From bde6c1704e9ac208b23f3770a65374e9c75590f2 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= Date: Tue, 14 Nov 2023 18:09:29 +1300 Subject: [PATCH] Update libraries --- environment.yml | 60 +++++++++++++++++++++++------------------------ requirements.txt | 61 ++++++++++++++++++++++++------------------------ 2 files changed, 60 insertions(+), 61 deletions(-) diff --git a/environment.yml b/environment.yml index c6efd40..bfffaa2 100644 --- a/environment.yml +++ b/environment.yml @@ -4,42 +4,42 @@ channels: - defaults dependencies: - box2d-py=2.3 # used only in chapter 18, exercise 8 - - ffmpeg=5.1 # used only in the matplotlib tutorial to generate animations + - ffmpeg=6.1 # used only in the matplotlib tutorial to generate animations - graphviz # used only in chapter 6 for dot files - python-graphviz # used only in chapter 6 for dot files - - ipython=8.5 # a powerful Python shell - - ipywidgets=8.0 # optionally used only in chapter 12 for tqdm in Jupyter - - joblib=1.1 # used only in chapter 2 to save/load Scikit-Learn models - - jupyterlab=3.4 # to edit and run Jupyter notebooks - - matplotlib=3.5 # beautiful plots. See tutorial tools_matplotlib.ipynb - - nbdime=3.1 # optional tool to diff Jupyter notebooks - - nltk=3.6 # optionally used in chapter 3, exercise 4 + - ipython=8.17 # a powerful Python shell + - ipywidgets=8.1 # optionally used only in chapter 12 for tqdm in Jupyter + - joblib=1.3 # used only in chapter 2 to save/load Scikit-Learn models + - jupyterlab=4.0 # to edit and run Jupyter notebooks + - matplotlib=3.8 # beautiful plots. See tutorial tools_matplotlib.ipynb + - nbdime=3.2 # optional tool to diff Jupyter notebooks + - nltk=3.8 # optionally used in chapter 3, exercise 4 - numexpr=2.8 # used only in the Pandas tutorial for numerical expressions - - numpy=1.23 # Powerful n-dimensional arrays and numerical computing tools - - pandas=1.4 # data analysis and manipulation tool - - pillow=9.2 # image manipulation library, (used by matplotlib.image.imread) + - numpy=1.26 # Powerful n-dimensional arrays and numerical computing tools + - pandas=2.1 # data analysis and manipulation tool + - pillow=10.1 # image manipulation library, (used by matplotlib.image.imread) - pip # Python's package-management system - - py-xgboost=1.6 # used only in chapter 6 for optimized Gradient Boosting + - py-xgboost=1.7 # used only in chapter 6 for optimized Gradient Boosting - pydot=1.4 # used only for in chapter 10 for tf.keras.utils.plot_model() - python=3.10 # your beloved programming language! :) - - requests=2.28 # used only in chapter 19 for REST API queries - - scikit-learn=1.1 # machine learning library - - scipy=1.9 # scientific/technical computing library - - statsmodels=0.13 # used only in chapter 15 for time series analysis - - tqdm=4.64 # used only in chapter 12 to display nice progress bars + - requests=2.31 # used only in chapter 19 for REST API queries + - scikit-learn=1.3 # machine learning library + - scipy=1.11 # scientific/technical computing library + - statsmodels=0.14 # used only in chapter 15 for time series analysis + - tqdm=4.66 # used only in chapter 12 to display nice progress bars - wheel # built-package format for pip - widgetsnbextension=4.0 # interactive HTML widgets for Jupyter notebooks - pip: - - keras-tuner~=1.1.3 # used in chapters 10 and 19 for hyperparameter tuning - - tensorboard-plugin-profile~=2.8.0 # profiling plugin for TensorBoard - - tensorboard~=2.10.0 # TensorFlow's visualization toolkit - - tensorflow-addons~=0.17.1 # used in chapters 11 & 16 (for AdamW & seq2seq) - - tensorflow-datasets~=4.6.0 # datasets repository, ready to use - - tensorflow-hub~=0.12.0 # trained ML models repository, ready to use - - tensorflow-serving-api~=2.10.0 # or tensorflow-serving-api-gpu if gpu - - tensorflow~=2.10.0 # Deep Learning library - - transformers~=4.21.3 # Natural Language Processing lib for TF or PyTorch - - urlextract~=1.6.0 # optionally