vis4d.engine.util

Run utilities.

Functions

apply_to_collection(data, dtype, function, *args)	Recursively applies a function to all elements of a certain dtype.
is_dataclass_instance(obj)	Check if obj is dataclass instance.
move_data_to_device(batch, device[, ...])	Transfers a collection of data to the given device.

Classes

TransferableDataType()

A custom type for data that can be moved to a torch device.

class TransferableDataType

A custom type for data that can be moved to a torch device.

Example

>>> isinstance(dict, TransferableDataType)
False
>>> isinstance(torch.rand(2, 3), TransferableDataType)
True
>>> class CustomObject:
...     def __init__(self):
...         self.x = torch.rand(2, 2)
...     def to(self, device):
...         self.x = self.x.to(device)
...         return self
>>> isinstance(CustomObject(), TransferableDataType)
True

classmethod __subclasshook__(subclass)

Subclass hook.

Return type:

Union[bool, Any]

apply_to_collection(data, dtype, function, *args, wrong_dtype=None, include_none=True, **kwargs)

Recursively applies a function to all elements of a certain dtype.

Parameters:

• data (Any) – the collection to apply the function to

• dtype (Union[type, Any, tuple[Union[type, Any]]]) – the given function will be applied to all elements of this dtype

• function (Callable[[Any], Any]) – the function to apply

• *args (Any) – positional arguments (will be forwarded to calls of function)

• wrong_dtype (Union[None, type, tuple[type, ...]]) – the given function won’t be applied if this type is specified and the given collections is of the wrong_dtype even if it is of type dtype

• include_none (bool) – Whether to include an element if the output of function is None.

• **kwargs (Any) – keyword arguments (will be forwarded to calls of function)

Raises:

ValueError – If frozen dataclass is passed to apply_to_collection.

Return type:

Any

Returns:

The resulting collection

is_dataclass_instance(obj)

Check if obj is dataclass instance.

https://docs.python.org/3/library/dataclasses.html#module-level-decorators-classes-and-functions

Return type:

bool

move_data_to_device(batch, device, convert_to_numpy=False)

Transfers a collection of data to the given device.

Any object that defines a method to(device) will be moved and all other objects in the collection will be left untouched.

This implementation is modified from https://github.com/Lightning-AI/lightning

Parameters:

• batch (Any) – A tensor or collection of tensors or anything that has a method .to(...). See apply_to_collection() for a list of supported collection types.

• device (device | str | int) – The device to which the data should be moved.

• convert_to_numpy (bool) – Whether to convert from tensor to numpy array.

Return type:

Any

Returns:

The same collection but with all contained tensors residing on the new

device.