################################################################################
# Copyright (c) 2021 ContinualAI. #
# Copyrights licensed under the MIT License. #
# See the accompanying LICENSE file for terms. #
# #
# Date: 12-05-2020 #
# Author(s): Lorenzo Pellegrini #
# E-mail: contact@continualai.org #
# Website: avalanche.continualai.org #
################################################################################
from abc import abstractmethod
import warnings
try:
from typing import (
TypeVar,
Tuple,
List,
Protocol,
runtime_checkable,
Sequence,
Any,
Union,
Iterable,
Generic,
TYPE_CHECKING,
)
if TYPE_CHECKING:
from .generic_scenario import CLScenario, CLStream, CLExperience
except ImportError:
from typing import (
TypeVar,
Tuple,
List,
Sequence,
Any,
Union,
Iterable,
Generic,
)
from typing_extensions import Protocol, runtime_checkable
from avalanche.benchmarks.utils import AvalancheDataset
TCLScenario = TypeVar("TCLScenario", bound="CLScenario")
TCLExperience = TypeVar("TCLExperience", bound="CLExperience")
TCLStream = TypeVar("TCLStream", bound="CLStream")
[docs]@runtime_checkable
class ClassificationExperience(Protocol[TCLScenario, TCLStream]):
"""Definition of a classification experience.
A classification experience contains a set of patterns
which has become available at a particular time instant. The content and
size of an Experience is defined by the specific benchmark that creates the
IExperience instance.
For instance, an experience of a New Classes scenario will contain all
patterns belonging to a subset of classes of the original training set. An
experience of a New Instance scenario will contain patterns from previously
seen classes.
Experiences of Single Incremental Task (a.k.a. task-free) scenarios are
usually called "batches" while in Multi Task scenarios an Experience is
usually associated to a "task". Finally, in a Multi Incremental Task
scenario the Experience may be composed by patterns from different tasks.
"""
origin_stream: TCLStream
"""
A reference to the original stream from which this experience was obtained.
"""
benchmark: TCLScenario
"""
A reference to the benchmark.
"""
current_experience: int
"""
This is an incremental, 0-indexed, value used to keep track of the position
of current experience in the original stream.
Beware that this value only describes the experience position in the
original stream and may be unrelated to the order in which the strategy will
encounter experiences.
"""
dataset: AvalancheDataset
"""
The dataset containing the patterns available in this experience.
"""
@property
@abstractmethod
def task_labels(self) -> List[int]:
"""
This list will contain the unique task labels of the patterns contained
in this experience. In the most common scenarios this will be a list
with a single value. Note: for scenarios that don't produce task labels,
a placeholder task label value like 0 is usually set to each pattern
(see the description of the originating scenario for details).
"""
...
@property
@abstractmethod
def task_label(self) -> int:
"""
The task label. This value will never have value "None". However,
for scenarios that don't produce task labels a placeholder value like 0
is usually set. Beware that this field is meant as a shortcut to obtain
a unique task label: it assumes that only patterns labeled with a
single task label are present. If this experience contains patterns from
multiple tasks, accessing this property will result in an exception.
"""
...
@property
def scenario(self) -> TCLScenario:
"""This property is DEPRECATED, use self.benchmark instead."""
warnings.warn(
"Using self.scenario is deprecated in Experience. "
"Consider using self.benchmark instead.",
stacklevel=2,
)
return self.benchmark
__all__ = [
"ClassificationExperience",
"TCLExperience",
"TCLScenario",
"TCLStream",
]