A Python script that tracks Pull Request activity for a specific user over a configurable time period using the PyGithub library.
- Tracks PRs where the user:
- Created the PR
- Added comments
- Submitted reviews
betatim
/ test_rf_with_max_calls.py
Last active
December 15, 2025 16:45
Investigate ray with max_calls=1 for cuml.accel
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| #!/usr/bin/env python3 | |
| """ | |
| Ray + RandomForestClassifier with max_calls=1 | |
| Demonstrates the impact of max_calls=1 on Ray task execution when using | |
| scikit-learn's RandomForestClassifier. | |
| """ | |
| import time | |
| import ray | |
| from sklearn.datasets import make_classification |
betatim
/ benchmark_rf_sklearn_vs_lightgbm.py
Last active
December 10, 2025 07:38
Comparing scikit-learn's random forest with lightgbm's implementation.
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| """ | |
| Benchmark: scikit-learn RandomForest vs LightGBM RandomForest | |
| Compares performance across: | |
| - Number of samples (1K, 10K, 100K, 500K) | |
| - Number of features (10, 50, 200) | |
| - Feature types (numerical, categorical, mixed) | |
| - Number of classes (2, 5, 10) | |
| Includes cases optimized for LightGBM's strengths: |
betatim
/ tabareana-20251202.yaml
Created
December 3, 2025 16:22
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| name: tabareana-20251202 | |
| channels: | |
| - conda-forge | |
| dependencies: | |
| - _libgcc_mutex=0.1=conda_forge | |
| - _openmp_mutex=4.5=2_gnu | |
| - bzip2=1.0.8=hda65f42_8 | |
| - ca-certificates=2025.11.12=hbd8a1cb_0 | |
| - cuda-cccl_linux-64=13.0.85=ha770c72_0 | |
| - cuda-cudart-dev_linux-64=13.0.96=h376f20c_0 |
betatim
/ quickstart.py
Created
December 3, 2025 08:25
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| from __future__ import annotations | |
| import warnings | |
| warnings.simplefilter("error", FutureWarning) | |
| from pathlib import Path | |
| from typing import Any | |
| import pandas as pd | |
| from tabarena.benchmark.experiment import AGModelBagExperiment, ExperimentBatchRunner |
betatim
/ AI_REVIEW_CHECKLIST.md
Created
October 14, 2025 07:21
Purpose: This checklist is optimized for AI assistants (like Cursor) to perform automated PR reviews. It separates automatable checks from those requiring human judgment, provides specific patterns to detect, and includes commands to run.
- Run all AUTOMATED checks first and report findings with severity levels
betatim
/ summary1.md
Created
August 28, 2025 11:47
-
Classification Metrics Sparse Support Bug (Issue #32036): A bug where classification metrics in scikit-learn claim sparse matrix support in docstrings but raise an error when used with sparse inputs. The issue is reliably reproducible with provided code steps, expected (support) vs. actual behavior (TypeError), and environment details in the traceback. No major missing elements. Link
-
RandomizedSearchCV Feature Request (Issue #32032): A proposal to add weights for controlling the probability of selecting items in a list of parameter distributions, useful for complex pipelines with interdependent hyperparameters. This is a feature enhancement, not a bug, and includes clear examples and rationale. Link
-
CI Failure on Linux Build (Issue #32022): Reported CI failure on a specific build configuration, with a reference to logs but no detailed steps to rep
betatim
/ log-test.py
Created
July 17, 2025 08:17
Associate log output with the (top level) line of a script. Makes it easier to know which log messages where output while a particular line was running. Try it with `python -m log_tracer -o traced_output.txt log-test.py`
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| import numpy as np | |
| import logging | |
| import time | |
| # Configure logging | |
| logging.basicConfig( | |
| level=logging.INFO, | |
| format='%(asctime)s - %(levelname)s - %(message)s', | |
| handlers=[ | |
| logging.FileHandler('calculations.log'), |
betatim
/ mem_usage.py
Created
June 12, 2025 13:53
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| import sklearn | |
| import numpy as np | |
| import torch | |
| sklearn.set_config(array_api_dispatch=True) | |
| def my_code(X, cdist=False): | |
| if cdist: | |
| dist = torch.cdist(X, X, p=2) |
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| [215/275] Linking CXX shared library libcuml++.so | |
| FAILED: libcuml++.so | |
| : && /datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/bin/x86_64-conda-linux-gnu-c++ -fPIC -fvisibility-inlines-hidden -fmessage-length=0 -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/include -I/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/include -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/lib -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/targets/x86_64-linux/lib/stubs -O3 -DNDEBUG -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,--disable-new-dtags -Wl,--gc-sections -Wl,--allow-shlib-undefined -Wl,-rpath,/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib -Wl,-rpath-link,/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib -L/datasets/thead/mambaforge/envs/cuml-dev-23.12-dgx15/lib -L/datasets/thead/mamb |
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