TPS-free 2D bucket estimation and filtering #11738
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Signed-off-by: Piotr Żelasko <[email protected]>
Signed-off-by: Piotr Żelasko <[email protected]>
![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
| @@ -15,9 +15,11 @@ | |||
| import bisect | |||
| import logging | |||
| import math | |||
| from bisect import bisect_left, bisect_right | |||
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Unused import Note
Signed-off-by: Piotr Żelasko <[email protected]>
| from lhotse.testing.dummies import DummyManifest, dummy_cut | ||
| from nemo.collections.common.data.lhotse.sampling import FixedBucketBatchSizeConstraint2D | ||
| from lhotse.testing.dummies import dummy_cut | ||
| from lhotse.testing.random import deterministic_rng |
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Unused import Note test
Signed-off-by: Piotr Żelasko <[email protected]>
Signed-off-by: pzelasko <[email protected]>
Signed-off-by: Piotr Żelasko <[email protected]>
…com/nvidia/nemo into 2d-bucketing-and-tps-improvements-2
| filter_2d = BucketingFilter(constraint) | ||
| cut = make_cut(duration=2.0, num_tokens=20) | ||
| assert filter_2d(cut) == False | ||
| assert constraint.select_bucket(constraint.max_seq_len_buckets, cut) == None |
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Testing equality to None Note test
Signed-off-by: Piotr Żelasko <[email protected]>
Signed-off-by: Piotr Żelasko <[email protected]>
Signed-off-by: Piotr Żelasko <[email protected]>
nithinraok
reviewed
Jan 10, 2025
| @@ -698,28 +709,32 @@ def make_structured_with_schema_warnings(config: DictConfig | dict) -> DictConfi | |||
| if not isinstance(config, DictConfig): | |||
| config = DictConfig(config) | |||
|
|
|||
| if config.get("tarred_random_access", False): | |||
| logging.warning( | |||
| "Option 'tarred_random_access' is deprecated and replaced with 'skip_missing_manifest_entries'.", | |||
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may be also add version from which this would be removed
nithinraok
previously approved these changes
Jan 10, 2025
Signed-off-by: Piotr Zelasko <[email protected]>
Signed-off-by: Piotr Żelasko <[email protected]>
|
beep boop 🤖: 🚨 The following files must be fixed before merge! Your code was analyzed with PyLint. The following annotations have been identified: Mitigation guide:
By applying these rules, we reduce the occurance of this message in future. Thank you for improving NeMo's documentation! |
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beep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base. Your code was analyzed with PyLint. The following annotations have been identified: Mitigation guide:
By applying these rules, we reduce the occurance of this message in future. Thank you for improving NeMo's documentation! |
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What does this PR do ?
Improves the UX of estimating 2D buckets and preparing the training configuration. Key changes:
model.train_ds.bucketing_2d_strict_mode=False): find any bucket that will fit a given example. That means token-per-second outliers are pushed to buckets with higher durations increasing the padding but reducing the amount of discarded data. Use at your own risk - for the setups I tested it so far with, it may cause training instability (likely due to inclusion of lower-quality data).estimate_duration_bins_2d.pyscript.estimate_duration_bins_2d.py.tarred_random_accesstoskip_missing_manifest_entriesand adjusted the logic to reduce CPU memory usage and accelerate loading time.Collection: ASR, TTS, SpeechLLM
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