domainbed/algorithms.py [1505:1515]:
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        ib_penalty = 0.

        all_x = torch.cat([x for x,y in minibatches])
        all_features = self.featurizer(all_x)
        all_logits = self.classifier(all_features)
        all_logits_idx = 0
        for i, (x, y) in enumerate(minibatches):
            features = all_features[all_logits_idx:all_logits_idx + x.shape[0]]
            logits = all_logits[all_logits_idx:all_logits_idx + x.shape[0]]
            all_logits_idx += x.shape[0]
            nll += F.cross_entropy(logits, y)
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domainbed/algorithms.py [1577:1587]:
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        ib_penalty = 0.

        all_x = torch.cat([x for x,y in minibatches])
        all_features = self.featurizer(all_x)
        all_logits = self.classifier(all_features)
        all_logits_idx = 0
        for i, (x, y) in enumerate(minibatches):
            features = all_features[all_logits_idx:all_logits_idx + x.shape[0]]
            logits = all_logits[all_logits_idx:all_logits_idx + x.shape[0]]
            all_logits_idx += x.shape[0]
            nll += F.cross_entropy(logits, y)
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