prototorch_models/prototorch/models/architectures/components.py

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from dataclasses import dataclass
from prototorch.core.components import LabeledComponents
from prototorch.core.initializers import (
AbstractComponentsInitializer,
LabelsInitializer,
ZerosCompInitializer,
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)
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from prototorch.models import BaseYArchitecture
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class SupervisedArchitecture(BaseYArchitecture):
"""
Supervised Architecture
An architecture that uses labeled Components as component Layer.
"""
components_layer: LabeledComponents
# HyperParameters
# ----------------------------------------------------------------------------------------------------
@dataclass
class HyperParameters:
"""
distribution: A valid prototype distribution. No default possible.
components_initializer: An implementation of AbstractComponentsInitializer. No default possible.
"""
distribution: "dict[str, int]"
component_initializer: AbstractComponentsInitializer
# Steps
# ----------------------------------------------------------------------------------------------------
def init_components(self, hparams: HyperParameters):
if hparams.component_initializer is not None:
self.components_layer = LabeledComponents(
distribution=hparams.distribution,
components_initializer=hparams.component_initializer,
labels_initializer=LabelsInitializer(),
)
proto_shape = self.components_layer.components.shape[1:]
self.hparams["initialized_proto_shape"] = proto_shape
else:
# when restoring a checkpointed model
self.components_layer = LabeledComponents(
distribution=hparams.distribution,
components_initializer=ZerosCompInitializer(
self.hparams["initialized_proto_shape"]),
)
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# Properties
# ----------------------------------------------------------------------------------------------------
@property
def prototypes(self):
"""
Returns the position of the prototypes.
"""
return self.components_layer.components.detach().cpu()
@property
def prototype_labels(self):
"""
Returns the labels of the prototypes.
"""
return self.components_layer.labels.detach().cpu()