From 23b6366c39e47ba0ca2760f0a2e2b2b9a056d464 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= Date: Sun, 13 Oct 2019 00:19:05 +0930 Subject: [PATCH] Update to TF 2.0.0 (from nightly) and update other libraries --- requirements.txt | 62 ++++++++++++++++++++++-------------------------- 1 file changed, 29 insertions(+), 33 deletions(-) diff --git a/requirements.txt b/requirements.txt index 5ecb458..193351e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,8 +1,8 @@ # First make sure to update pip: -# $ sudo pip install --upgrade pip +# $ sudo python3 -m pip install --upgrade pip # # Then you probably want to work in a virtualenv (optional): -# $ sudo pip install --upgrade virtualenv +# $ 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 @@ -13,11 +13,9 @@ # # Next, optionally uncomment the OpenAI gym lines (see below). # If you do, make sure to install the dependencies first. -# If you are interested in xgboost for high performance Gradient Boosting, you -# should uncomment the xgboost line (used in the ensemble learning notebook). # # Then install these requirements: -# $ pip install --upgrade -r requirements.txt +# $ python3 -m pip install --upgrade -r requirements.txt # # Finally, start jupyter: # $ jupyter notebook @@ -26,17 +24,17 @@ ##### Core scientific packages jupyter==1.0.0 -matplotlib==3.0.3 -numpy==1.16.2 -pandas==0.24.1 -scipy==1.1.0 +matplotlib==3.1.1 +numpy==1.17.2 +pandas==0.25.1 +scipy==1.3.1 ##### Machine Learning packages -scikit-learn==0.20.3 +scikit-learn==0.20.4 # Optional: the XGBoost library is only used in the ensemble learning chapter. -xgboost==0.82 +xgboost==0.90 ##### TensorFlow-related packages @@ -46,36 +44,35 @@ xgboost==0.82 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed # installation instructions. -tf-nightly-2.0-preview -#tf-nightly-gpu-2.0-preview +tensorflow==2.0.0 +#tensorflow-gpu==2.0.0 -#tensorboard -tb-nightly +tensorboard==2.0.0 -#tensorflow-datasets -tfds-nightly +tensorflow-datasets==1.2.0 -tensorflow-hub +tensorflow-hub==0.6.0 # Optional: only used in chapter 13. -#tensorflow-transform==0.13.0 +tfx==0.14.0 # Optional: only used in chapter 16. -# At the present (April 2019) the TF Addons library is only available on Linux -# So uncomment this line if you are using Linux. -#tensorflow-addons +#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 +tensorflow-serving-api==1.14.0 ##### Image manipulation -imageio==2.5.0 -Pillow==5.4.1 -scikit-image==0.14.2 +imageio==2.6.0 +Pillow==6.2.0 +scikit-image==0.15.0 +graphviz==0.10.1 +pygraphviz==1.3 +pydot==1.4.1 ##### Reinforcement Learning library @@ -83,7 +80,7 @@ scikit-image==0.14.2 # 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]==0.10.9 +gym[atari]==0.15.3 ##### Additional utilities @@ -93,19 +90,18 @@ joblib==0.13.2 # May be useful with Pandas for complex "where" clauses (e.g., Pandas # tutorial). -numexpr==2.6.9 +numexpr==2.7.0 # Optional: these libraries can be useful in chapter 3, exercise 4. nltk==3.4.5 -urlextract==0.9 +urlextract==0.13.0 # Needed in chapter 19. requests==2.22.0 # Optional: nice utility to diff Jupyter Notebooks. -#nbdime==1.0.5 +#nbdime==1.1.0 # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support -tqdm==4.31.1 -ipywidgets==7.4.2 - +tqdm==4.36.1 +ipywidgets==7.5.1