Mask vs sequence #5565
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Mask vs sequence #5565
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tabergma
requested changes
Apr 2, 2020
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I haven't seen performance improvements F1-accuracy-wise (it's the same), and I wouldn't expect that because we're essentially doing the same thing. Would need to check memory / time! |
tabergma
approved these changes
Apr 3, 2020
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👍 Thanks for improving this!
Sorry, I meant performance = time/memory. F1 score should not change. Would be great is we could to a quick comparison time wise at least. I think we are fine, but we should make sure that we don't merge something that slows things down.
| @@ -1255,10 +1251,12 @@ def _create_sequence( | |||
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| def _create_all_labels(self) -> Tuple[tf.Tensor, tf.Tensor]: | |||
| all_label_ids = self.tf_label_data[LABEL_IDS][0] | |||
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| label_lengths = tf.cast(self.tf_label_data[LABEL_SEQ_LENGTH][0], dtype=tf.int32) | |||
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Should we add a helper method for this? Something like sequence_length_for? This logic is repeated all over the place.
tabergma
reviewed
Apr 3, 2020
| @@ -1352,13 +1350,19 @@ def _calculate_entity_loss( | |||
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| return loss, f1 | |||
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| def _compute_mask(self, sequence_lengths: tf.Tensor) -> tf.Tensor: | |||
tabergma
reviewed
Apr 3, 2020
Co-Authored-By: Tanja <tabergma@gmail.com>
…o mask-vs-sequence
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Timewise it is the same as the previous way of doing it. |
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