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vanderschaarlab / autoprognosis

A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
https://www.autoprognosis.vanderschaar-lab.com/
Apache License 2.0
95 stars 26 forks source link

Installation from source seems to require `torch` and `numpy` to be installed first (at least in some cases) #56

Open DrShushen opened 1 year ago

DrShushen commented 1 year ago

When running

cd autoprognosis
pip install .

installation initially failed due to lack of torch installed, then due to lack of numpy installed. Installing those via pip install first fixes the issue.

See full installation logs ```sh (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ pip install . Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.ngc.nvidia.com Processing /some_path/autoprognosis Installing build dependencies ... done Getting requirements to build wheel ... done Preparing metadata (pyproject.toml) ... done Collecting pyod Downloading pyod-1.0.7.tar.gz (147 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 147.7/147.7 kB 3.4 MB/s eta 0:00:00 Preparing metadata (setup.py) ... done Collecting torch>=1.10 Downloading torch-1.13.1-cp38-cp38-manylinux1_x86_64.whl (887.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 887.4/887.4 MB 8.5 MB/s eta 0:00:00 Collecting optuna>=1.4.0 Downloading optuna-3.0.5-py3-none-any.whl (348 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 348.5/348.5 kB 65.0 MB/s eta 0:00:00 Collecting hyperimpute Downloading hyperimpute-0.1.12-py3-none-any.whl (99 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 99.5/99.5 kB 360.4 MB/s eta 0:00:00 Collecting scipy>=1.3.2 Downloading scipy-1.9.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (33.8 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 33.8/33.8 MB 5.5 MB/s eta 0:00:00 Collecting matplotlib Downloading matplotlib-3.6.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (9.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.4/9.4 MB 47.4 MB/s eta 0:00:00 Collecting loguru Downloading loguru-0.6.0-py3-none-any.whl (58 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 58.3/58.3 kB 330.6 MB/s eta 0:00:00 Collecting joblib Downloading joblib-1.2.0-py3-none-any.whl (297 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 298.0/298.0 kB 69.4 MB/s eta 0:00:00 Collecting scikit-learn>=1.0 Downloading scikit_learn-1.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.7/9.7 MB 1.7 MB/s eta 0:00:00 Collecting seaborn Downloading seaborn-0.12.1-py3-none-any.whl (288 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 kB 213.7 MB/s eta 0:00:00 Collecting pandas>=1.3 Downloading pandas-1.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.2/12.2 MB 1.0 MB/s eta 0:00:00 Collecting lifelines Downloading lifelines-0.27.4-py3-none-any.whl (349 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 349.7/349.7 kB 273.2 MB/s eta 0:00:00 Collecting cloudpickle Downloading cloudpickle-2.2.0-py3-none-any.whl (25 kB) Collecting pydantic Downloading pydantic-1.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.2/3.2 MB 2.3 MB/s eta 0:00:00 Collecting redis Downloading redis-4.4.0-py3-none-any.whl (236 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 236.4/236.4 kB 418.5 MB/s eta 0:00:00 Collecting shap>=0.40.0 Downloading shap-0.41.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (575 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 575.9/575.9 kB 1.0 MB/s eta 0:00:00 Collecting numpy>=1.20 Downloading numpy-1.24.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 17.3/17.3 MB 1.4 MB/s eta 0:00:00 Collecting colorlog Downloading colorlog-6.7.0-py2.py3-none-any.whl (11 kB) Collecting sqlalchemy>=1.3.0 Downloading SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.6/1.6 MB 2.4 MB/s eta 0:00:00 Collecting cmaes>=0.8.2 Downloading cmaes-0.9.0-py3-none-any.whl (23 kB) Collecting cliff Downloading cliff-4.1.0-py3-none-any.whl (81 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 81.0/81.0 kB 9.8 MB/s eta 0:00:00 Collecting tqdm Downloading tqdm-4.64.1-py2.py3-none-any.whl (78 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 78.5/78.5 kB 12.1 MB/s eta 0:00:00 Requirement already satisfied: packaging>=20.