diff --git a/environment.yml b/environment.yml index f485394..73e22ad 100644 --- a/environment.yml +++ b/environment.yml @@ -1,48 +1,54 @@ -name: tf2 +name: homl3 channels: - conda-forge - defaults dependencies: - - atari_py=0.2.6 # used only in chapter 18 - - box2d-py=2.3 # used only in chapter 18 - - ftfy=5.8 # used only in chapter 16 by the transformers library - - graphviz # used only in chapter 6 for dot files - - gym=0.18 # used only in chapter 18 - - ipython=7.20 # a powerful Python shell - - ipywidgets=7.6 # optionally used only in chapter 12 for tqdm in Jupyter + - atari_py==0.2.6 # used only in chapter 17 + - box2d-py=2.3 # used only in chapter 17 + - 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 + - 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 - jupyter=1.0 # to edit and run Jupyter notebooks - - matplotlib=3.3 # beautiful plots. See tutorial tools_matplotlib.ipynb - - nbdime=2.1 # optional tool to diff Jupyter notebooks - - nltk=3.4 # optionally used in chapter 3, exercise 4 + - matplotlib=3.4 # 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 18 by TF Agents for image preprocessing - - pandas=1.2 # data analysis and manipulation tool - - pillow=8.1 # image manipulation library, (used by matplotlib.image.imread) + - 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) - pip # Python's package-management system - - py-xgboost=0.90 # used only in chapter 7 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 + - 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=3.7 # Python! Not using latest version as some libs lack support - - python-graphviz # used only in chapter 6 for dot files - #- pyvirtualdisplay=1.3 # used only in chapter 18 if on headless server - - requests=2.25 # used only in chapter 19 for REST API queries - - scikit-learn=0.24 # machine learning library - - scipy=1.6 # scientific/technical computing library - - tqdm=4.56 # a progress bar library - - transformers=4.3 # Natural Language Processing lib for TF or PyTorch + - 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 + - scikit-learn=1.0 # machine learning library + - scipy=1.7 # 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==2.4.0 # profiling plugin for TensorBoard - - tensorboard==2.4.1 # TensorFlow's visualization toolkit - - tensorflow-addons==0.12.1 # used only in chapter 16 for a seq2seq impl. - - tensorflow-datasets==3.0.0 # datasets repository, ready to use - - tensorflow-hub==0.9.0 # trained ML models repository, ready to use - - tensorflow-probability==0.12.1 # Optional. Probability/Stats lib. - - tensorflow-serving-api==2.4.1 # or tensorflow-serving-api-gpu if gpu - - tensorflow==2.4.2 # Deep Learning library - - tf-agents==0.7.1 # Reinforcement Learning lib based on TensorFlow - - tfx==0.27.0 # platform to deploy production ML pipelines - - urlextract==1.2.0 # optionally used in chapter 3, exercise 4 + - tensorboard-plugin-profile==2.5.0 # profiling plugin for TensorBoard + - tensorboard==2.6.0 # 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 + - 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 + - attrs=20.3 + - click=7.1 + - packaging=20.9 + - six=1.15 + - typing-extensions=3.7 + diff --git a/requirements.txt b/requirements.txt index 0b7d84d..a93983a 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,19 +5,19 @@ ##### Core scientific packages jupyter==1.0.0 -matplotlib==3.3.4 +matplotlib==3.4.3 numpy==1.19.5 -pandas==1.2.2 -scipy==1.6.0 +pandas==1.3.3 +scipy==1.7.1 ##### Machine Learning packages -scikit-learn==0.24.2 +scikit-learn==1.0 # Optional: the XGBoost library is only used in chapter 7 -xgboost==1.3.3 +xgboost==1.4.2 # Optional: the transformers library is only using in chapter 16 -transformers==4.3.2 +transformers==4.11.3 ##### TensorFlow-related packages @@ -27,41 +27,41 @@ transformers==4.3.2 # you must install CUDA, cuDNN and more: see tensorflow.org for the detailed # installation instructions. -tensorflow==2.4.2 +tensorflow==2.6.0 # Optional: the TF Serving API library is just needed for chapter 19. -tensorflow-serving-api==2.4.1 # or tensorflow-serving-api-gpu if gpu +tensorflow-serving-api==2.6.0 # or tensorflow-serving-api-gpu if gpu -tensorboard==2.4.1 -tensorboard-plugin-profile==2.4.0 -tensorflow-datasets==3.0.0 -tensorflow-hub==0.9.0 -tensorflow-probability==0.12.1 +tensorboard==2.6.0 +tensorboard-plugin-profile==2.5.0 +tensorflow-datasets==4.4.0 +tensorflow-hub==0.12.0 +tensorflow-probability==0.14.1 # Optional: only used in chapter 13. # NOT AVAILABLE ON WINDOWS -tfx==0.27.0 +tfx==1.3.0 # Optional: only used in chapter 16. # NOT AVAILABLE ON WINDOWS -tensorflow-addons==0.12.1 +tensorflow-addons==0.14.0 ##### 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[Box2D]==0.18.0 -atari_py==0.2.5 +gym[Box2D]==0.21.0 +atari-py==0.2.5 # On Windows, install atari_py using: # pip install --no-index -f https://github.com/Kojoley/atari-py/releases atari_py -tf-agents==0.7.1 +tf-agents==0.10.0 ##### Image manipulation Pillow==8.3.2 -graphviz==0.16 -opencv-python==4.5.1.48 -pyglet==1.5.0 +graphviz==0.17 +opencv-python==4.5.3.56 +pyglet==1.5.21 #pyvirtualdisplay # needed in chapter 16, if on a headless server # (i.e., without screen, e.g., Colab or VM) @@ -73,23 +73,24 @@ pyglet==1.5.0 joblib==0.14.1 # Easy http requests -requests==2.25.1 +requests==2.26.0 # Nice utility to diff Jupyter Notebooks. -nbdime==2.1.0 +nbdime==3.1.0 # May be useful with Pandas for complex "where" clauses (e.g., Pandas # tutorial). -numexpr==2.7.2 +numexpr==2.7.3 # Optional: these libraries can be useful in the classification chapter, # exercise 4. -nltk==3.5 -urlextract==1.2.0 +nltk==3.6.3 +urlextract==1.4.0 # Optional: these libraries are only used in chapter 16 -ftfy==5.8 +ftfy==6.0.3 # Optional: tqdm displays nice progress bars, ipywidgets for tqdm's notebook support -tqdm==4.56.1 -ipywidgets==7.6.3 +tqdm==4.62.3 +ipywidgets==7.6.5 +