deepvats / docker /environment.yml
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name: dvats_env
channels:
#--- Torch & Cuda
- pytorch
#- nvidia/label/cuda-12.2.0
- nvidia
#--- Generic
- conda-forge
- defaults
#--- AI
- fastai
- rapidsai
- defaults
- conda-forge
- timeseriesai
dependencies:
##########################
# Generic configurations #
##########################
- nano=7.2=h8228510_0
- git=2.42.0=pl5321h86e50cf_0
#--- github
- gh=2.37.0=ha8f183a_0
#--- Python
- python=3.10.13=hd12c33a_0_cpython
#WANDB <= 0.15.12 needs this version. See https://github.com/wandb/wandb/issues/6546
- ipython=8.16.1=pyh0d859eb_0
- pip=23.3.1=pyhd8ed1ab_0
- conda-forge::twine=4.0.2=pyhd8ed1ab_0
- conda-forge::xeus-python=0.15.10=py310hd41b1e2_1
#--- NodeJS
- conda-forge::nodejs=20.8.1=h1990674_0
#---Jupyter
- conda-forge::ipywidgets=8.1.1=pyhd8ed1ab_0
- conda-forge::jupyterlab=4.0.7=pyhd8ed1ab_0
- conda-forge::jupyterlab-git=0.41.0=pyhd8ed1ab_1
- conda-forge::nbclassic=1.0.0=pyhb4ecaf3_1
- conda-forge::nbdev=2.2.10=pyhd8ed1ab_0
- nbformat>=5.1.3
#--- passwords & files
- keyrings.alt
- platformdirs=2.5.2
- conda-forge::keyrings.alt=4.2.0=pyhd8ed1ab_0
- psutil>=5.4.8
##############
# CUDA & GPU #
##############
- nvidia::cuda-toolkit=11.6=0
- rapidsai::cudf=23.02=cuda_11_py310_g5ad4a85b9d_0
- rapidsai::cuml=23.02=cuda11_py310_g3356f05bd_0
- conda-forge::genv=1.2.0=pyhd8ed1ab_0
############
# Specific #
############
#--- Torch
- pytorch=1.13=py3.10_cuda11.7_cudnn8.5.0_0
#---Graphs & imgs
- conda-forge::plotly=5.18.0=pyhd8ed1ab_0
- conda-forge::jpeg=9e=h166bdaf_2
- conda-forge::seaborn=0.13.0=hd8ed1ab_0
- conda-forge::matplotlib=3.8.1=py310hff52083_0
#--- IA
- conda-forge::hdbscan=0.8.33=py310h1f7b6fc_4
- conda-forge::imbalanced-learn>= 0.8.0
- conda-forge::pyts >= 0.12.0
- conda-forge::umap-learn=0.5.4=py310hff52083_0
- conda-forge::scikit-learn=1.2.2=py310hf7d194e_2
- conda-forge::wandb=0.14.2=pyhd8ed1ab_0
- fastai::fastai>=2.7.9
- timeseriesai::tsai
- conda-forge::feather-format