From a964e479743928ace3dcc6667c0e0bcc823034c3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 2 Dec 2024 09:59:35 +0100 Subject: [PATCH] Venv creation and uv support (#245) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * add empty requirements file for cuda * add requirements files and update pyproject toml * update pyproject * update installation in pyproject.toml * update readme and horovod installation script * update readme with horovod explanation * update horovod installation script * update readme with -e flag * fix linter readme errors * add more info to readme * trailing whitespace 🙃 * trailing whitespace 🙃 (again) * add draft of table of contents to readme * update readme toc * update readme toc again * add section about uv lock to readme * update toc of readme * fix errors in readme * add version numbers to packages in pyproject.toml * remove uv.lock (for now) * remove link from readme * put toc in html comment * remove toc, remove ds and horovod from reqs, add docs comment to pyproj * Itwinai jlab Docker image (#236) * Refactor Dockerfiles * Refactor container gen script * ADD jlab dockerfile * First working version of jlab container * ADD CMCC requirements * update dockerfiles * ADD nvconda and refactor * Update containers * ADD containers * ADD simple plus dockerfile * Update NV deps * Update CUDA * Add comment * Cleanup * Cleanup * UPDATE README * Refactor * Fix linter * Refactor dockerfiles and improve tests * Refactor * Refactor * Fix * Add first tests for HPC * First broken tests for HPC * Update tests and strategy * UPDATE tests * Update horovod tests * Update tests and jlab deps * Add MLFLow tracking URI * ADD distributed trainer tests * mpirun container deepspeed * Fix distributed strategy tests on multi-node * ADD srun launcher * Refactor jobscript * Cleanup * isort tests * Refactor scripts * Minor fixes * Add logging to file for all workers * Add jupyter base files * Add jupyter base files * spelling * Update provenance deps * Update DS version * Update prov docs * Cleanup * add nvidia dep * Remove incomplete work * update pyproject * ADD hadolit config file * FIX flag * Fix linters * Refactor * Update prov4ml * Update pytest CI * Minor fix * Incorporate feedback * Update Dockerfiles * Incorporate feedback * Update comments * Refactor tests * Virgo HDF5 file format (#240) * update virgo generated dataset to use hdf5 format * add functionality for selecting output location * set new data format as standard * make virgo work with new data loader and add progress bar * remove old generation files and add script for concatenating hdf5 files * remove old generation files and add script for concatenating hdf5 files * rename folder using hyphens * remove multiprocessing * add multiprocessing at correct place * update handling of seed and num processes * Gpu monitoring (#237) * add gpu utilization decorator and begin work on plots * add decorator for gpu energy utilization * Added config option to hpo script, styling (#235) * Update README.md * Update README.md * Update createEnvVega.sh * remove unused dist file * run black and isort to fix linting errors * remove redundant variable * remove trailing whitespace * fix issues from PR * fix import in eurac trainer * fix linting errors * update logging directory and pattern * update default pattern for gpu energy plots * fix isort linting * add support for none pattern and general cleanup * fix linting errors with black and isort * add configurable and dynamic wait and warmup times for the profiler * remove old plot * move horovod import * fix linting errors --------- Co-authored-by: Anna Lappe <153988542+annaelisalappe@users.noreply.github.com> Co-authored-by: Matteo Bunino <48362942+matbun@users.noreply.github.com> * Scalability