Optimize internal clip_noise_rates and remove_noise_from_class functions

[gogetron]

Summary

This PR partially addresses #862

🎯 Purpose: Improve performance of internal clip_noise_rates and remove_noise_from_class functions.

[ ✏️ Write your summary here. ]
The significant improvement comes from using numpy operations where possible.

For memory I used the memory-profiler library. The code I used for benchmarking is copied below. In addition I sorted the imports in the modified files.

Code Setup

import numpy as np

from cleanlab.internal.util import clip_noise_rates, remove_noise_from_class

np.random.seed(0)

K = 5_000
x = np.random.random((K, K))

Current version

%%timeit
%memit clip_noise_rates(x)
# peak memory: 1779.00 MiB, increment: 1308.72 MiB
# peak memory: 1779.38 MiB, increment: 1335.93 MiB
# peak memory: 1755.99 MiB, increment: 1311.49 MiB
# peak memory: 1779.37 MiB, increment: 1333.59 MiB
# peak memory: 1779.60 MiB, increment: 1333.10 MiB
# peak memory: 1779.62 MiB, increment: 1331.66 MiB
# peak memory: 1776.17 MiB, increment: 1327.21 MiB
# peak memory: 1779.68 MiB, increment: 1330.00 MiB
# 4.07 s ± 32.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%%timeit
%memit remove_noise_from_class(x, 1)
# peak memory: 635.38 MiB, increment: 171.43 MiB
# peak memory: 635.41 MiB, increment: 190.74 MiB
# peak memory: 635.41 MiB, increment: 190.74 MiB
# peak memory: 635.61 MiB, increment: 190.93 MiB
# peak memory: 635.61 MiB, increment: 190.74 MiB
# peak memory: 635.61 MiB, increment: 190.74 MiB
# peak memory: 635.61 MiB, increment: 190.74 MiB
# peak memory: 635.61 MiB, increment: 190.74 MiB
# 354 ms ± 3.67 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

This PR

%%timeit
%memit clip_noise_rates(x)
# peak memory: 817.28 MiB, increment: 332.71 MiB
# peak memory: 454.48 MiB, increment: 0.00 MiB
# peak memory: 454.48 MiB, increment: 0.00 MiB
# peak memory: 454.68 MiB, increment: 0.00 MiB
# peak memory: 793.55 MiB, increment: 338.88 MiB
# peak memory: 454.68 MiB, increment: 0.00 MiB
# peak memory: 454.68 MiB, increment: 0.00 MiB
# peak memory: 454.68 MiB, increment: 0.00 MiB
# 255 ms ± 11.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

%%timeit
%memit remove_noise_from_class(x, 1)
# peak memory: 459.73 MiB, increment: 0.00 MiB
# peak memory: 443.90 MiB, increment: 0.06 MiB
# peak memory: 443.90 MiB, increment: 0.00 MiB
# peak memory: 444.15 MiB, increment: 0.00 MiB
# peak memory: 444.15 MiB, increment: 0.00 MiB
# peak memory: 444.15 MiB, increment: 0.00 MiB
# peak memory: 444.15 MiB, increment: 0.00 MiB
# peak memory: 444.15 MiB, increment: 0.00 MiB
# 204 ms ± 1.33 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

Testing

🔍 Testing Done: Existing test suite and I also verified that the outputs were the same after refactoring.

References

Reviewer Notes

💡 Include any specific points for the reviewer to consider during their review.