#
# This file is autogenerated by pip-compile
# To update, run:
#
# pip-compile requirements_tune.in
#
--find-links https://download.pytorch.org/whl/torch_stable.html
absl-py==0.11.0
# via tensorboard
alembic==1.4.1
# via
# mlflow
# optuna
argon2-cffi==20.1.0
# via notebook
async-generator==1.10
# via nbclient
atari-py==0.2.6
# via
# -c ../requirements.txt
# gym
attrs==20.3.0
# via
# cmd2
# jsonschema
# pytest
autocfg==0.0.6
# via gluoncv
autogluon.core==0.0.16b20210122
# via gluoncv
autograd==1.3
# via autogluon.core
ax-platform==0.1.19 ; python_version >= "3.7"
# via -r requirements_tune.in
azure-core==1.10.0
# via azure-storage-blob
azure-storage-blob==12.7.1
# via mlflow
backcall==0.2.0
# via ipython
bayesian-optimization==1.2.0
# via
# -r requirements_tune.in
# nevergrad
bcrypt==3.2.0
# via paramiko
bleach==3.2.2
# via nbconvert
bokeh==2.2.3
# via dask
boto3==1.16.58
# via
# -c ../requirements.txt
# autogluon.core
# smart-open
botocore==1.19.58
# via
# boto3
# s3transfer
botorch==0.3.3
# via ax-platform
cached-property==1.5.2
# via h5py
cachetools==4.2.0
# via google-auth
certifi==2020.12.5
# via
# kubernetes
# msrest
# requests
# sentry-sdk
cffi==1.14.4
# via
# argon2-cffi
# bcrypt
# cryptography
# pynacl
chardet==4.0.0
# via requests
click==7.1.2
# via
# -c ../requirements.txt
# databricks-cli
# distributed
# flask
# mlflow
# sacremoses
# wandb
cliff==3.6.0
# via optuna
cloudpickle==1.6.0
# via
# dask
# distributed
# gym
# hyperopt
# mlflow
# tensorflow-probability
cma==3.0.3
# via nevergrad
cmaes==0.7.0
# via optuna
cmd2==1.4.0
# via cliff
colorama==0.4.4
# via
# -c ../requirements.txt
# cmd2
colorlog==4.7.2
# via optuna
configparser==5.0.1
# via wandb
configspace==0.4.10
# via
# -r requirements_tune.in
# autogluon.core
# hpbandster
cryptography==3.3.1
# via
# azure-storage-blob
# paramiko
cycler==0.10.0
# via matplotlib
cython==0.29.0
# via
# -c ../requirements.txt
# autogluon.core
# configspace
dask[complete]==2021.1.0
# via
# -c ../requirements.txt
# autogluon.core
# distributed
databricks-cli==0.14.1
# via mlflow
dataclasses==0.6
# via torch
decorator==4.4.2
# via
# ipython
# networkx
# paramz
# tensorflow-probability
decord==0.4.2
# via gluoncv
defusedxml==0.6.0
# via nbconvert
dill==0.3.3
# via autogluon.core
distributed==2021.1.0
# via
# autogluon.core
# dask
dm-tree==0.1.5
# via
# -c ../requirements.txt
# tensorflow-probability
docker-pycreds==0.4.0
# via wandb
docker==4.4.1
# via mlflow
dragonfly-opt==0.1.6
# via -r requirements_tune.in
entrypoints==0.3
# via
# mlflow
# nbconvert
filelock==3.0.12
# via
# -c ../requirements.txt
# transformers
flask==1.1.2
# via
# -c ../requirements.txt
# mlflow
# prometheus-flask-exporter
fsspec==0.8.5
# via
# dask
# pytorch-lightning
future==0.18.2
# via
# autograd
# dragonfly-opt
# hyperopt
# pyglet
# pytorch-lightning
# torch
gast==0.4.0
# via tensorflow-probability
gitdb==4.0.5
# via gitpython
gitpython==3.1.12
# via
# mlflow
# wandb
gluoncv==0.9.1
# via -r requirements_tune.in
google-auth-oauthlib==0.4.2
# via tensorboard
google-auth==1.24.0
# via
# google-auth-oauthlib
# kubernetes
# tensorboard
gpy==1.9.9
# via -r requirements_tune.in
gpytorch==1.3.1
# via botorch
graphviz==0.8.4