test wall clock (#239) * add gpu utilization decorator and begin work on plots * add decorator for gpu energy utilization * Added config option to hpo script, styling (#235) * Update README.md * Update README.md * Update createEnvVega.sh * remove unused dist file * run black and isort to fix linting errors * temporary changes * remove redundant variable * add absolute time plot * remove trailing whitespace * remove redundant variable * remove trailing whitespace * begin implementation of backup * fix issues from PR * fix issues from PR * add backup to gpu monitoring * fix import in eurac trainer * cleanup backup mechanism slightly * fix linting errors * update logging directory and pattern * update default pattern for gpu energy plots * fix isort linting * add support for none pattern and general cleanup * fix linting errors with black and isort * fix import in eurac trainer * fix linting errors * update logging directory and pattern * update default pattern for gpu energy plots * fix isort linting * add support for none pattern and general cleanup * fix linting errors with black and isort * begin implementation of backup * add backup to gpu monitoring * add backup functionality to communication plot * rewrite epochtimetracker and refactor scalability plot code * cleanup scalability plot code * updating some epochtimetracker dependencies * add configurable and dynamic wait and warmup times for the profiler * temporary changes * add absolute time plot * begin implementation of backup * add backup to gpu monitoring * cleanup backup mechanism slightly * fix isort linting * add support for none pattern and general cleanup * fix linting errors with black and isort * begin implementation of backup * add backup functionality to communication plot * rewrite epochtimetracker and refactor scalability plot code * cleanup scalability plot code * updating some epochtimetracker dependencies * fix linting errors * fix more linting errors * add utilization percentage plot * run isort for linting * update default save path for metrics * add decorators to virgo and some cleanup * add contributions and cleanup * fix linting errors * change 'credits' to 'credit' * update communication plot style * update function names * update scalability function for a more streamlined approach * run isort * move horovod import * fix linting errors * add contributors --------- Co-authored-by: Anna Lappe <153988542+annaelisalappe@users.noreply.github.com> Co-authored-by: Matteo Bunino <48362942+matbun@users.noreply.github.com> * make virgo work with new data loader and add progress bar * add contributors * update ruff settings in pyproject * update virgo dataset concatenation * add isort option to ruff * break imports on purpose * break more imports to test * remove ruff config file * 😀 * test linter 😁 * remove comment in github workflows * add validation python to linter and make more mistakes * add linting errors to trainer * remove isort and flake8 and replace with ruff * update linters * run formatter on virgo folder * fix linting errors and stuff from PR * update config * change config for timing code * update profiler to use 'with' for context managing * fix profiler.py --------- Co-authored-by: Anna Lappe <153988542+annaelisalappe@users.noreply.github.com> Co-authored-by: Matteo Bunino <48362942+matbun@users.noreply.github.com> * add requirements files and update pyproject toml * update installation in pyproject.toml * add pytorch extra to horovod and remove redundant script * update readme tutorial with pip installation * add uv tutorial in separate file * fix linting errors * update horovod install script * fix dead link * update readme * add uv installation command to readme * add