used in chapter 3, exercise 4 - - gym[classic_control,atari,accept-rom-license]~=0.26.1 # used only in ch18 - - google-cloud-aiplatform~=1.17.0 # used only in chapter 19 - - google-cloud-storage~=2.5.0 # used only in chapter 19 + - keras-core # used in chapter 10 + - keras-tuner~=1.4.6 # used in chapters 10 and 19 for hyperparameter tuning + - tensorboard-plugin-profile~=2.14.0 # profiling plugin for TensorBoard + - tensorboard~=2.14.1 # TensorFlow's visualization toolkit + - tensorflow-datasets~=4.9.3 # datasets repository, ready to use + - tensorflow-hub~=0.15.0 # trained ML models repository, ready to use + - tensorflow-serving-api~=2.14.0 # or tensorflow-serving-api-gpu if gpu + - tensorflow~=2.14.0 # Deep Learning library + - transformers~=4.35.0 # Natural Language Processing lib for TF or PyTorch + - urlextract~=1.8.0 # optionally used in chapter 3, exercise 4 + - gym[classic_control,atari,accept-rom-license] # used only in ch18 + - google-cloud-aiplatform~=1.36.2 # used only in chapter 19 + - google-cloud-storage~=2.13.0 # used only in chapter 19 diff --git a/requirements.txt b/requirements.txt index ee866d7..47f10ea 100644 --- a/requirements.txt +++ b/requirements.txt @@ -4,20 +4,20 @@ ##### Core scientific packages -jupyterlab~=3.4.6 -matplotlib~=3.5.3 -numpy~=1.23.3 -pandas~=1.4.4 -scipy~=1.9.1 +jupyterlab~=4.0.8 +matplotlib~=3.8.1 +numpy~=1.26.2 +pandas~=2.1.3 +scipy~=1.11.3 ##### Machine Learning packages -scikit-learn~=1.1.2 +scikit-learn~=1.3.2 # Optional: the XGBoost library is only used in chapter 7 -xgboost~=1.6.2 +xgboost~=2.0.2 # Optional: the transformers library is only used in chapter 16 -transformers~=4.21.3 +transformers~=4.35.0 ##### TensorFlow-related packages @@ -27,26 +27,24 @@ transformers~=4.21.3 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed # installation instructions. -tensorflow~=2.10.0 +tensorflow~=2.14.0 +keras-core # Optional: the TF Serving API library is just needed for chapter 18. -tensorflow-serving-api~=2.10.0 # or tensorflow-serving-api-gpu if gpu +tensorflow-serving-api~=2.14.0 # or tensorflow-serving-api-gpu if gpu -tensorboard~=2.10.0 -tensorboard-plugin-profile~=2.8.0 -tensorflow-datasets~=4.6.0 -tensorflow-hub~=0.12.0 +tensorboard~=2.14.1 +tensorboard-plugin-profile~=2.14.0 +tensorflow-datasets~=4.9.3 +tensorflow-hub~=0.15.0 # Used in chapter 10 and 19 for hyperparameter tuning -keras-tuner~=1.1.3 - -# Optional: used in chapters 11 & 16 (for AdamW & seq2seq) -tensorflow-addons~=0.17.1 +keras-tuner~=1.4.6 ##### 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[Box2D,atari,accept-rom-license]~=0.26.1 +gym[Box2D,atari,accept-rom-license]~=0.26.2 # WARNING: on Windows, installing Box2D this way requires: # * Swig: http://www.swig.org/download.html @@ -55,39 +53,40 @@ gym[Box2D,atari,accept-rom-license]~=0.26.1 # It's much easier to use Anaconda instead. ##### Image manipulation -Pillow~=9.2.0 +Pillow~=10.1.0 graphviz~=0.20.1 ##### Google Cloud Platform - used only in chapter 19 -google-cloud-aiplatform~=1.17.0 -google-cloud-storage~=2.5.0 +google-cloud-aiplatform~=1.36.2 +google-cloud-storage~=2.13.0 ##### Additional utilities # Efficient jobs (caching, parallelism, persistence) -joblib~=1.1.0 +joblib~=1.3.2 # Easy http requests -requests~=2.28.1 +requests~=2.31.0 # Nice utility to diff Jupyter Notebooks. -nbdime~=3.1.1 +nbdime~=3.2.1 # May be useful with Pandas for complex "where" clauses (e.g., Pandas # tutorial). -numexpr~=2.8.3 +numexpr~=2.8.7 # Optional: these libraries can be useful in chapter 3, exercise 4. -nltk~=3.7 -urlextract~=1.6.0 +nltk~=3.8.1 +urlextract~=1.8.0 # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook # support -tqdm~=4.64.1 -ipywidgets~=8.0.2 +tqdm~=4.66.1 +ipywidgets~=8.1.1 # Optional: pydot is only used in chapter 10 for tf.keras.utils.plot_model() pydot~=1.4.2 # Optional: statsmodels is only used in chapter 15 for time series analysis -statsmodels~=0.13.2 +statsmodels~=0.14.0 +