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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
| 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'), |
| 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) |
| [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 |
| conda-forge/osx-arm64 Using cache | |
| conda-forge/noarch Using cache | |
| Looking for: ['python=3.9', 'numpy=1.19.5', 'blas', 'scipy=1.6.0', 'cython=3.0.10', 'joblib', 'threadpoolctl', 'matplotlib=3.3.4', 'pandas=1.1.5', 'pyamg', "pytest[version='<8']", 'pytest-xdist', 'pillow', 'pip', 'ninja', 'meson-python', 'scikit-image=0.17.2', 'seaborn', 'memory_profiler', 'compilers', 'sphinx=6.0.0', 'sphinx-gallery=0.15.0', 'sphinx-copybutton=0.5.2', 'numpydoc=1.2.0', 'sphinx-prompt=1.3.0', 'plotly=5.14.0', 'polars=0.19.12', 'pooch', 'pip'] | |
| Could not solve for environment specs | |
| The following packages are incompatible | |
| ├─ numpy 1.19.5** is installable with the potential options |
Checkout https://github.com/rapidsai/gpu-xb-ai:
git clone https://github.com/rapidsai/gpu-xb-ai
Create a conda environment from conda/environments/gpu-xb-ai-legate-all.yaml:
conda env create -f conda/environments/gpu-xb-ai-legate-all.yaml
| ==================================================================================== short test summary info ==================================================================================== | |
| FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-None-cupy.array_api-None-None] - ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() | |
| FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-stratify1-cupy-None-None] - ValueError: kind can only be None or 'stable' | |
| FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[True-stratify1-cupy.array_api-None-None] - ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2. | |
| FAILED sklearn/model_selection/tests/test_split.py::test_array_api_train_test_split[False-None-cupy.array_api-None-None] - ValueError: The truth value of an array with |
| from dask_mpi import initialize | |
| from dask import distributed | |
| def dask_info(): | |
| distributed.print("woah i'm running!") | |
| distributed.print("ncores:", client.ncores()) | |
| distributed.print() | |
| distributed.print(client.scheduler_info()) |
| # packages in environment at /opt/conda/envs/rapids-23.06: | |
| # | |
| # Name Version Build Channel | |
| _libgcc_mutex 0.1 conda_forge conda-forge | |
| _openmp_mutex 4.5 2_gnu conda-forge | |
| aiohttp 3.8.5 py310h2372a71_0 conda-forge | |
| aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge | |
| anyio 3.7.1 pyhd8ed1ab_0 conda-forge | |
| aom 3.5.0 h27087fc_0 conda-forge | |
| appdirs 1.4.4 pyh9f0ad1d_0 conda-forge |