arpes.deep_learning.interpret.InterpretationItem

class arpes.deep_learning.interpret.InterpretationItem(target: Any, predicted_target: Any, loss: float, index: int, parent_dataloader: torch.utils.data.DataLoader)

Provides tools to introspect model performance on a single item.

__init__(target: Any, predicted_target: Any, loss: float, index: int, parent_dataloader: torch.utils.data.DataLoader) → None

Methods

__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__(target, predicted_target, loss, …)
__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)
__reduce__()	Helper for pickle.
__reduce_ex__(protocol, /)	Helper for pickle.
__repr__()	Return repr(self).
__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(value)	Pulls the predicted target backwards through the transformation stack.
show(input_formatter, target_formatter[, …])	Plots this item onto the provided axes.

Attributes

__annotations__
__dataclass_fields__
__dataclass_params__
__dict__
__doc__
__hash__
__module__
__weakref__	list of weak references to the object (if defined)
dataset	Fetches the original dataset used to train and containing this item.
target
predicted_target
loss
index
parent_dataloader