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Update lib versions

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Aurélien Geron
2022-02-19 18:49:54 +13:00
parent 9e5ee748d9
commit 8745a9c2ac
2 changed files with 55 additions and 74 deletions
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environment.yml
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@@ -3,53 +3,41 @@ channels:
- conda-forge
- defaults
dependencies:
- box2d-py # used only in chapter 17, exercise 8
- ftfy=6.0 # used only in chapter 15 by the transformers library
- graphviz # used only in chapter 5 for dot files
- gym=0.19 # used only in chapter 17
- ipython=7.28 # a powerful Python shell
- box2d-py # used only in chapter 18, exercise 8
- ftfy=5.5 # used only in chapter 16 by the transformers library
- graphviz # used only in chapter 6 for dot files
- python-graphviz # used only in chapter 6 for dot files
- ipython=8.0 # a powerful Python shell
- ipywidgets=7.6 # optionally used only in chapter 11 for tqdm in Jupyter
- joblib=0.14 # used only in chapter 2 to save/load Scikit-Learn models
- joblib=1.1 # used only in chapter 2 to save/load Scikit-Learn models
- jupyterlab=3.2 # to edit and run Jupyter notebooks
- matplotlib=3.4 # beautiful plots. See tutorial tools_matplotlib.ipynb
- 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
- numexpr=2.7 # used only in the Pandas tutorial for numerical expressions
- numpy=1.19 # Powerful n-dimensional arrays and numerical computing tools
- opencv=4.5 # used only in chapter 17 by TF Agents for image preprocessing
- pandas=1.3 # data analysis and manipulation tool
- pillow=8.3 # image manipulation library, (used by matplotlib.image.imread)
- numexpr=2.8 # used only in the Pandas tutorial for numerical expressions
- numpy=1.22 # Powerful n-dimensional arrays and numerical computing tools
- pandas=1.4 # data analysis and manipulation tool
- pillow=9.0 # image manipulation library, (used by matplotlib.image.imread)
- pip # Python's package-management system
- py-xgboost=1.4 # used only in chapter 6 for optimized Gradient Boosting
- pyglet=1.5 # used only in chapter 17 to render environments
- pyopengl=3.1 # used only in chapter 17 to render environments
- python=3.8 # Python! Not using latest version as some libs lack support
- python-graphviz # used only in chapter 5 for dot files
#- pyvirtualdisplay=2.2 # used only in chapter 17 if on headless server
- requests=2.26 # used only in chapter 18 for REST API queries
- py-xgboost=1.5 # used only in chapter 6 for optimized Gradient Boosting
- pyglet=1.5 # used only in chapter 18 to render environments
- pyopengl=3.1 # used only in chapter 18 to render environments
- python=3.9 # Python! Not using latest version as some libs lack support
#- pyvirtualdisplay=2.2 # used only in chapter 18 if on headless server
- requests=2.27 # used only in chapter 19 for REST API queries
- scikit-learn=1.0 # machine learning library
- scipy=1.7 # scientific/technical computing library
- scipy=1.8 # scientific/technical computing library
- tqdm=4.62 # a progress bar library
- wheel # built-package format for pip
- widgetsnbextension=3.5 # interactive HTML widgets for Jupyter notebooks
- pip:
- tensorboard-plugin-profile~=2.5.0 # profiling plugin for TensorBoard
- tensorboard~=2.7.0 # TensorFlow's visualization toolkit
- tensorflow-addons~=0.14.0 # used only in chapter 15 for a seq2seq impl.
- tensorflow-datasets~=4.4.0 # datasets repository, ready to use
- tensorboard~=2.8.0 # TensorFlow's visualization toolkit
- tensorflow-addons~=0.15.0 # used in chapters 11 & 16 (for AdamW & seq2seq)
- tensorflow-datasets~=4.5.2 # datasets repository, ready to use
- tensorflow-hub~=0.12.0 # trained ML models repository, ready to use
- tensorflow-probability~=0.14.1 # Optional. Probability/Stats lib.
- tensorflow-serving-api~=2.6.0 # or tensorflow-serving-api-gpu if gpu
- tensorflow~=2.6.0 # Deep Learning library
- tf-agents~=0.10.0 # Reinforcement Learning lib based on TensorFlow
- tfx~=1.3.0 # platform to deploy production ML pipelines
- transformers~=4.11.3 # Natural Language Processing lib for TF or PyTorch
- urlextract~=1.4.0 # optionally used in chapter 3, exercise 4
- tensorflow-serving-api~=2.7.0 # or tensorflow-serving-api-gpu if gpu
- tensorflow~=2.7.1 # Deep Learning library
- transformers~=4.16.2 # Natural Language Processing lib for TF or PyTorch
- urlextract~=1.5.0 # optionally used in chapter 3, exercise 4
- gym[atari,accept-rom-license]~=0.21.0 # used only in chapter 18
# Specific lib versions to avoid conflicts
- attrs=20.3
- click=7.1
- packaging=20.9
- six=1.15
- typing-extensions=3.7