# via
# autogluon.core
# mxnet
grpcio==1.35.0
# via
# -c ../requirements.txt
# tensorboard
gunicorn==20.0.4
# via mlflow
gym[atari]==0.18.0
# via
# -c ../requirements.txt
# -r requirements_tune.in
h5py==3.1.0
# via
# -r requirements_tune.in
# keras
heapdict==1.0.1
# via zict
hpbandster==0.7.4
# via -r requirements_tune.in
hyperopt==0.2.5
# via -r requirements_tune.in
idna==2.10
# via requests
importlib-metadata==3.4.0
# via
# cmd2
# jsonschema
# markdown
# pluggy
# pytest
# stevedore
ipykernel==5.4.3
# via
# ipywidgets
# jupyter
# jupyter-console
# notebook
# qtconsole
ipython-genutils==0.2.0
# via
# nbformat
# notebook
# qtconsole
# traitlets
ipython==7.19.0
# via
# ipykernel
# ipywidgets
# jupyter-console
ipywidgets==7.6.3
# via jupyter
isodate==0.6.0
# via msrest
itsdangerous==1.1.0
# via flask
jedi==0.18.0
# via ipython
jinja2==2.11.2
# via
# ax-platform
# bokeh
# flask
# nbconvert
# notebook
jmespath==0.10.0
# via
# boto3
# botocore
joblib==1.0.0
# via
# optuna
# sacremoses
# scikit-learn
# scikit-optimize
jsonschema==3.2.0
# via
# -c ../requirements.txt
# nbformat
jupyter-client==6.1.11
# via
# ipykernel
# jupyter-console
# nbclient
# notebook
# qtconsole
jupyter-console==6.2.0
# via jupyter
jupyter-core==4.7.0
# via
# jupyter-client
# nbconvert
# nbformat
# notebook
# qtconsole
jupyter==1.0.0
# via -r requirements_tune.in
jupyterlab-pygments==0.1.2
# via nbconvert
jupyterlab-widgets==1.0.0
# via ipywidgets
keras==2.4.3
# via -r requirements_tune.in
kiwisolver==1.3.1
# via matplotlib
kubernetes==12.0.1
# via
# -c ../requirements.txt
# -r requirements_tune.in
lightgbm==3.1.1
# via -r requirements_tune.in
locket==0.2.1
# via partd
mako==1.1.4
# via alembic
markdown==3.3.3
# via tensorboard
markupsafe==1.1.1
# via
# jinja2
# mako
matplotlib==3.3.3
# via
# -r requirements_tune.in
# autogluon.core
# gluoncv
# zoopt
mistune==0.8.4
# via nbconvert
mlflow==1.13.1
# via -r requirements_tune.in
more-itertools==8.6.0
# via pytest
msgpack==1.0.2
# via
# -c ../requirements.txt
# distributed
msrest==0.6.19
# via azure-storage-blob
mxnet==1.7.0.post1
# via -r requirements_tune.in
nbclient==0.5.1
# via nbconvert
nbconvert==6.0.7
# via
# jupyter
# notebook
nbformat==5.1.2
# via
# ipywidgets
# nbclient
# nbconvert
# notebook
nest-asyncio==1.4.3
# via nbclient
netifaces==0.10.9
# via hpbandster
networkx==2.5
# via
# -c ../requirements.txt
# hyperopt
nevergrad==0.4.2.post5
# via -r requirements_tune.in
notebook==6.2.0
# via
# jupyter
# widgetsnbextension
numpy==1.19.5
# via
# -c ../requirements.txt
# atari-py
# autogluon.core
# autograd
# bayesian-optimization
# bokeh
# cma
# cmaes
# configspace
# dask
# decord
# dragonfly-opt
# gluoncv
# gpy
# gym
# h5py
# hpbandster
# hyperopt
# keras
# lightgbm
# matplotlib
# mlflow
# mxnet
# nevergrad
# opencv-python
# optuna
# pandas
# paramz
# patsy
# pytorch-lightning
# scikit-learn
# scikit-optimize
# scipy
# statsmodels
# tensorboard
# tensorboardx
# tensorflow-probability
# torch
# torchvision
# transformers
# xgboost
# zoopt
oauthlib==3.1.0
# via requests-oauthlib
opencv-python==4.5.1.48
# via
# gluoncv
# gym
optuna==2.4.0
# via -r requirements_tune.in
packaging==20.8
# via
# bleach
# bokeh
# optuna
# pytest
# transformers
pandas==1.0.5
