chore: replace relative imports
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@ -3,13 +3,15 @@
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import pytorch_lightning as pl
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import torch
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import torchmetrics
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from ..core.competitions import WTAC
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from ..core.components import Components, LabeledComponents
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from ..core.distances import euclidean_distance
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from ..core.initializers import LabelsInitializer, ZerosCompInitializer
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from ..core.pooling import stratified_min_pooling
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from ..nn.wrappers import LambdaLayer
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from prototorch.core.competitions import WTAC
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from prototorch.core.components import Components, LabeledComponents
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from prototorch.core.distances import euclidean_distance
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from prototorch.core.initializers import (
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LabelsInitializer,
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ZerosCompInitializer,
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)
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from prototorch.core.pooling import stratified_min_pooling
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from prototorch.nn.wrappers import LambdaLayer
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class ProtoTorchBolt(pl.LightningModule):
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@ -4,9 +4,9 @@ import logging
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import pytorch_lightning as pl
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import torch
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from prototorch.core.components import Components
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from prototorch.core.initializers import LiteralCompInitializer
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from ..core.components import Components
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from ..core.initializers import LiteralCompInitializer
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from .extras import ConnectionTopology
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@ -1,12 +1,12 @@
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import torch
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import torchmetrics
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from prototorch.core.competitions import CBCC
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from prototorch.core.components import ReasoningComponents
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from prototorch.core.initializers import RandomReasoningsInitializer
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from prototorch.core.losses import MarginLoss
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from prototorch.core.similarities import euclidean_similarity
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from prototorch.nn.wrappers import LambdaLayer
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from ..core.competitions import CBCC
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from ..core.components import ReasoningComponents
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from ..core.initializers import RandomReasoningsInitializer
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from ..core.losses import MarginLoss
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from ..core.similarities import euclidean_similarity
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from ..nn.wrappers import LambdaLayer
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from .abstract import ImagePrototypesMixin
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from .glvq import SiameseGLVQ
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@ -5,8 +5,7 @@ Modules not yet available in prototorch go here temporarily.
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"""
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import torch
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from ..core.similarities import gaussian
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from prototorch.core.similarities import gaussian
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def rank_scaled_gaussian(distances, lambd):
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@ -1,22 +1,22 @@
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"""Models based on the GLVQ framework."""
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import torch
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from torch.nn.parameter import Parameter
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from ..core.competitions import wtac
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from ..core.distances import (
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from prototorch.core.competitions import wtac
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from prototorch.core.distances import (
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lomega_distance,
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omega_distance,
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squared_euclidean_distance,
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)
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from ..core.initializers import EyeLinearTransformInitializer
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from ..core.losses import (
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from prototorch.core.initializers import EyeLinearTransformInitializer
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from prototorch.core.losses import (
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GLVQLoss,
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lvq1_loss,
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lvq21_loss,
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)
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from ..core.transforms import LinearTransform
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from ..nn.wrappers import LambdaLayer, LossLayer
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from prototorch.core.transforms import LinearTransform
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from prototorch.nn.wrappers import LambdaLayer, LossLayer
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from torch.nn.parameter import Parameter
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from .abstract import ImagePrototypesMixin, SupervisedPrototypeModel
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from .extras import ltangent_distance, orthogonalization
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@ -2,13 +2,14 @@
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import warnings
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from ..core.competitions import KNNC
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from ..core.components import LabeledComponents
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from ..core.initializers import (
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from prototorch.core.competitions import KNNC
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from prototorch.core.components import LabeledComponents
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from prototorch.core.initializers import (
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LiteralCompInitializer,
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LiteralLabelsInitializer,
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)
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from ..utils.utils import parse_data_arg
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from prototorch.utils.utils import parse_data_arg
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from .abstract import SupervisedPrototypeModel
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@ -1,8 +1,9 @@
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"""LVQ models that are optimized using non-gradient methods."""
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from ..core.losses import _get_dp_dm
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from ..nn.activations import get_activation
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from ..nn.wrappers import LambdaLayer
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from prototorch.core.losses import _get_dp_dm
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from prototorch.nn.activations import get_activation
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from prototorch.nn.wrappers import LambdaLayer
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from .abstract import NonGradientMixin
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from .glvq import GLVQ
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@ -1,10 +1,13 @@
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"""Probabilistic GLVQ methods"""
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import torch
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from prototorch.core.losses import nllr_loss, rslvq_loss
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from prototorch.core.pooling import (
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stratified_min_pooling,
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stratified_sum_pooling,
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)
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from prototorch.nn.wrappers import LossLayer
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from ..core.losses import nllr_loss, rslvq_loss
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from ..core.pooling import stratified_min_pooling, stratified_sum_pooling
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from ..nn.wrappers import LambdaLayer, LossLayer
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from .extras import GaussianPrior, RankScaledGaussianPrior
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from .glvq import GLVQ, SiameseGMLVQ
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@ -2,11 +2,10 @@
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import numpy as np
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import torch
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from prototorch.core.competitions import wtac
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from prototorch.core.distances import squared_euclidean_distance
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from prototorch.core.losses import NeuralGasEnergy
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from ..core.competitions import wtac
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from ..core.distances import squared_euclidean_distance
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from ..core.losses import NeuralGasEnergy
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from ..nn.wrappers import LambdaLayer
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from .abstract import NonGradientMixin, UnsupervisedPrototypeModel
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from .callbacks import GNGCallback
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from .extras import ConnectionTopology
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@ -5,11 +5,10 @@ import pytorch_lightning as pl
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import torch
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import torchvision
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from matplotlib import pyplot as plt
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from prototorch.utils.colors import get_colors, get_legend_handles
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from prototorch.utils.utils import mesh2d
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from torch.utils.data import DataLoader, Dataset
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from ..utils.colors import get_colors, get_legend_handles
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from ..utils.utils import mesh2d
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class Vis2DAbstract(pl.Callback):
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