requirements files and update pyproject toml * update pyproject * update installation in pyproject.toml * add version numbers to packages in pyproject.toml * update horovod install script and add pip as dependency * formatting * fix linting * trailing whitespace * remove comment from readme * remove comments and small formatting difference * move uv tutorial under docs/ * update readme with nvidia and amd instead of linux * remove duplicate entries in pyproject and reformat distributed file * update readmes * separate horovod ds installation script into two files * fix linting errors and update dependencies * fix tests and update lockfile * fix linting errors * update installation scripts for testing * add local test command * add tf to installation in readme * add torch cuda to project dependencies * remove index from tutorial * remove unused comments and update tutorial --------- Co-authored-by: Matteo Bunino <48362942+matbun@users.noreply.github.com> Co-authored-by: Anna Lappe <153988542+annaelisalappe@users.noreply.github.com> --- Makefile | 7 +- README.md | 80 +- docs/uv-tutorial.md | 98 + env-files/tensorflow/generic_tf.sh | 91 +- env-files/torch/generic_torch.sh | 164 +- env-files/torch/horovod-deepspeed.slurm | 20 + .../torch/install-horovod-deepspeed-cuda.sh | 33 + pyproject.toml | 81 +- src/itwinai/torch/distributed.py | 12 +- src/itwinai/torch/profiling/profiler.py | 1 - tests/conftest.py | 15 +- tests/use-cases/test_3dgan.py | 10 +- tests/use-cases/test_cyclones.py | 13 +- tests/use-cases/test_mnist.py | 15 +- .../torch-scaling-test/README.md | 5 +- use-cases/eurac/config.yaml | 2 +- use-cases/eurac/requirements.txt | 1 + use-cases/eurac/trainer.py | 1 - use-cases/virgo/trainer.py | 9 +- uv.lock | 9274 +++++++++++++++++ 20 files changed, 9614 insertions(+), 318 deletions(-) create mode 100644 docs/uv-tutorial.md create mode 100644 env-files/torch/horovod-deepspeed.slurm create mode 100755 env-files/torch/install-horovod-deepspeed-cuda.sh create mode 100644 uv.lock diff --git a/Makefile b/Makefile index e612dd69..e03a7579 100644 --- a/Makefile +++ b/Makefile @@ -11,7 +11,7 @@ torch-env-cpu: env-files/torch/generic_torch.sh env ENV_NAME=.venv-pytorch \ NO_CUDA=1 \ bash -c 'bash env-files/torch/generic_torch.sh' - .venv-pytorch/bin/horovodrun --check-build + # .venv-pytorch/bin/horovodrun --check-build # Install TensorFlow env (GPU support) tensorflow-env: env-files/tensorflow/generic_tf.sh @@ -44,7 +44,10 @@ tf-env-vega: env-files/tensorflow/createEnvVegaTF.sh env-files/tensorflow/generi test: - PYTORCH_ENABLE_MPS_FALLBACK=1 .venv-pytorch/bin/pytest -v tests/ -m "not slurm" + .venv/bin/pytest -v tests/ + +test-local: + PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ -m "not hpc" test-jsc: tests/run_on_jsc.sh bash tests/run_on_jsc.sh diff --git a/README.md b/README.md index 9eb0cb92..778a15ae 100644 --- a/README.md +++ b/README.md @@ -128,10 +128,84 @@ git clone [--recurse-submodules] git@github.com:interTwin-eu/itwinai.git ### Install itwinai environment -You can create the -Python virtual environments using our predefined Makefile targets. +In this project, we are using `uv` as a project-wide package manager. Therefore, if +you are a developer, you should see the [uv tutorial](/docs/uv-tutorial.md) after reading +the following `pip` tutorial. -#### PyTorch (+ Lightning) virtual environment +#### Installation using pip + +##### Creating a venv + +You can install the `itwinai` environment for development using `pip`. First, however, +you would want to make a Python venv if you haven't already. Make sure you have +Python installed (on HPC you have to load it with `module load Python`), and then you +can create a venv with the following command: + +```bash +python -m venv +``` + +For example, if I wanted to create a venv in the directory `.venv` (which is useful if +you use e.g. `uv`), then I would do: + +```bash +python -m venv .venv +``` + +After this you can activate your venv using the following command: + +```bash +source .venv/bin/activate +``` + +Now anything you pip install will be installed in your venv and if you run any python +commands they will use the version from your venv. + +##### Installation of packages + +We provide some _extras_ that can be activated depending on which platform you are +using. + +- `macos`, `amd` or `nvidia` depending on which platform you use. Changes the version +of `prov4ML`. +- `dev` for development purposes. Includes libraries for testing and tensorboard etc. +- `torch` for installation with PyTorch. + +If you want to install PyTorch using CUDA then you also have to add an +`--extra-index-url` to the CUDA version that you want. Since you are developing the +library, you also want to enable the editable flag, `-e`, so that you don't have to +reinstall everything every time you make a change. If you are on HPC, then you will +usually want to add the `--no-cache-dir` flag to avoid filling up your `~/.cache` +directory, as you can very easily reach your disk quota otherwise. An example of a +complete command for installing as a developer on HPC with CUDA thus becomes: + +```bash +pip install -e ".[torch,dev,nvidia,tf]" \ + --no-cache-dir \ + --extra-index-url https://download.pytorch.org/whl/cu121 +``` + +If you wanted to install this locally on macOS (i.e. without CUDA) with PyTorch, you +would do the following instead: + +```bash +pip install -e ".[torch,dev,macos,tf]" +``` + + + +#### Horovod and DeepSpeed + +The above does not install `Horovod` and `DeepSpeed`, however, as they require a +specialized [script](env-files/torch/install-horovod-deepspeed-cuda.sh). If you do not +require CUDA, then you can install them using `pip` as follows: + +```bash +pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git +pip install --no-cache-dir --no-build-isolation deepspeed +``` + +#### PyTorch (+ Lightning) virtual environment with makefiles Makefile targets for environment installation: diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md new file mode 100644 index 00000000..fc240e2a --- /dev/null +++ b/docs/uv-tutorial.md @@ -0,0 +1,98 @@ +# Tutorial for using the uv package manager + +[uv](https://docs.astral.sh/uv/) is a Python package manager meant to act as a drop-in +replacement for `pip` (and many more tools). In this project, we use it to manage our +packages, similar to how `poetry` works. This is done using a lockfile called +`uv.lock`. + +## uv as a drop-in replacement for pip + +`uv` is a lot faster than `pip`, so we recommend installing packages from `PyPI` +with `uv pip install ` instead of `pip install `. You don't need to +change anything in your project to use this feature, as it works as a drop-in +replacement to `pip`. + +## uv as a project-wide package manager + +If you wish to use the `uv sync` and/or `uv lock` commands, which is how you use `uv` +to manage all your project packages, then note that these commands will only work +with the directory called `.venv` in the project directory. Sometimes, this can be a +bit annoying, especially with an existing venv, so we recommend using a +[symlink](https://en.wikipedia.org/wiki/Symbolic_link). If you need to have multiple +venvs that you want to switch between, you can update the symlink to whichever of them +you want to use at the moment. For SLURM scripts, you can hardcode them if need be. + +### Symlinking .venv + +To create a symlink between your venv and the `.venv` directory, you can use the +following command: + +```bash +ln -s +``` + +As an example, if I am in the `itwinai/` folder and my venv is called `envAI_juwels`, +then the following will create the wanted symlink: + +```bash +ln -s envAI_juwels .venv +``` + +### Installing from uv.lock + +> [!Warning] +> If `uv` creates your venv for you, the venv will not contain `pip`. However, you need +> to have `pip` installed to be able to run the installation scripts for `Horovod` and +> `DeepSpeed`, so we have included `pip` in the dependencies in `pyproject.toml`. + +To install from the `uv.lock` file into the `.venv` venv, you can do the following: + +```bash +uv sync +``` + +If the `uv.lock` file has optional dependencies (e.g. `macos` or `torch`), then these +can be added with the `--extra` flag as follows: + +```bash +uv sync --extra torch --extra macos +``` + +These will usually correspond to the optional dependencies in the `pyproject.toml`. In +particular, if you are a developer you would use one of the following two commands. If +you are on HPC with cuda, you would use: + +```bash +uv sync --no-cache --extra dev --extra nvidia --extra torch --extra tf +``` + +If you are developing on your local computer with macOS, then you would use: + +```bash +uv sync --extra torch --extra tf --extra dev --extra macos +``` + +### Updating the uv.lock file + +To update the project's `uv.lock` file with the dependencies of the project, you can +use the command: + +```bash +uv lock +``` + +This will create a `uv.lock` file if it doesn't already exist, using the dependencies +from the `pyproject.toml`. + +## Adding new packages to the project + +To add a new package to the project (i.e. to the `pyproject.toml` file) with `uv`, you +can use the following command: + +```bash +uv add +``` + +> [!Warning] +> This will add the package to your `.venv` venv, so make sure to have symlinked to +> this directory if you haven't already. diff --git a/env-files/tensorflow/generic_tf.sh b/env-files/tensorflow/generic_tf.sh index 008839af..0b5d216e 100644 --- a/env-files/tensorflow/generic_tf.sh +++ b/env-files/tensorflow/generic_tf.sh @@ -1,97 +1,18 @@ #!/bin/bash -# ENV VARIABLES: -# - ENV_NAME: set custom name for virtual env. Default: ".venv-tf" -# - NO_CUDA: if set, install without cuda support - -# Detect custom env name from env if [ -z "$ENV_NAME" ]; then ENV_NAME=".venv-tf" fi -if [ -z "$NO_CUDA" ]; then - echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA enabled)" -else - echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA disabled)" -fi - -# get python version -pver="$(python --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)" - -# use pyenv if exist -if [ -d "$HOME/.pyenv" ];then - export PYENV_ROOT="$HOME/.pyenv" - export PATH="$PYENV_ROOT/bin:$PATH" -fi +work_dir=$PWD -# set dir -cDir=$PWD - -# create environment -if [ -d "${cDir}/$ENV_NAME" ];then +# Create the python venv if it doesn't already exist +if [ -d "${work_dir}/$ENV_NAME" ];then echo "env $ENV_NAME already exists" - - source $ENV_NAME/bin/activate else python3 -m venv $ENV_NAME - - # activate env - source $ENV_NAME/bin/activate - - echo "$ENV_NAME environment is created in ${cDir}" -fi - -pip3 install --no-cache-dir --upgrade pip - -# get wheel -- setuptools extension -pip3 install --no-cache-dir wheel - -# install TF -if [ -f "${cDir}/$ENV_NAME/bin/tensorboard" ]; then - echo 'TF already installed' - echo -else - if [ -z "$NO_CUDA" ]; then - pip3 install tensorflow[and-cuda]==2.16.* --no-cache-dir - else - # CPU only installation - pip3 install tensorflow==2.16.