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (22.0) Requirement already satisfied: PyYAML in /home/user/.local/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (6.0) Collecting scipy>=1.3.2 Downloading scipy-1.8.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 41.6/41.6 MB 5.0 MB/s eta 0:00:00 Requirement already satisfied: importlib-metadata<5.0.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (4.11.3) Collecting alembic>=1.5.0 Downloading alembic-1.9.1-py3-none-any.whl (210 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 210.4/210.4 kB 429.3 kB/s eta 0:00:00 Requirement already satisfied: python-dateutil>=2.8.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2.8.2) Requirement already satisfied: pytz>=2020.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2022.7) Collecting threadpoolctl>=2.0.0 Downloading threadpoolctl-3.1.0-py3-none-any.whl (14 kB) Collecting numba Downloading numba-0.56.4-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.5/3.5 MB 5.9 MB/s eta 0:00:00 Collecting slicer==0.0.7 Downloading slicer-0.0.7-py3-none-any.whl (14 kB) Collecting nvidia-cuda-runtime-cu11==11.7.99 Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 849.3/849.3 kB 36.7 MB/s eta 0:00:00 Requirement already satisfied: typing-extensions in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (4.4.0) Collecting nvidia-cublas-cu11==11.10.3.66 Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 317.1/317.1 MB 971.5 kB/s eta 0:00:00 Collecting nvidia-cudnn-cu11==8.5.0.96 Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 557.1/557.1 MB 10.0 MB/s eta 0:00:00 Collecting nvidia-cuda-nvrtc-cu11==11.7.99 Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.0/21.0 MB 2.6 MB/s eta 0:00:00 Requirement already satisfied: wheel in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (0.37.1) Requirement already satisfied: setuptools in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (65.5.0) Collecting xgboost>=1.6.1 Downloading xgboost-1.7.2-py3-none-manylinux2014_x86_64.whl (193.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 193.6/193.6 MB 47.5 MB/s eta 0:00:00 Collecting gpboost Downloading gpboost-0.8.0.1-py3-none-manylinux1_x86_64.whl (3.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.0/3.0 MB 1.1 MB/s eta 0:00:00 Collecting geomloss Downloading geomloss-0.2.5.tar.gz (26 kB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error × python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [10 lines of output] Traceback (most recent call last): File "", line 2, in File "", line 34, in File "/tmp/pip-install-x3ql65lp/geomloss_e98b1548ad7949c7b79cd9fce931bcc9/setup.py", line 14, in import geomloss File "/tmp/pip-install-x3ql65lp/geomloss_e98b1548ad7949c7b79cd9fce931bcc9/geomloss/__init__.py", line 5, in from .samples_loss import SamplesLoss File "/tmp/pip-install-x3ql65lp/geomloss_e98b1548ad7949c7b79cd9fce931bcc9/geomloss/samples_loss.py", line 1, in import torch ModuleNotFoundError: No module named 'torch' [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed × Encountered error while generating package metadata. ╰─> See above for output. note: This is an issue with the package mentioned above, not pip. hint: See above for details. (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ python Python 3.8.15 (default, Nov 24 2022, 15:19:38) [GCC 11.2.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> import torch Traceback (most recent call last): File "", line 1, in ModuleNotFoundError: No module named 'torch' >>> (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ pip install torch Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.ngc.nvidia.com Collecting torch Downloading torch-1.13.1-cp38-cp38-manylinux1_x86_64.whl (887.