# via
# -c ../requirements.txt
# autogluon.core
# ax-platform
# dask
# gluoncv
# mlflow
# statsmodels
pandocfilters==1.4.3
# via nbconvert
paramiko==2.7.2
# via autogluon.core
paramz==0.9.5
# via gpy
parso==0.8.1
# via jedi
partd==1.1.0
# via dask
patsy==0.5.1
# via statsmodels
pbr==5.5.1
# via
# cliff
# stevedore
pexpect==4.8.0
# via
# -c ../requirements.txt
# ipython
pickleshare==0.7.5
# via ipython
pillow==7.2.0 ; platform_system != "Windows"
# via
# -c ../requirements.txt
# bokeh
# gluoncv
# gym
# matplotlib
# torchvision
plotly==4.14.3
# via ax-platform
pluggy==0.13.1
# via pytest
portalocker==2.0.0
# via gluoncv
prettytable==0.7.2
# via cliff
prometheus-client==0.9.0
# via
# -c ../requirements.txt
# notebook
# prometheus-flask-exporter
prometheus-flask-exporter==0.18.1
# via mlflow
promise==2.3
# via wandb
prompt-toolkit==3.0.13
# via
# ipython
# jupyter-console
protobuf==3.14.0
# via
# -c ../requirements.txt
# mlflow
# tensorboard
# tensorboardx
# wandb
psutil==5.8.0
# via
# distributed
# wandb
ptyprocess==0.7.0
# via
# pexpect
# terminado
py==1.10.0
# via pytest
pyaml==20.4.0
# via scikit-optimize
pyasn1-modules==0.2.8
# via google-auth
pyasn1==0.4.8
# via
# pyasn1-modules
# rsa
pycparser==2.20
# via cffi
pyglet==1.5.0
# via gym
pygments==2.7.4
# via
# -c ../requirements.txt
# ipython
# jupyter-console
# jupyterlab-pygments
# nbconvert
# qtconsole
pynacl==1.4.0
# via paramiko
pyparsing==2.4.7
# via
# cliff
# configspace
# matplotlib
# packaging
pyperclip==1.8.1
# via cmd2
pyro4==4.80
# via hpbandster
pyrsistent==0.17.3
# via jsonschema
pytest-remotedata==0.3.2
# via -r requirements_tune.in
pytest==5.4.3
# via
# -c ../requirements.txt
# autogluon.core
# pytest-remotedata
python-dateutil==2.8.1
# via
# alembic
# bokeh
# botocore
# jupyter-client
# kubernetes
# matplotlib
# mlflow
# pandas
# wandb
python-editor==1.0.4
# via alembic
pytorch-lightning-bolts==0.2.5
# via -r requirements_tune.in
pytorch-lightning==1.0.3
# via
# -r requirements_tune.in
# pytorch-lightning-bolts
pytz==2020.5
# via pandas
pyyaml==5.4.1
# via
# -c ../requirements.txt
# autocfg
# bokeh
# cliff
# dask
# distributed
# gluoncv
# keras
# kubernetes
# mlflow
# pyaml
# pytorch-lightning
# wandb
# yacs
pyzmq==21.0.1
# via
# jupyter-client
# notebook
# qtconsole
qtconsole==5.0.2
# via jupyter
qtpy==1.9.0
# via qtconsole
querystring-parser==1.2.4
# via mlflow
regex==2020.11.13
# via
# sacremoses
# transformers
requests-oauthlib==1.3.0
# via
# google-auth-oauthlib
# kubernetes
# msrest
requests==2.25.1
# via
# -c ../requirements.txt
# autogluon.core
# azure-core
# databricks-cli
# docker
# gluoncv
# kubernetes
# mlflow
# msrest
# mxnet
# requests-oauthlib
# sigopt
# tensorboard
# transformers
# wandb
retrying==1.3.3
# via plotly
rsa==4.7
# via google-auth
s3transfer==0.3.4
# via boto3
sacremoses==0.0.43
# via transformers
scikit-learn==0.22.2
# via
# -c ../requirements.txt
# -r requirements_tune.in
# autogluon.core
# ax-platform
# bayesian-optimization
# gpytorch
# lightgbm
# scikit-optimize
scikit-optimize==0.8.1
# via
# -r requirements_tune.in
# autogluon.core
scipy==1.4.1
