. At runtime, Any should not be used with instance checks.

class Callable#

Bases: object

class DictConfig(content, key=None, parent=None, ref_type=typing.Any, key_type=typing.Any, element_type=typing.Any, is_optional=True, flags=None)#

Bases: BaseContainer, MutableMapping[Any, Any]

__init__(content, key=None, parent=None, ref_type=typing.Any, key_type=typing.Any, element_type=typing.Any, is_optional=True, flags=None)#
copy()#
get(key, default_value=None)#

Return the value for key if key is in the dictionary, else default_value (defaulting to None).

items() → a set-like object providing a view on D's items#
items_ex(resolve=True, keys=None)#
keys() → a set-like object providing a view on D's keys#
pop(k[, d]) → v, remove specified key and return the corresponding value.#

If key is not found, d is returned if given, otherwise KeyError is raised.

setdefault(k[, d]) → D.get(k,d), also set D[k]=d if k not in D#
extras(cfg)#

Apply optional utilities before the task is started.

Utilities:

  • Ignoring python warnings.

  • Setting tags from command line.

  • Rich config printing.

Parameters:
cfgDictConfig

A DictConfig object containing the config tree.

find_spec(name, package=None)#

Return the spec for the specified module.

First, sys.modules is checked to see if the module was already imported. If so, then sys.modules[name].__spec__ is returned. If that happens to be set to None, then ValueError is raised. If the module is not in sys.modules, then sys.meta_path is searched for a suitable spec with the value of ‘path’ given to the finders. None is returned if no spec could be found.

If the name is for submodule (contains a dot), the parent module is automatically imported.

The name and package arguments work the same as importlib.import_module(). In other words, relative module names (with leading dots) work.

get_metric_value(metric_dict, metric_name)#

Safely retrieves value of the metric logged in LightningModule.

Parameters:
metric_dictdict

A dict containing metric values.

metric_namestr, optional

If provided, the name of the metric to retrieve.

Returns:
float, None

If a metric name was provided, the value of the metric.

task_wrapper(task_func)#

Optional decorator that controls the failure behavior when executing the task function.

This wrapper can be used to: - make sure loggers are closed even if the task function raises an exception (prevents multirun failure). - save the exception to a .log file. - mark the run as failed with a dedicated file in the logs/ folder (so we can find and rerun it later). - etc. (adjust depending on your needs).

Example: ``` @utils.task_wrapper def train(cfg: DictConfig) -> Tuple[Dict[str, Any], Dict[str, Any]]:

… return metric_dict, object_dict

```

Parameters:
task_funcCallable

The task function to be wrapped.

Returns:
Callable

The wrapped task function.