arpes.deep_learning.transforms.ComposeBoth

class arpes.deep_learning.transforms.ComposeBoth(transforms: List[Any])

Like torchvision.transforms.Compose but this operates on data & target in each transform.

__init__(transforms: List[Any]) → None

Methods

__call__(x, y)	If this transform has separate data and target functions, apply separately.
__delattr__(name, /)	Implement delattr(self, name).
__dir__()	Default dir() implementation.
__eq__(other)	Return self==value.
__format__(format_spec, /)	Default object formatter.
__ge__(value, /)	Return self>=value.
__getattribute__(name, /)	Return getattr(self, name).
__gt__(value, /)	Return self>value.
__init__(transforms)
__init_subclass__	This method is called when a class is subclassed.
__le__(value, /)	Return self<=value.
__lt__(value, /)	Return self<value.
__ne__(value, /)	Return self!=value.
__new__(**kwargs)
__post_init__()	Replace missing transforms with identities.
__reduce__()	Helper for pickle.
__reduce_ex__(protocol, /)	Helper for pickle.
__repr__()	Show both of the constitutent parts of this transform.
__setattr__(name, value, /)	Implement setattr(self, name, value).
__sizeof__()	Size of object in memory, in bytes.
__str__()	Return str(self).
__subclasshook__	Abstract classes can override this to customize issubclass().
decodes_target(y)	Pull the target back in the transform stack as far as possible.

Attributes

__annotations__
__dataclass_fields__
__dataclass_params__
__dict__
__doc__
__hash__
__module__
__weakref__	list of weak references to the object (if defined)
transforms