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)[source]

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