Update lib versions

environment.yml

@@ -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

requirements.txt

@@ -5,19 +5,19 @@
 
 ##### Core scientific packages
 jupyterlab~=3.2.0
-matplotlib~=3.4.3
-numpy~=1.19.5
-pandas~=1.3.3
-scipy~=1.7.1
+matplotlib~=3.5.0
+numpy~=1.22.0
+pandas~=1.4.0
+scipy~=1.8.0
 
 ##### Machine Learning packages
-scikit-learn~=1.0.1
+scikit-learn~=1.0.2
 
-# Optional: the XGBoost library is only used in chapter 6
-xgboost~=1.4.2
+# Optional: the XGBoost library is only used in chapter 7
+xgboost~=1.5.0
 
-# Optional: the transformers library is only using in chapter 15
-transformers~=4.11.3
+# Optional: the transformers library is only using in chapter 16
+transformers~=4.16.2
 
 ##### TensorFlow-related packages
 
@@ -27,23 +27,19 @@ transformers~=4.11.3
 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed
 # installation instructions.
 
-tensorflow~=2.6.0
+tensorflow~=2.7.1
 # Optional: the TF Serving API library is just needed for chapter 18.
-tensorflow-serving-api~=2.6.0 # or tensorflow-serving-api-gpu if gpu
+tensorflow-serving-api~=2.7.0 # or tensorflow-serving-api-gpu if gpu
 
-tensorboard~=2.7.0
+tensorboard~=2.8.0
 tensorboard-plugin-profile~=2.5.0
-tensorflow-datasets~=4.4.0
+tensorflow-datasets~=4.5.2
 tensorflow-hub~=0.12.0
-tensorflow-probability~=0.14.1
 
-# Optional: only used in chapter 12.
-tfx~=1.3.0
+# Optional: used in chapters 11 & 16 (for AdamW & seq2seq)
+tensorflow-addons~=0.15.0
 
-# Optional: only used in chapter 15.
-tensorflow-addons~=0.14.0
-
-##### Reinforcement Learning library (chapter 17)
+##### Reinforcement Learning library (chapter 18)
 
 # There are a few dependencies you need to install first, check out:
 # https://github.com/openai/gym#installing-everything
@@ -51,45 +47,42 @@ gym[Box2D,atari,accept-rom-license]~=0.21.0
 
 # WARNING: on Windows, installing Box2D this way requires:
 # * Swig: http://www.swig.org/download.html
-# * Microsoft C++ Build Tools: https://visualstudio.microsoft.com/visual-cpp-build-tools/
+# * Microsoft C++ Build Tools:
+#   https://visualstudio.microsoft.com/visual-cpp-build-tools/
 # It's much easier to use Anaconda instead.
 
-tf-agents~=0.10.0
-
 ##### Image manipulation
-Pillow~=8.4.0
-graphviz~=0.17
-opencv-python~=4.5.3.56
+Pillow~=9.0.0
+graphviz~=0.19.1
 pyglet~=1.5.21
 
-#pyvirtualdisplay # needed in chapter 17, if on a headless server
+#pyvirtualdisplay # needed in chapter 18, if on a headless server
                   # (i.e., without screen, e.g., Colab or VM)
 
 
 ##### Additional utilities
 
 # Efficient jobs (caching, parallelism, persistence)
-joblib~=0.14.1
+joblib~=1.1.0
 
 # Easy http requests
-requests~=2.26.0
+requests~=2.27.0
 
 # Nice utility to diff Jupyter Notebooks.
 nbdime~=3.1.0
 
 # May be useful with Pandas for complex "where" clauses (e.g., Pandas
 # tutorial).
-numexpr~=2.7.3
+numexpr~=2.8.0
 
-# Optional: these libraries can be useful in the chapter 3, exercise 4.
+# Optional: these libraries can be useful in chapter 3, exercise 4.
 nltk~=3.6.5
-urlextract~=1.4.0
+urlextract~=1.5.0
 
-# Optional: these libraries are only used in chapter 15
-ftfy~=6.0.3
+# Optional: these libraries are only used in chapter 16
+ftfy~=5.5.0
 
-# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support
+# Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook
+#           support
 tqdm~=4.62.3
 ipywidgets~=7.6.5
-
-