91 lines
2.3 KiB
Python
91 lines
2.3 KiB
Python
"""prototorch.models.extras
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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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def rank_scaled_gaussian(distances, lambd):
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order = torch.argsort(distances, dim=1)
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ranks = torch.argsort(order, dim=1)
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return torch.exp(-torch.exp(-ranks / lambd) * distances)
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class GaussianPrior(torch.nn.Module):
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def __init__(self, variance):
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super().__init__()
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self.variance = variance
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def forward(self, distances):
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return gaussian(distances, self.variance)
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class RankScaledGaussianPrior(torch.nn.Module):
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def __init__(self, lambd):
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super().__init__()
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self.lambd = lambd
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def forward(self, distances):
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return rank_scaled_gaussian(distances, self.lambd)
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class ConnectionTopology(torch.nn.Module):
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def __init__(self, agelimit, num_prototypes):
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super().__init__()
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self.agelimit = agelimit
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self.num_prototypes = num_prototypes
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self.cmat = torch.zeros((self.num_prototypes, self.num_prototypes))
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self.age = torch.zeros_like(self.cmat)
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def forward(self, d):
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order = torch.argsort(d, dim=1)
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for element in order:
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i0, i1 = element[0], element[1]
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self.cmat[i0][i1] = 1
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self.cmat[i1][i0] = 1
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self.age[i0][i1] = 0
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self.age[i1][i0] = 0
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self.age[i0][self.cmat[i0] == 1] += 1
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self.age[i1][self.cmat[i1] == 1] += 1
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self.cmat[i0][self.age[i0] > self.agelimit] = 0
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self.cmat[i1][self.age[i1] > self.agelimit] = 0
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def get_neighbors(self, position):
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return torch.where(self.cmat[position])
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def add_prototype(self):
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new_cmat = torch.zeros([dim + 1 for dim in self.cmat.shape])
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new_cmat[:-1, :-1] = self.cmat
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self.cmat = new_cmat
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new_age = torch.zeros([dim + 1 for dim in self.age.shape])
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new_age[:-1, :-1] = self.age
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self.age = new_age
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def add_connection(self, a, b):
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self.cmat[a][b] = 1
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self.cmat[b][a] = 1
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self.age[a][b] = 0
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self.age[b][a] = 0
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def remove_connection(self, a, b):
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self.cmat[a][b] = 0
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self.cmat[b][a] = 0
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self.age[a][b] = 0
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self.age[b][a] = 0
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def extra_repr(self):
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return f"(agelimit): ({self.agelimit})"
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