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| def cross_entropy(self, scaled_logits, one_hot): | |
| if self.library == "tf": | |
| masked_logits = tf.boolean_mask(scaled_logits, one_hot) | |
| ce = -tf.math.log(masked_logits) | |
| else: | |
| masked_logits = torch.masked_select(scaled_logits, one_hot) | |
| ce = -torch.log(masked_logits) | |
| return ce |
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