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authorGustaf Rydholm <gustaf.rydholm@gmail.com>2021-10-27 22:27:24 +0200
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2021-10-27 22:27:24 +0200
commit9a8044f4a3826a119416665741b709cd686fca87 (patch)
treee339593bb4e3858fa9379d14752dc52bf5949825 /text_recognizer/criterions
parentae8bfa62f0e02bd70c27bc1e71697249a5a79e7e (diff)
Remove Barlow Twins
Diffstat (limited to 'text_recognizer/criterions')
-rw-r--r--text_recognizer/criterions/barlow_twins.py26
1 files changed, 0 insertions, 26 deletions
diff --git a/text_recognizer/criterions/barlow_twins.py b/text_recognizer/criterions/barlow_twins.py
deleted file mode 100644
index fe30b22..0000000
--- a/text_recognizer/criterions/barlow_twins.py
+++ /dev/null
@@ -1,26 +0,0 @@
-"""Barlow twins loss function."""
-
-import torch
-from torch import nn, Tensor
-
-
-def off_diagonal(x: Tensor) -> Tensor:
- n, m = x.shape
- assert n == m
- return x.flatten()[:-1].view(n - 1, n + 1)[:, 1:].flatten()
-
-
-class BarlowTwinsLoss(nn.Module):
- def __init__(self, dim: int, lambda_: float) -> None:
- super().__init__()
- self.bn = nn.BatchNorm1d(dim, affine=False)
- self.lambda_ = lambda_
-
- def forward(self, z1: Tensor, z2: Tensor) -> Tensor:
- """Calculates the Barlow Twin loss."""
- c = self.bn(z1).T @ self.bn(z2)
- c.div_(z1.shape[0])
-
- on_diag = torch.diagonal(c).add_(-1).pow_(2).sum()
- off_diag = off_diagonal(c).pow_(2).sum()
- return on_diag + self.lambda_ * off_diag