diff options
author | aktersnurra <gustaf.rydholm@gmail.com> | 2020-09-20 00:14:27 +0200 |
---|---|---|
committer | aktersnurra <gustaf.rydholm@gmail.com> | 2020-09-20 00:14:27 +0200 |
commit | e181195a699d7fa237f256d90ab4dedffc03d405 (patch) | |
tree | 6d8d50731a7267c56f7bf3ed5ecec3990c0e55a5 /src/text_recognizer/networks/losses.py | |
parent | 3b06ef615a8db67a03927576e0c12fbfb2501f5f (diff) |
Minor bug fixes etc.
Diffstat (limited to 'src/text_recognizer/networks/losses.py')
-rw-r--r-- | src/text_recognizer/networks/losses.py | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/src/text_recognizer/networks/losses.py b/src/text_recognizer/networks/losses.py new file mode 100644 index 0000000..73e0641 --- /dev/null +++ b/src/text_recognizer/networks/losses.py @@ -0,0 +1,31 @@ +"""Implementations of custom loss functions.""" +from pytorch_metric_learning import distances, losses, miners, reducers +from torch import nn +from torch import Tensor + + +class EmbeddingLoss: + """Metric loss for training encoders to produce information-rich latent embeddings.""" + + def __init__(self, margin: float = 0.2, type_of_triplets: str = "semihard") -> None: + self.distance = distances.CosineSimilarity() + self.reducer = reducers.ThresholdReducer(low=0) + self.loss_fn = losses.TripletMarginLoss( + margin=margin, distance=self.distance, reducer=self.reducer + ) + self.miner = miners.MultiSimilarityMiner(epsilon=margin, distance=self.distance) + + def __call__(self, embeddings: Tensor, labels: Tensor) -> Tensor: + """Computes the metric loss for the embeddings based on their labels. + + Args: + embeddings (Tensor): The laten vectors encoded by the network. + labels (Tensor): Labels of the embeddings. + + Returns: + Tensor: The metric loss for the embeddings. + + """ + hard_pairs = self.miner(embeddings, labels) + loss = self.loss_fn(embeddings, labels, hard_pairs) + return loss |