host = github

lib_name = tsai

repo = tsai

user = timeseriesAI

branch = main

version = 0.3.10

description = Practical Deep Learning for Time Series / Sequential Data library based on fastai & Pytorch

keywords = fastai time-series time-series-classification time-series-regression deep-learning Pytorch

author = Ignacio Oguiza and contributors

author_email = [email protected]

copyright = Ignacio Oguiza

license = apache2

status = 4

min_python = 3.8

audience = Developers

language = English

requirements = fastai>=2.7.14 pyts>=0.12.0 imbalanced-learn>=0.11.0 psutil>=5.4.8 scikit-learn>=1.2

pip_requirements = torch>=1.10,<2.3

conda_user = timeseriesAI

conda_requirements = pytorch>=1.10,<2.3

extra_requirements = sktime>=0.10.1 tsfresh>=0.18.0 PyWavelets>=1.1.1 nbformat>=5.1.3

dev_requirements = nbdev>2 ipykernel>6

console_scripts = nb2py=tsai.export:nb2py

nbs_path = nbs

doc_path = _docs

doc_host = https://timeseriesAI.github.io/tsai

doc_baseurl = /

git_url = https://github.com/timeseriesAI/tsai/

lib_path = tsai

title = tsai

tst_flags = local slow extras onnx

custom_sidebar = True

recursive = True

clean_ids = True

black_formatting = False

readme_nb = index.ipynb

allowed_metadata_keys =

allowed_cell_metadata_keys =

jupyter_hooks = True

clear_all = False

put_version_in_init = True