* --no-cache-dir - fi -fi - -# CURRENTLY, horovod is not used with TF. Skipped. -# # install horovod -# if [ -f "${cDir}/$ENV_NAME/bin/horovodrun" ]; then -# echo 'Horovod already installed' -# echo -# else -# if [ -z "$NO_CUDA" ]; then -# export HOROVOD_GPU=CUDA -# export HOROVOD_GPU_OPERATIONS=NCCL -# export HOROVOD_WITH_TENSORFLOW=1 -# # export TMPDIR=${cDir} -# else -# # CPU only installation -# export HOROVOD_WITH_TENSORFLOW=1 -# # export TMPDIR=${cDir} -# fi - -# pip3 install --no-cache-dir horovod[tensorflow,keras] # --ignore-installed -# fi - -# WHEN USING TF >= 2.16: -# install legacy version of keras (2.16) -# Since TF 2.16, keras updated to 3.3, -# which leads to an error when more than 1 node is used -# https://keras.io/getting_started/ -pip3 install --no-cache-dir tf_keras==2.16.* - -# Install Pov4ML -if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -else - pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 + echo "$ENV_NAME environment is created in ${work_dir}" fi -# Install itwinai: MUST be last line of the script for the user installation script to work! -pip3 install --no-cache-dir -e .[dev] +source $ENV_NAME/bin/activate +pip install --no-cache-dir -e ".[dev,nvidia,tf]" diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index dc839e62..ac80b9f1 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -1,166 +1,20 @@ #!/bin/bash -# ENV VARIABLES: -# - ENV_NAME: set custom name for virtual env. Default: ".venv-pytorch" -# - NO_CUDA: if set, install without cuda support -# - PIP_INDEX_TORCH_CUDA: pip index to be used to install torch with CUDA. Defaults to https://download.pytorch.org/whl/cu121 -# Detect custom env name from env if [ -z "$ENV_NAME" ]; then ENV_NAME=".venv-pytorch" fi -if [ -z "$NO_CUDA" ]; then - echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA enabled)" -else - echo "Installing itwinai and its dependencies in '$ENV_NAME' virtual env (CUDA disabled)" -fi - -if [ -z "$PIP_INDEX_TORCH_CUDA" ]; then - PIP_INDEX_TORCH_CUDA="https://download.pytorch.org/whl/cu121" -fi - -# get python version -pver="$(python3 --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)" +work_dir=$PWD -# use pyenv if exist -if [ -d "$HOME/.pyenv" ];then - export PYENV_ROOT="$HOME/.pyenv" - export PATH="$PYENV_ROOT/bin:$PATH" -fi - -# set dir -cDir=$PWD - -# create environment -if [ -d "${cDir}/$ENV_NAME" ];then +# Create the python venv if it doesn't already exist +if [ -d "${work_dir}/$ENV_NAME" ];then echo "env $ENV_NAME already exists" - - source $ENV_NAME/bin/activate else python3 -m venv $ENV_NAME - - # activate env - source $ENV_NAME/bin/activate - - echo "$ENV_NAME environment is created in ${cDir}" -fi - -pip install --no-cache-dir --upgrade pip -pip install --no-cache-dir packaging wheel - -# Adding this constraint as numpy >= 2 seems to clash with DeepSpeed -pip install --no-cache-dir 'numpy<2.0.0' || exit 1 - -# install Torch -if [ -f "${cDir}/$ENV_NAME/bin/torchrun" ]; then - echo 'Torch already installed' -else - if [ -z "$NO_CUDA" ] ; then - pip install --no-cache-dir \ - 'torch==2.4.*' torchvision torchaudio --index-url "$PIP_INDEX_TORCH_CUDA" || exit 1 - else - # CPU only installation for MacOS - if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install --no-cache-dir \ - 'torch==2.4.*' torchvision torchaudio || exit 1 - else - # CPU only installation for other OSs - pip install --no-cache-dir \ - 'torch==2.4.*' torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu || exit 1 - fi - fi -fi - -# HPO - RayTune -if [ -f "${cDir}/$ENV_NAME/bin/ray" ]; then - echo 'Ray already installed' -else - if [[ "$OSTYPE" =~ ^darwin ]] ; then - echo 'Installation issues: Skipping Ray installation for MacOS' - else - pip install --no-cache-dir ray[tune] || exit 1 - fi -fi - -# install deepspeed -if [ -f "${cDir}/$ENV_NAME/bin/deepspeed" ]; then - echo 'DeepSpeed already installed' -else - if [ -z "$NO_CUDA" ]; then - export DS_BUILD_CCL_COMM=1 - export DS_BUILD_UTILS=1 - export DS_BUILD_AIO=1 - export DS_BUILD_FUSED_ADAM=1 - export DS_BUILD_FUSED_LAMB=1 - export DS_BUILD_TRANSFORMER=1 - export DS_BUILD_STOCHASTIC_TRANSFORMER=1 - export DS_BUILD_TRANSFORMER_INFERENCE=1 - fi - pip install --no-cache-dir py-cpuinfo || exit 1 - pip install --no-cache-dir deepspeed==0.15.