From 1f542d27571595b78716e19c7e8fed00baf83a8c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= Date: Mon, 16 Dec 2019 23:18:29 +0800 Subject: [PATCH] Update requirements.txt and send Anaconda love --- requirements.txt | 122 ++++++++++++++++++++++------------------------- 1 file changed, 56 insertions(+), 66 deletions(-) diff --git a/requirements.txt b/requirements.txt index aaf078e..e75909f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,104 +1,94 @@ -# First make sure to update pip: -# $ sudo python3 -m pip install --upgrade pip -# -# Then you probably want to work in a virtualenv (optional): -# $ sudo python3 -m pip install --upgrade virtualenv -# Or if you prefer you can install virtualenv using your favorite packaging -# system. E.g., in Ubuntu: -# $ sudo apt-get update && sudo apt-get install virtualenv -# Then: -# $ cd $my_work_dir -# $ virtualenv my_env -# $ . my_env/bin/activate -# -# Next, optionally uncomment the OpenAI gym lines (see below). -# If you do, make sure to install the dependencies first. -# -# Then install these requirements: -# $ python3 -m pip install --upgrade -r requirements.txt -# -# Finally, start jupyter: -# $ jupyter notebook -# - +# TensorFlow is much easier to install using Anaconda, especially +# on Windows or when using a GPU. Please see the installation +# instructions in INSTALL.md ##### Core scientific packages jupyter==1.0.0 -matplotlib==3.1.1 -numpy==1.17.2 -pandas==0.25.1 +matplotlib==3.1.2 +numpy==1.17.3 +pandas==0.25.3 scipy==1.3.1 ##### Machine Learning packages -scikit-learn==0.20.4 +scikit-learn==0.22 -# Optional: the XGBoost library is only used in the ensemble learning chapter. +# Optional: the XGBoost library is only used in chapter 7 xgboost==0.90 - ##### TensorFlow-related packages -# Replace tensorflow with tensorflow-gpu if you want GPU support. If so, -# you need a GPU card with CUDA Compute Capability 3.5 or higher support, and +# If you have a TF-compatible GPU and you want to enable GPU support, then +# replace tensorflow with tensorflow-gpu, and replace tensorflow-serving-api +# with tensorflow-serving-api-gpu. +# Your GPU must have CUDA Compute Capability 3.5 or higher support, and # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed # installation instructions. tensorflow==2.0.0 #tensorflow-gpu==2.0.0 -tensorboard==2.0.0 - -tensorflow-datasets==1.3.0 - -tensorflow-hub==0.6.0 - -# Optional: only used in chapter 13. -tfx==0.15.0rc0 - -# Optional: only used in chapter 16. -#tensorflow-addons==0.6.0 - -# Optional: the TF Agents library is only needed in chapter 18 -tf-agents-nightly - # Optional: the TF Serving API library is just needed for chapter 19. tensorflow-serving-api==2.0.0 +#tensorflow-serving-api-gpu==2.0.0 + +tensorboard==2.0.0 +tensorflow-datasets==1.3.0 +tensorflow-hub==0.6.0 +tensorflow-probability==0.7 + +# Optional: only used in chapter 13. +# NOT AVAILABLE ON WINDOWS +tfx==0.15.0 + +# Optional: only used in chapter 16. +# NOT AVAILABLE ON WINDOWS +tensorflow-addons==0.6.0 + +##### Reinforcement Learning library (chapter 18) + +# There are a few dependencies you need to install first, check out: +# https://github.com/openai/gym#installing-everything +gym[atari]==0.15.4 +# On Windows, install atari_py using: +# pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py + +tf-agents==0.3.0rc0 ##### Image manipulation -imageio==2.6.0 -Pillow==6.2.0 -scikit-image==0.15.0 -graphviz==0.10.1 +imageio==2.6.1 +Pillow==6.2.1 +scikit-image==0.16.2 +graphviz +pydot==1.4.1 +opencv-python==4.1.2.30 +pyglet==1.3.2 -##### Reinforcement Learning library - -# OpenAI gym is only needed in chapter 18. -# There are a few dependencies you need to install first, check out: -# https://github.com/openai/gym#installing-everything -gym[atari,box2d,classic_control]==0.15.3 +#pyvirtualdisplay # needed in chapter 16, if on a headless server + # (i.e., without screen, e.g., Colab or VM) ##### Additional utilities -# Joblib is a set of tools to provide lightweight pipelining -joblib==0.13.2 +# Efficient jobs (caching, parallelism, persistence) +joblib==0.14.0 + +# Easy http requests +requests==2.22.0 + +# Nice utility to diff Jupyter Notebooks. +nbdime==1.1.0 # May be useful with Pandas for complex "where" clauses (e.g., Pandas # tutorial). numexpr==2.7.0 -# Optional: these libraries can be useful in chapter 3, exercise 4. +# Optional: these libraries can be useful in the classification chapter, +# exercise 4. nltk==3.4.5 urlextract==0.13.0 -# Needed in chapter 19. -requests==2.22.0 - -# Optional: nice utility to diff Jupyter Notebooks. -#nbdime==1.1.0 - # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support -tqdm==4.36.1 +tqdm==4.40.0 ipywidgets==7.5.1