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 887.4/887.4 MB 55.8 MB/s eta 0:00:00 Requirement already satisfied: typing-extensions in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch) (4.4.0) Collecting nvidia-cuda-nvrtc-cu11==11.7.99 Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.0/21.0 MB 7.6 MB/s eta 0:00:00 Collecting nvidia-cudnn-cu11==8.5.0.96 Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 557.1/557.1 MB 67.1 MB/s eta 0:00:00 Collecting nvidia-cublas-cu11==11.10.3.66 Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 317.1/317.1 MB 63.9 MB/s eta 0:00:00 Collecting nvidia-cuda-runtime-cu11==11.7.99 Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 849.3/849.3 kB 163.0 MB/s eta 0:00:00 Requirement already satisfied: wheel in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (0.37.1) Requirement already satisfied: setuptools in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch) (65.5.0) Installing collected packages: nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cublas-cu11, nvidia-cudnn-cu11, torch Attempting uninstall: nvidia-cuda-runtime-cu11 Found existing installation: nvidia-cuda-runtime-cu11 11.8.89 Uninstalling nvidia-cuda-runtime-cu11-11.8.89: Successfully uninstalled nvidia-cuda-runtime-cu11-11.8.89 Attempting uninstall: nvidia-cublas-cu11 Found existing installation: nvidia-cublas-cu11 11.11.3.6 Uninstalling nvidia-cublas-cu11-11.11.3.6: Successfully uninstalled nvidia-cublas-cu11-11.11.3.6 Attempting uninstall: nvidia-cudnn-cu11 Found existing installation: nvidia-cudnn-cu11 8.6.0.163 Uninstalling nvidia-cudnn-cu11-8.6.0.163: Successfully uninstalled nvidia-cudnn-cu11-8.6.0.163 Successfully installed nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 torch-1.13.1 (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ pip install . Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.ngc.nvidia.com Processing /some_path/autoprognosis Installing build dependencies ... done Getting requirements to build wheel ... done Preparing metadata (pyproject.toml) ... done Collecting seaborn Downloading seaborn-0.12.1-py3-none-any.whl (288 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 kB 54.9 kB/s eta 0:00:00 Collecting loguru Downloading loguru-0.6.0-py3-none-any.whl (58 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 58.3/58.3 kB 321.4 MB/s eta 0:00:00 Collecting pydantic Downloading pydantic-1.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.2/3.2 MB 1.2 MB/s eta 0:00:00 Collecting redis Downloading redis-4.4.0-py3-none-any.whl (236 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 236.4/236.4 kB 2.7 MB/s eta 0:00:00 Collecting optuna>=1.4.0 Downloading optuna-3.0.5-py3-none-any.whl (348 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 348.5/348.5 kB 303.3 MB/s eta 0:00:00 Collecting cloudpickle Downloading cloudpickle-2.2.0-py3-none-any.whl (25 kB) Collecting lifelines Downloading lifelines-0.27.4-py3-none-any.whl (349 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 349.7/349.7 kB 2.5 MB/s eta 0:00:00 Collecting shap>=0.40.0 Downloading shap-0.41.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (575 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 575.9/575.9 kB 2.6 MB/s eta 0:00:00 Collecting joblib Downloading joblib-1.2.0-py3-none-any.whl (297 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 298.0/298.0 kB 263.6 kB/s eta 0:00:00 Collecting hyperimpute Downloading hyperimpute-0.1.12-py3-none-any.whl (99 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 99.5/99.5 kB 2.9 MB/s eta 0:00:00 Collecting pandas>=1.3 Downloading pandas-1.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.2/12.2 MB 1.1 MB/s eta 0:00:00 Requirement already satisfied: torch>=1.10 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from autoprognosis==0.1.14) (1.13.1) Collecting matplotlib Downloading matplotlib-3.6.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (9.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.4/9.4 MB 4.9 MB/s eta 0:00:00 Collecting numpy>=1.20 Downloading numpy-1.24.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 17.3/17.3 MB 1.6 MB/s eta 0:00:00 Collecting scikit-learn>=1.0 Downloading scikit_learn-1.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.7/9.7 MB 1.3 MB/s eta 0:00:00 Collecting scipy>=1.3.2 Downloading scipy-1.9.