# via
# -c ../requirements.txt
# autogluon.core
# ax-platform
# bayesian-optimization
# botorch
# dragonfly-opt
# gluoncv
# gpy
# gpytorch
# gym
# hpbandster
# hyperopt
# keras
# lightgbm
# optuna
# paramz
# scikit-learn
# scikit-optimize
# statsmodels
# xgboost
send2trash==1.5.0
# via notebook
sentencepiece==0.1.95
# via transformers
sentry-sdk==0.19.5
# via wandb
serpent==1.30.2
# via
# hpbandster
# pyro4
shortuuid==1.0.1
# via wandb
sigopt==5.7.0
# via -r requirements_tune.in
six==1.15.0
# via
# absl-py
# argon2-cffi
# atari-py
# azure-core
# bcrypt
# bleach
# cryptography
# cycler
# databricks-cli
# dm-tree
# docker
# docker-pycreds
# dragonfly-opt
# google-auth
# gpy
# grpcio
# hyperopt
# isodate
# jsonschema
# kubernetes
# mlflow
# paramz
# patsy
# plotly
# promise
# protobuf
# pynacl
# pytest-remotedata
# python-dateutil
# querystring-parser
# retrying
# sacremoses
# tensorboard
# tensorboardx
# tensorflow-probability
# wandb
# websocket-client
smart_open[s3]==4.0.1
# via
# -c ../requirements.txt
# -r requirements_tune.in
smmap==3.0.4
# via gitdb
sortedcontainers==2.3.0
# via distributed
sqlalchemy==1.3.22
# via
# alembic
# mlflow
# optuna
sqlparse==0.4.1
# via mlflow
statsmodels==0.12.1
# via hpbandster
stevedore==3.3.0
# via cliff
subprocess32==3.5.4
# via wandb
tabulate==0.8.7
# via
# -c ../requirements.txt
# databricks-cli
tblib==1.7.0
# via distributed
tensorboard-plugin-wit==1.8.0
# via tensorboard
tensorboard==2.4.1
# via pytorch-lightning
tensorboardx==2.1
# via
# -c ../requirements.txt
# gluoncv
tensorflow-probability==0.11.1
# via -r requirements_tune.in
terminado==0.9.2
# via notebook
testpath==0.4.4
# via nbconvert
timm==0.3.2
# via -r requirements_tune.in
tokenizers==0.8.1.rc2
# via transformers
toolz==0.11.1
# via
# dask
# distributed
# partd
torch==1.7.0+cpu ; sys_platform != "darwin"
# via
# -r requirements_tune.in
# botorch
# gpytorch
# pytorch-lightning
# pytorch-lightning-bolts
# timm
# torchvision
torchvision==0.8.1+cpu ; sys_platform != "darwin"
# via
# -r requirements_tune.in
# timm
tornado==6.1
# via
# autogluon.core
# bokeh
# distributed
# ipykernel
# jupyter-client
# notebook
# terminado
tqdm==4.56.0
# via
# autogluon.core
# gluoncv
# hyperopt
# optuna
# pytorch-lightning
# sacremoses
# transformers
traitlets==5.0.5
# via
# ipykernel
# ipython
# ipywidgets
# jupyter-client
# jupyter-core
# nbclient
# nbconvert
# nbformat
# notebook
# qtconsole
transformers==3.1
# via -r requirements_tune.in
typeguard==2.10.0
# via ax-platform
typing-extensions==3.7.4.3
# via
# bokeh
# importlib-metadata
# nevergrad
# torch
typing==3.7.4.3
# via configspace
urllib3==1.26.2
# via
# botocore
# kubernetes
# requests
# sentry-sdk
wandb==0.10.12
# via -r requirements_tune.in
watchdog==1.0.2
# via wandb
wcwidth==0.2.5
# via
# cmd2
# prompt-toolkit
# pytest
webencodings==0.5.1
# via bleach
websocket-client==0.57.0
# via
# docker
# kubernetes
werkzeug==1.0.1
# via
# -c ../requirements.txt
# flask
# tensorboard
wheel==0.36.2
# via
# lightgbm
# tensorboard
widgetsnbextension==3.5.1
# via ipywidgets
xgboost==1.3.0.post0
# via -r requirements_tune.in
yacs==0.1.8
# via gluoncv
zict==2.0.0
# via distributed
zipp==3.4.0
# via importlib-metadata
zoopt==0.4.1
# via -r requirements_tune.in
# The following packages are considered to be unsafe in a requirements file:
# setuptools