* || exit 1 - - # fix .triton/autotune/Fp16Matmul_2d_kernel.pickle bug - line=$(cat -n $ENV_NAME/lib/python${pver}/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py | grep os.rename | awk '{print $1}' | head -n 1) - - # 'sed' is implemented differently on MacOS than on Linux (https://stackoverflow.com/questions/4247068/sed-command-with-i-option-failing-on-mac-but-works-on-linux) - if [[ "$OSTYPE" =~ ^darwin ]] ; then - sed -i '' "${line}s|^|#|" $ENV_NAME/lib/python${pver}/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py || exit 1 - else - sed -i "${line}s|^|#|" $ENV_NAME/lib/python${pver}/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py || exit 1 - fi -fi - -# install horovod -if [ -f "${cDir}/$ENV_NAME/bin/horovodrun" ]; then - echo 'Horovod already installed' -else - - if [ -z "$NO_CUDA" ]; then - # compiler vars - export LDSHARED="$CC -shared" && - export CMAKE_CXX_STANDARD=17 - - # CPU vars - export HOROVOD_MPI_THREADS_DISABLE=1 - export HOROVOD_CPU_OPERATIONS=MPI - - # GPU vars - export HOROVOD_GPU_ALLREDUCE=NCCL - export HOROVOD_NCCL_LINK=SHARED - export HOROVOD_NCCL_HOME=$EBROOTNCCL - - # Host language vars - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 - else - # CPU only installation - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 - fi - pip install --no-cache-dir git+https://github.com/horovod/horovod.git@3a31d93 || exit 1 -fi - -# get required libraries in reqs.txt -# if [ -f "${cDir}/$ENV_NAME/lib/python${pver}/site-packages/torchnlp/_third_party/weighted_random_sampler.py" ]; then - # echo 'required libs already exist' -# else -# pip install -r Scripts/reqs.txt --no-cache-dir - - # fix int bug: modify l.4 of /torchnlp/_third_party/weighted_random_sampler.py - # var='int_classes = int' - # sed -i .backup_file "4s|.*|$var|" \ - # ${cDir}/$ENV_NAME/lib/python${pver}/site-packages/torchnlp/_third_party/weighted_random_sampler.py || exit 1 - # Deleting unnecessary backup file - # rm ${cDir}/$ENV_NAME/lib/python${pver}/site-packages/torchnlp/_third_party/weighted_random_sampler.py.backup_file -# fi - -# Install Pov4ML -if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install --no-cache-dir "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -else - pip install --no-cache-dir "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 + echo "$ENV_NAME environment is created in ${work_dir}" fi -# Install itwinai: MUST be last line of the script for the user installation script to work! -pip install --no-cache-dir -e .[torch,dev] || exit 1 \ No newline at end of file +# Activate the venv and then install itwinai as editable +source $ENV_NAME/bin/activate +pip install -e ".[torch,tf,dev,nvidia]" \ + --no-cache-dir \ + --extra-index-url https://download.pytorch.org/whl/cu121 diff --git a/env-files/torch/horovod-deepspeed.slurm b/env-files/torch/horovod-deepspeed.slurm new file mode 100644 index 00000000..00e9934f --- /dev/null +++ b/env-files/torch/horovod-deepspeed.slurm @@ -0,0 +1,20 @@ +#!/bin/bash + +# Job configuration +#SBATCH --job-name=setup_venv +#SBATCH --account=intertwin +#SBATCH --output=horovod_ds_installation.out +#SBATCH --error=horovod_ds_installation.err +#SBATCH --time=00:30:00 + +# Resources allocation +#SBATCH --partition=develbooster +#SBATCH --nodes=1 +#SBATCH --gres=gpu + +ml --force purge +ml Stages/2024 GCC OpenMPI CUDA/12 cuDNN MPI-settings/CUDA +ml Python/3.11.3 CMake HDF5 PnetCDF libaio mpi4py git Clang + +source .venv/bin/activate +source env-files/torch/install-horovod-deepspeed-cuda.sh diff --git a/env-files/torch/install-horovod-deepspeed-cuda.