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (33.8 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 33.8/33.8 MB 38.3 MB/s eta 0:00:00 Collecting pyod Downloading pyod-1.0.7.tar.gz (147 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 147.7/147.7 kB 169.7 MB/s eta 0:00:00 Preparing metadata (setup.py) ... done Collecting cliff Downloading cliff-4.1.0-py3-none-any.whl (81 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 81.0/81.0 kB 66.3 MB/s eta 0:00:00 Collecting sqlalchemy>=1.3.0 Downloading SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.6/1.6 MB 162.7 MB/s eta 0:00:00 Collecting alembic>=1.5.0 Downloading alembic-1.9.1-py3-none-any.whl (210 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 210.4/210.4 kB 148.7 MB/s eta 0:00:00 Collecting scipy>=1.3.2 Downloading scipy-1.8.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 41.6/41.6 MB 2.1 MB/s eta 0:00:00 Collecting tqdm Downloading tqdm-4.64.1-py2.py3-none-any.whl (78 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 78.5/78.5 kB 146.2 kB/s eta 0:00:00 Collecting colorlog Downloading colorlog-6.7.0-py2.py3-none-any.whl (11 kB) Collecting cmaes>=0.8.2 Downloading cmaes-0.9.0-py3-none-any.whl (23 kB) Requirement already satisfied: importlib-metadata<5.0.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (4.11.3) Requirement already satisfied: packaging>=20.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (22.0) Requirement already satisfied: PyYAML in /home/user/.local/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (6.0) Requirement already satisfied: pytz>=2020.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2022.7) Requirement already satisfied: python-dateutil>=2.8.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2.8.2) Collecting threadpoolctl>=2.0.0 Downloading threadpoolctl-3.1.0-py3-none-any.whl (14 kB) Collecting numba Downloading numba-0.56.4-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.5/3.5 MB 22.0 MB/s eta 0:00:00 Collecting slicer==0.0.7 Downloading slicer-0.0.7-py3-none-any.whl (14 kB) Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.7.99) Requirement already satisfied: typing-extensions in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (4.4.0) Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (8.5.0.96) Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.10.3.66) Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.7.99) Requirement already satisfied: setuptools in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (65.5.0) Requirement already satisfied: wheel in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (0.37.1) Collecting catboost>=1.0.5 Downloading catboost-1.1.1-cp38-none-manylinux1_x86_64.whl (76.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 76.6/76.6 MB 60.6 MB/s eta 0:00:00 Collecting miracle-imputation>=0.1.3 Downloading miracle_imputation-0.1.5-py3-none-any.whl (15 kB) Collecting jupyter Downloading jupyter-1.0.0-py2.py3-none-any.whl (2.7 kB) Collecting geomloss Downloading geomloss-0.2.5.tar.gz (26 kB) Preparing metadata (setup.py) ... error error: subprocess-exited-with-error × python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> [12 lines of output] Traceback (most recent call last): File "", line 2, in File "", line 34, in File "/tmp/pip-install-mdmdyc9w/geomloss_893fc7852ae740dd8ac31412e774bc78/setup.py", line 14, in import geomloss File "/tmp/pip-install-mdmdyc9w/geomloss_893fc7852ae740dd8ac31412e774bc78/geomloss/__init__.py", line 5, in from .samples_loss import SamplesLoss File "/tmp/pip-install-mdmdyc9w/geomloss_893fc7852ae740dd8ac31412e774bc78/geomloss/samples_loss.py", line 6, in from .kernel_samples import kernel_tensorized, kernel_online, kernel_multiscale File "/tmp/pip-install-mdmdyc9w/geomloss_893fc7852ae740dd8ac31412e774bc78/geomloss/kernel_samples.py", line 22, in import numpy as np ModuleNotFoundError: No module named 'numpy' [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed × Encountered error while generating package metadata. ╰─> See above for output. note: This is an issue with the package mentioned above, not pip. hint: See above for details. (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ pip install numpy Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.ngc.nvidia.com Collecting numpy Downloading numpy-1.24.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 17.3/17.3 MB 11.7 MB/s eta 0:00:00 Installing collected packages: numpy ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. keras-applications 1.0.8 requires h5py, which is not installed. Successfully installed numpy-1.24.1 (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ pip install . Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com, https://pypi.ngc.nvidia.com Processing /some_path/autoprognosis Installing build dependencies ... done Getting requirements to build wheel ... done Preparing metadata (pyproject.toml) ... done Collecting seaborn Downloading seaborn-0.12.1-py3-none-any.whl (288 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 288.2/288.2 kB 164.5 kB/s eta 0:00:00 Collecting pandas>=1.3 Downloading pandas-1.5.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 12.2/12.2 MB 3.2 MB/s eta 0:00:00 Collecting matplotlib Downloading matplotlib-3.6.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (9.4 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.4/9.4 MB 1.8 MB/s eta 0:00:00 Collecting shap>=0.40.0 Downloading shap-0.41.0-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (575 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 575.9/575.9 kB 3.4 MB/s eta 0:00:00 Collecting cloudpickle Downloading cloudpickle-2.2.0-py3-none-any.whl (25 kB) Collecting redis Downloading redis-4.4.0-py3-none-any.whl (236 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 236.4/236.4 kB 414.3 MB/s eta 0:00:00 Collecting optuna>=1.4.0 Downloading optuna-3.0.5-py3-none-any.whl (348 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 348.5/348.5 kB 2.8 MB/s eta 0:00:00 Collecting lifelines Downloading lifelines-0.27.4-py3-none-any.whl (349 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 349.7/349.7 kB 91.4 MB/s eta 0:00:00 Collecting hyperimpute Downloading hyperimpute-0.1.12-py3-none-any.whl (99 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 99.5/99.5 kB 6.8 MB/s eta 0:00:00 Collecting pydantic Downloading pydantic-1.10.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.2/3.2 MB 4.4 MB/s eta 0:00:00 Requirement already satisfied: torch>=1.10 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from autoprognosis==0.1.14) (1.13.1) Collecting joblib Downloading joblib-1.2.0-py3-none-any.whl (297 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 298.0/298.0 kB 8.1 MB/s eta 0:00:00 Collecting loguru Downloading loguru-0.6.0-py3-none-any.whl (58 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 58.3/58.3 kB 20.1 MB/s eta 0:00:00 Collecting scipy>=1.3.2 Downloading scipy-1.9.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (33.8 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 33.8/33.8 MB 29.3 MB/s eta 0:00:00 Collecting scikit-learn>=1.0 Downloading scikit_learn-1.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.7/9.7 MB 13.4 MB/s eta 0:00:00 Requirement already satisfied: numpy>=1.20 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from autoprognosis==0.1.14) (1.24.1) Collecting pyod Downloading pyod-1.0.7.tar.gz (147 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 147.7/147.7 kB 131.2 MB/s eta 0:00:00 Preparing metadata (setup.py) ... done Collecting colorlog Downloading colorlog-6.7.0-py2.py3-none-any.whl (11 kB) Collecting tqdm Downloading tqdm-4.64.1-py2.py3-none-any.whl (78 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 78.5/78.5 kB 370.5 MB/s eta 0:00:00 Requirement already satisfied: importlib-metadata<5.0.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (4.11.3) Collecting cliff Downloading cliff-4.1.0-py3-none-any.whl (81 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 81.0/81.0 kB 348.2 MB/s eta 0:00:00 Requirement already satisfied: packaging>=20.0 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (22.0) Requirement already satisfied: PyYAML in /home/user/.local/lib/python3.8/site-packages (from optuna>=1.4.0->autoprognosis==0.1.14) (6.0) Collecting scipy>=1.3.2 Downloading scipy-1.8.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (41.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 41.6/41.6 MB 5.9 MB/s eta 0:00:00 Collecting sqlalchemy>=1.3.0 Downloading SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.6/1.6 MB 8.2 MB/s eta 0:00:00 Collecting alembic>=1.5.0 Downloading alembic-1.9.1-py3-none-any.whl (210 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 210.4/210.4 kB 21.5 MB/s eta 0:00:00 Collecting cmaes>=0.8.2 Downloading cmaes-0.9.0-py3-none-any.whl (23 kB) Requirement already satisfied: python-dateutil>=2.8.