feat: data
argument optional in some visualizers
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ce14dec7e9
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@ -14,7 +14,7 @@ from ..utils.utils import mesh2d
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class Vis2DAbstract(pl.Callback):
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def __init__(self,
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data,
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data=None,
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title="Prototype Visualization",
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cmap="viridis",
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xlabel="Data dimension 1",
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@ -32,6 +32,7 @@ class Vis2DAbstract(pl.Callback):
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block=False):
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super().__init__()
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if data:
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if isinstance(data, Dataset):
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x, y = next(iter(DataLoader(data, batch_size=len(data))))
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elif isinstance(data, torch.utils.data.DataLoader):
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@ -48,6 +49,9 @@ class Vis2DAbstract(pl.Callback):
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self.x_train = x
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self.y_train = y
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else:
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self.x_train = None
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self.y_train = None
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self.title = title
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self.xlabel = xlabel
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@ -136,10 +140,13 @@ class VisGLVQ2D(Vis2DAbstract):
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plabels = pl_module.prototype_labels
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x_train, y_train = self.x_train, self.y_train
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ax = self.setup_ax()
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self.plot_data(ax, x_train, y_train)
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self.plot_protos(ax, protos, plabels)
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x = np.vstack((x_train, protos))
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mesh_input, xx, yy = mesh2d(x, self.border, self.resolution)
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if x_train is not None:
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self.plot_data(ax, x_train, y_train)
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mesh_input, xx, yy = mesh2d(np.vstack([x_train, protos]),
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self.border, self.resolution)
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else:
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mesh_input, xx, yy = mesh2d(protos, self.border, self.resolution)
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_components = pl_module.proto_layer._components
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mesh_input = torch.from_numpy(mesh_input).type_as(_components)
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y_pred = pl_module.predict(mesh_input)
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