From 3da537d096f9bcc3220a9d3ef48f9db7a2cf521a Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Sat, 1 Jul 2023 19:07:37 +0200
Subject: [PATCH] [data.dataset] Make function private
---
src/ptbench/data/dataset.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/src/ptbench/data/dataset.py b/src/ptbench/data/dataset.py
index c85fbcb3..af8a7364 100644
--- a/src/ptbench/data/dataset.py
+++ b/src/ptbench/data/dataset.py
@@ -10,7 +10,7 @@ import torch.utils.data
logger = logging.getLogger(__name__)
-def get_positive_weights(dataset):
+def _get_positive_weights(dataset):
"""Compute the positive weights of each class of the dataset to balance the
BCEWithLogitsLoss criterion.
@@ -84,7 +84,7 @@ def reweight_BCEWithLogitsLoss(datamodule, model, criterion, criterion_valid):
# Redefine a weighted criterion if possible
if isinstance(criterion, torch.nn.BCEWithLogitsLoss):
- positive_weights = get_positive_weights(train_dataset)
+ positive_weights = _get_positive_weights(train_dataset)
model.hparams.criterion = BCEWithLogitsLoss(pos_weight=positive_weights)
else:
logger.warning("Weighted criterion not supported")
@@ -95,7 +95,7 @@ def reweight_BCEWithLogitsLoss(datamodule, model, criterion, criterion_valid):
isinstance(criterion_valid, torch.nn.BCEWithLogitsLoss)
or criterion_valid is None
):
- positive_weights = get_positive_weights(validation_dataset)
+ positive_weights = _get_positive_weights(validation_dataset)
model.hparams.criterion_valid = BCEWithLogitsLoss(
pos_weight=positive_weights
)
--
GitLab