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2.8.2) Requirement already satisfied: pytz>=2020.1 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pandas>=1.3->autoprognosis==0.1.14) (2022.7) Collecting threadpoolctl>=2.0.0 Downloading threadpoolctl-3.1.0-py3-none-any.whl (14 kB) Collecting slicer==0.0.7 Downloading slicer-0.0.7-py3-none-any.whl (14 kB) Collecting numba Downloading numba-0.56.4-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (3.5 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.5/3.5 MB 2.7 MB/s eta 0:00:00 Requirement already satisfied: typing-extensions in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (4.4.0) Requirement already satisfied: nvidia-cudnn-cu11==8.5.0.96 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (8.5.0.96) Requirement already satisfied: nvidia-cuda-nvrtc-cu11==11.7.99 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.7.99) Requirement already satisfied: nvidia-cuda-runtime-cu11==11.7.99 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.7.99) Requirement already satisfied: nvidia-cublas-cu11==11.10.3.66 in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from torch>=1.10->autoprognosis==0.1.14) (11.10.3.66) Requirement already satisfied: wheel in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (0.37.1) Requirement already satisfied: setuptools in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from nvidia-cublas-cu11==11.10.3.66->torch>=1.10->autoprognosis==0.1.14) (65.5.0) Collecting lightgbm Downloading lightgbm-3.3.3-py3-none-manylinux1_x86_64.whl (2.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2.0/2.0 MB 2.8 MB/s eta 0:00:00 Collecting gpboost Downloading gpboost-0.8.0.1-py3-none-manylinux1_x86_64.whl (3.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.0/3.0 MB 2.8 MB/s eta 0:00:00 Collecting jupyter Downloading jupyter-1.0.0-py2.py3-none-any.whl (2.7 kB) Collecting xgboost>=1.6.1 Downloading xgboost-1.7.2-py3-none-manylinux2014_x86_64.whl (193.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 193.6/193.6 MB 2.2 MB/s eta 0:00:00 Collecting catboost>=1.0.5 Downloading catboost-1.1.1-cp38-none-manylinux1_x86_64.whl (76.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 76.6/76.6 MB 58.9 MB/s eta 0:00:00 Collecting geomloss Downloading geomloss-0.2.5.tar.gz (26 kB) Preparing metadata (setup.py) ... done Collecting miracle-imputation>=0.1.3 Downloading miracle_imputation-0.1.5-py3-none-any.whl (15 kB) Requirement already satisfied: notebook in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from hyperimpute->autoprognosis==0.1.14) (6.5.2) Collecting autograd>=1.5 Downloading autograd-1.5-py3-none-any.whl (48 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 48.9/48.9 kB 310.5 MB/s eta 0:00:00 Collecting autograd-gamma>=0.3 Downloading autograd-gamma-0.5.0.tar.gz (4.0 kB) Preparing metadata (setup.py) ... done Collecting formulaic>=0.2.2 Downloading formulaic-0.5.2-py3-none-any.whl (77 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 77.1/77.1 kB 33.3 MB/s eta 0:00:00 Collecting cycler>=0.10 Downloading cycler-0.11.0-py3-none-any.whl (6.4 kB) Collecting pillow>=6.2.0 Downloading Pillow-9.3.0-cp38-cp38-manylinux_2_28_x86_64.whl (3.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.3/3.3 MB 7.6 MB/s eta 0:00:00 Collecting pyparsing>=2.2.1 Downloading pyparsing-3.0.9-py3-none-any.whl (98 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 98.3/98.3 kB 365.3 MB/s eta 0:00:00 Collecting fonttools>=4.22.0 Downloading fonttools-4.38.0-py3-none-any.whl (965 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 965.4/965.4 kB 141.2 MB/s eta 0:00:00 Collecting contourpy>=1.0.1 Downloading contourpy-1.0.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (295 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 296.0/296.0 kB 3.1 MB/s eta 0:00:00 Collecting kiwisolver>=1.0.1 Downloading kiwisolver-1.4.4-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 68.2 MB/s eta 0:00:00 Requirement already satisfied: six in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from pyod->autoprognosis==0.1.14) (1.16.0) Collecting statsmodels Downloading statsmodels-0.13.