diff --git a/Dockerfile b/Dockerfile index d182a2b..80f8986 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,4 +1,4 @@ -FROM ucsdets/scipy-ml-notebook:2023.1-stable +FROM ucsdets/scipy-ml-notebook:2024.2-stable LABEL maintainer="Javier Duarte " USER root @@ -11,22 +11,21 @@ USER jovyan RUN mamba install -c conda-forge uproot xrootd root -RUN pip install --no-cache-dir 'xgboost==1.7.3' 'scikit-learn==1.2.1' 'spektral==1.2.0' 'gdown==4.6.0' 'mplhep==0.3.26' && \ +RUN pip install --no-cache-dir 'xgboost==2.0.3' 'scikit-learn==1.4.1' 'spektral==1.3.1' 'gdown==5.1.0' 'mplhep==0.3.43' && \ fix-permissions /opt/conda && \ fix-permissions /home/jovyan -RUN pip install --no-cache-dir --no-index torch-scatter torch-sparse torch-cluster torch-spline-conv -f https://data.pyg.org/whl/torch-1.9.0+cu111.html && \ - pip install --no-cache-dir torch-geometric && \ +RUN pip install --no-cache-dir --no-index pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cu118.html && \ pip install --no-cache-dir typing-extensions --upgrade # RUN pip install --no-cache-dir 'jetnet==0.2.2' -USER $NB_UID:$NB_GID -RUN mkdir -p /tmp/nvvm && mkdir -p /tmp/nvvm/libdevice && cp /opt/conda/lib/libdevice.10.bc /tmp/nvvm/libdevice/ -ENV XLA_FLAGS="--xla_gpu_cuda_data_dir=/tmp" -ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/opt/conda/lib -ENV PATH=${PATH}:/usr/local/nvidia/bin:/opt/conda/bin:/datasets/software/R2019a/sys/cuda/glnxa64/cuda/bin +# USER $NB_UID:$NB_GID +# RUN mkdir -p /tmp/nvvm && mkdir -p /tmp/nvvm/libdevice && cp /opt/conda/lib/libdevice.10.bc /tmp/nvvm/libdevice/ +# ENV XLA_FLAGS="--xla_gpu_cuda_data_dir=/tmp" +# ENV LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/opt/conda/lib +# ENV PATH=${PATH}:/usr/local/nvidia/bin:/opt/conda/bin:/datasets/software/R2019a/sys/cuda/glnxa64/cuda/bin # larcv2 build -ADD build_larcv2.sh /home/jovyan/build_larcv2.sh -RUN source build_larcv2.sh +# ADD build_larcv2.sh /home/jovyan/build_larcv2.sh +# RUN source build_larcv2.sh diff --git a/notebooks/environment.yml b/notebooks/environment.yml index 458c813..840c86b 100644 --- a/notebooks/environment.yml +++ b/notebooks/environment.yml @@ -4,7 +4,7 @@ channels: - pytorch - conda-forge dependencies: - - python=3.9 + - python=3.10.10 - numpy - uproot - tensorflow @@ -19,9 +19,10 @@ dependencies: - mplhep - tqdm - xgboost + - jupyter-book==0.15.1 + - jupyter_contrib_nbextensions==0.7.0 - pip - pip: - - jupyter-book - jetnet - gdown - spektral @@ -29,4 +30,3 @@ dependencies: - requests - ipywidgets - widgetsnbextension - - jupyter_contrib_nbextensions diff --git a/syllabus/syllabus.tex b/syllabus/syllabus.tex index d076a1f..0f7036e 100644 --- a/syllabus/syllabus.tex +++ b/syllabus/syllabus.tex @@ -142,7 +142,7 @@ \end{center} \noindent\textbf{Drop policy}: The lowest homework score is dropped automatically. -This drop policy is designed to account for any and all illnesses, family, medical, mental, or other emergencies. +This drop policy is designed to account for any illnesses, family, medical, mental, or other emergencies. If you have an extended emergency (e.g., a long hospital stay) that hinders your ability to turn complete assignments beyond the emergency policy allowance, contact the professor directly as soon as the situation arises. @@ -159,9 +159,9 @@ \noindent\textbf{Homework}: Each homework will consist of a set of conceptual and programming problems. The assignments will be submitted as Jupyter notebooks or GitHub repositories. -There will be a first deadline (on Fridays at 5:00pm) to submit a ``draft'' version of the homework, which will be graded based on effort. +There will be a first deadline (on Fridays at 8:00pm) to submit the homework, which will be graded based on effort and completeness. -There will be a second deadline (on Wednesdays at 5:00pm) to submit a ``final'' version of the homework, which will be graded based on effort and correctness. +There will be a second deadline (on Wednesdays at 8:00pm) to submit corrections for the homework, which will be graded based on effort and correctness. \begin{center} \rule{\textwidth}{0.5pt} @@ -171,7 +171,7 @@ For the final project, students will work in groups of $\sim$4 to reproduce or extend the results of an ML in physics research article. Some candidate articles are listed at the end of the syllabus. The final project deliverables are: (1) a 4-page paper on the project, (2) code provided as a public GitHub repository, (3) a 10-minute presentation by all members of the group during finals week, and (4) self and peer evaluations for group contributions. -Students will also be required to submit a 2-page written proposal for the project in Week 7. +Students will also be required to submit a 1-page written proposal for the project in Week 7. This is to ensure the project is feasible and to receive feedback from the instructors. \begin{center}