chore: replace relative imports

prototorch/models/abstract.py

@@ -3,13 +3,15 @@
 import pytorch_lightning as pl
 import torch
 import torchmetrics
-
-from ..core.competitions import WTAC
-from ..core.components import Components, LabeledComponents
-from ..core.distances import euclidean_distance
-from ..core.initializers import LabelsInitializer, ZerosCompInitializer
-from ..core.pooling import stratified_min_pooling
-from ..nn.wrappers import LambdaLayer
+from prototorch.core.competitions import WTAC
+from prototorch.core.components import Components, LabeledComponents
+from prototorch.core.distances import euclidean_distance
+from prototorch.core.initializers import (
+    LabelsInitializer,
+    ZerosCompInitializer,
+)
+from prototorch.core.pooling import stratified_min_pooling
+from prototorch.nn.wrappers import LambdaLayer
 
 
 class ProtoTorchBolt(pl.LightningModule):

prototorch/models/callbacks.py

@@ -4,9 +4,9 @@ import logging
 
 import pytorch_lightning as pl
 import torch
+from prototorch.core.components import Components
+from prototorch.core.initializers import LiteralCompInitializer
 
-from ..core.components import Components
-from ..core.initializers import LiteralCompInitializer
 from .extras import ConnectionTopology
 
 

prototorch/models/cbc.py

@@ -1,12 +1,12 @@
 import torch
 import torchmetrics
+from prototorch.core.competitions import CBCC
+from prototorch.core.components import ReasoningComponents
+from prototorch.core.initializers import RandomReasoningsInitializer
+from prototorch.core.losses import MarginLoss
+from prototorch.core.similarities import euclidean_similarity
+from prototorch.nn.wrappers import LambdaLayer
 
-from ..core.competitions import CBCC
-from ..core.components import ReasoningComponents
-from ..core.initializers import RandomReasoningsInitializer
-from ..core.losses import MarginLoss
-from ..core.similarities import euclidean_similarity
-from ..nn.wrappers import LambdaLayer
 from .abstract import ImagePrototypesMixin
 from .glvq import SiameseGLVQ
 

prototorch/models/extras.py

@@ -5,8 +5,7 @@ Modules not yet available in prototorch go here temporarily.
 """
 
 import torch
-
-from ..core.similarities import gaussian
+from prototorch.core.similarities import gaussian
 
 
 def rank_scaled_gaussian(distances, lambd):

prototorch/models/glvq.py

@@ -1,22 +1,22 @@
 """Models based on the GLVQ framework."""
 
 import torch
-from torch.nn.parameter import Parameter
-
-from ..core.competitions import wtac
-from ..core.distances import (
+from prototorch.core.competitions import wtac
+from prototorch.core.distances import (
     lomega_distance,
     omega_distance,
     squared_euclidean_distance,
 )
-from ..core.initializers import EyeLinearTransformInitializer
-from ..core.losses import (
+from prototorch.core.initializers import EyeLinearTransformInitializer
+from prototorch.core.losses import (
     GLVQLoss,
     lvq1_loss,
     lvq21_loss,
 )
-from ..core.transforms import LinearTransform
-from ..nn.wrappers import LambdaLayer, LossLayer
+from prototorch.core.transforms import LinearTransform
+from prototorch.nn.wrappers import LambdaLayer, LossLayer
+from torch.nn.parameter import Parameter
+
 from .abstract import ImagePrototypesMixin, SupervisedPrototypeModel
 from .extras import ltangent_distance, orthogonalization
 

prototorch/models/knn.py

@@ -2,13 +2,14 @@
 
 import warnings
 
-from ..core.competitions import KNNC
-from ..core.components import LabeledComponents
-from ..core.initializers import (
+from prototorch.core.competitions import KNNC
+from prototorch.core.components import LabeledComponents
+from prototorch.core.initializers import (
     LiteralCompInitializer,
     LiteralLabelsInitializer,
 )
-from ..utils.utils import parse_data_arg
+from prototorch.utils.utils import parse_data_arg
+
 from .abstract import SupervisedPrototypeModel
 
 

prototorch/models/lvq.py

@@ -1,8 +1,9 @@
 """LVQ models that are optimized using non-gradient methods."""
 
-from ..core.losses import _get_dp_dm
-from ..nn.activations import get_activation
-from ..nn.wrappers import LambdaLayer
+from prototorch.core.losses import _get_dp_dm
+from prototorch.nn.activations import get_activation
+from prototorch.nn.wrappers import LambdaLayer
+
 from .abstract import NonGradientMixin
 from .glvq import GLVQ
 

prototorch/models/probabilistic.py

@@ -1,10 +1,13 @@
 """Probabilistic GLVQ methods"""
 
 import torch
+from prototorch.core.losses import nllr_loss, rslvq_loss
+from prototorch.core.pooling import (
+    stratified_min_pooling,
+    stratified_sum_pooling,
+)
+from prototorch.nn.wrappers import LossLayer
 
-from ..core.losses import nllr_loss, rslvq_loss
-from ..core.pooling import stratified_min_pooling, stratified_sum_pooling
-from ..nn.wrappers import LambdaLayer, LossLayer
 from .extras import GaussianPrior, RankScaledGaussianPrior
 from .glvq import GLVQ, SiameseGMLVQ
 

prototorch/models/unsupervised.py

@@ -2,11 +2,10 @@
 
 import numpy as np
 import torch
+from prototorch.core.competitions import wtac
+from prototorch.core.distances import squared_euclidean_distance
+from prototorch.core.losses import NeuralGasEnergy
 
-from ..core.competitions import wtac
-from ..core.distances import squared_euclidean_distance
-from ..core.losses import NeuralGasEnergy
-from ..nn.wrappers import LambdaLayer
 from .abstract import NonGradientMixin, UnsupervisedPrototypeModel
 from .callbacks import GNGCallback
 from .extras import ConnectionTopology

prototorch/models/vis.py

@@ -5,11 +5,10 @@ import pytorch_lightning as pl
 import torch
 import torchvision
 from matplotlib import pyplot as plt
+from prototorch.utils.colors import get_colors, get_legend_handles
+from prototorch.utils.utils import mesh2d
 from torch.utils.data import DataLoader, Dataset
 
-from ..utils.colors import get_colors, get_legend_handles
-from ..utils.utils import mesh2d
-
 
 class Vis2DAbstract(pl.Callback):