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (9.9 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.9/9.9 MB 1.5 MB/s eta 0:00:00 Collecting async-timeout>=4.0.2 Downloading async_timeout-4.0.2-py3-none-any.whl (5.8 kB) Requirement already satisfied: importlib-resources in /mnt/data-linux/miniconda3/envs/playaround_py38_autoprognosis/lib/python3.8/site-packages (from 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/tmp/pip-ephem-wheel-cache-d1glssxw/wheels/01/49/0c/4e0a697824c7bd6516afb22e1af9d51427ccd36c74b05a297e Building wheel for pyperclip (setup.py) ... done Created wheel for pyperclip: filename=pyperclip-1.8.2-py3-none-any.whl size=11123 sha256=fe59d584782dd723e4dcd2e28121a20f5b38a1df66a8c455ad1062099e6f5dcc Stored in directory: /tmp/pip-ephem-wheel-cache-d1glssxw/wheels/e9/08/ff/ce302129d1f57e10fd08d8a476ae601dedba9d08d47fe6be45 Successfully built autoprognosis pyod autograd-gamma geomloss future pyperclip Installing collected packages: tensorboard-plugin-wit, pyperclip, pyasn1, libclang, flatbuffers, widgetsnbextension, werkzeug, tqdm, threadpoolctl, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-se rver, tenacity, slicer, rsa, qtpy, pyparsing, pydantic, pyasn1-modules, protobuf, PrettyTable, pillow, pbr, oauthlib, numpy, Mako, loguru, llvmlite, kiwisolver, keras, jupyterlab-widgets, joblib, interface-meta, grpcio, greenlet, graphviz, graphlib-backport, gast, future, fonttools, cycler, colorlog, cmd2, cloudpickle, cachetools, autopage, async-timeout, absl-py, stevedore, sqlalchemy, scipy, requests-oauthlib, redis, plotly, patsy, pandas, numba, markdow n, h5py, google-auth, geomloss, contourpy, cmaes, autograd, xgboost, statsmodels, scikit-learn, matplotlib, google-auth-oauthlib, formulaic, cliff, autograd-gamma, alembic, tensorboard, shap, seaborn, pyod, optuna, lightgbm, lifel ines, gpboost, catboost, tensorflow, qtconsole, jupyter-console, ipywidgets, miracle-imputation, jupyter, hyperimpute, autoprognosis Attempting uninstall: numpy Found existing installation: numpy 1.24.1 Uninstalling numpy-1.24.1: Successfully uninstalled numpy-1.24.1 Successfully installed Mako-1.2.4 PrettyTable-3.5.0 absl-py-1.3.0 alembic-1.9.1 async-timeout-4.0.2 autograd-1.5 autograd-gamma-0.5.0 autopage-0.5.1 autoprognosis-0.1.14 cachetools-5.2.0 catboost-1.1.1 cliff-4.1.0 cloudpickle-2.2. 0 cmaes-0.9.0 cmd2-2.4.2 colorlog-6.7.0 contourpy-1.0.6 cycler-0.11.0 flatbuffers-22.12.6 fonttools-4.38.0 formulaic-0.5.2 future-0.18.2 gast-0.4.0 geomloss-0.2.5 google-auth-2.15.0 google-auth-oauthlib-0.4.6 gpboost-0.8.0.1 graph lib-backport-1.0.3 graphviz-0.20.1 greenlet-2.0.1 grpcio-1.51.1 h5py-3.7.0 hyperimpute-0.1.12 interface-meta-1.3.0 ipywidgets-8.0.4 joblib-1.2.0 jupyter-1.0.0 jupyter-console-6.4.4 jupyterlab-widgets-3.0.5 keras-2.11.0 kiwisolver- 1.4.4 libclang-14.0.6 lifelines-0.27.4 lightgbm-3.3.3 llvmlite-0.39.1 loguru-0.6.0 markdown-3.4.1 matplotlib-3.6.2 miracle-imputation-0.1.5 numba-0.56.4 numpy-1.23.5 oauthlib-3.2.2 optuna-3.0.5 pandas-1.5.2 patsy-0.5.3 pbr-5.11.0 pillow-9.3.0 plotly-5.11.0 protobuf-3.19.6 pyasn1-0.4.8 pyasn1-modules-0.2.8 pydantic-1.10.3 pyod-1.0.7 pyparsing-3.0.9 pyperclip-1.8.2 qtconsole-5.4.0 qtpy-2.3.0 redis-4.4.0 requests-oauthlib-1.3.1 rsa-4.9 scikit-learn-1.2.0 scip y-1.8.1 seaborn-0.12.1 shap-0.41.0 slicer-0.0.7 sqlalchemy-1.4.45 statsmodels-0.13.5 stevedore-4.1.1 tenacity-8.1.0 tensorboard-2.11.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.11.0 tensorflow-estimat or-2.11.0 tensorflow-io-gcs-filesystem-0.29.0 termcolor-2.1.1 threadpoolctl-3.1.0 tqdm-4.64.1 werkzeug-2.2.2 widgetsnbextension-4.0.5 xgboost-1.7.2 (playaround_py38_autoprognosis) user@computer:/some_path/autoprognosis$ clear ```
bcebere commented 1 year ago

Thank you for the feedback!

It is a known issue for new environments. The workaround in the CI workflows is to preinstall those from the prereq.txt file.

The problem is from the geomloss package, used by hyperimpute, which requires torch and numpy in its setup.py file. The solution is here, still pending the merge and release.

If they won't create a release with the fix soon, I will fork and patch the library directly in hyperimpute.