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh new file mode 100755 index 00000000..f596ae83 --- /dev/null +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -0,0 +1,33 @@ +#!/bin/bash + +# DeepSpeed variables +export DS_BUILD_CCL_COMM=1 +export DS_BUILD_UTILS=1 +export DS_BUILD_AIO=1 +export DS_BUILD_FUSED_ADAM=1 +export DS_BUILD_FUSED_LAMB=1 +export DS_BUILD_TRANSFORMER=1 +export DS_BUILD_STOCHASTIC_TRANSFORMER=1 +export DS_BUILD_TRANSFORMER_INFERENCE=1 + +# We do --no-cache-dir because the .cache dir eats our HPC quota :( +pip install --no-cache-dir --no-build-isolation "deepspeed==0.15.*" || exit 1 + +# Horovod variables +export LDSHARED="$CC -shared" && +export CMAKE_CXX_STANDARD=17 + +export HOROVOD_MPI_THREADS_DISABLE=1 +export HOROVOD_CPU_OPERATIONS=MPI + +export HOROVOD_GPU_ALLREDUCE=NCCL +export HOROVOD_NCCL_LINK=SHARED +export HOROVOD_NCCL_HOME=$EBROOTNCCL + +export HOROVOD_WITH_PYTORCH=1 +export HOROVOD_WITHOUT_TENSORFLOW=1 +export HOROVOD_WITHOUT_MXNET=1 + +pip install --no-cache-dir 'horovod[pytorch] @ git+https://github.com/horovod/horovod' || exit 1 + +echo "Finished Horovod and DeepSpeed installation script!" diff --git a/pyproject.toml b/pyproject.toml index 87749115..73af1099 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -25,38 +25,50 @@ classifiers = [ ] dependencies = [ - "wandb", - "mlflow", - "jsonargparse[signatures]", - "pyyaml", - "omegaconf", "rich>=13.5.3", "typer>=0.9.0", - "wheel", + "numpy<2.0.0", + "wandb>=0.18.7", + "mlflow>=2.17.2", + "wheel>=0.45.0", + "seaborn>=0.13.2", + "py-cpuinfo>=9.0.0", + "packaging", "pydantic", + "pyyaml>=6.0.2", + "omegaconf>=2.3.0", + "jsonargparse[signatures]>=4.34.0", + "matplotlib>=3.9.2", + "pip>=24.3.1", "prov4ml@git+https://github.com/matbun/ProvML@new-main", - "pandas", - "seaborn", + "ray", + "prov", ] -# dynamic = ["version", "description"] - [project.optional-dependencies] torch = [ "torch==2.4.*", "lightning==2.*", - "torchmetrics>=1.6.0", - "torchvision>=0.19.1", - "torchaudio>=2.4.1", + "torchmetrics", + "torchvision", + "torchaudio", +] +tf = [ + "tensorflow==2.16.*", + "tf_keras==2.16.*" +] +tf-cuda = [ + "tensorflow[and-cuda]==2.16.*", + "tf_keras==2.16.*" ] + dev = [ - "pytest>=7.4.2", - "pytest-mock>=3.11.1", - "pytest-cov>=4.1.0", - "ipykernel", - "ipython", - "isort", - "tensorflow==2.16.*", # needed by tests on tensorboard + "pytest>=7.4.2", + "pytest-mock>=3.11.1", + "pytest-cov>=4.1.0", + "ipykernel>=6.29.5", + "ipython", + "isort>=5.13.2", ] docs = [ "sphinx-rtd-theme==2.0.0", @@ -67,7 +79,7 @@ docs = [ ] macos = ["prov4ml[apple]@git+https://github.com/matbun/ProvML@new-main"] nvidia = ["prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main"] -amd = ["prov4ml[amd]@git+https://github.com/matbun/ProvML@new-main"] +# amd = ["prov4ml[amd]@git+https://github.com/matbun/ProvML@new-main"] [project.urls] Homepage = "https://www.intertwin.eu/" @@ -95,9 +107,30 @@ markers = [ "memory_heavy: high memory footprint. (deselect with '-m \"not heavy_memory\"')", ] -# [tool.isort] -# profile = "black" -# known_first_party = ["itwinai"] + +[tool.uv] +# This is how you can force uv to accept conflicting extras +conflicts = [ + [ + { extra = "tf-cuda" }, + { extra = "torch" }, + ], +] + +# Use PyTorch with CUDA for anything that is not macos +[tool.uv.sources] +torch = [ + { index = "pytorch-cu121", marker = "platform_system != 'Darwin'"}, +] +torchvision = [ + { index = "pytorch-cu121", marker = "platform_system != 'Darwin'"}, +] + +# Specific index for pytorch +[[tool.uv.index]] +name = "pytorch-cu121" +url = "https://download.pytorch.org/whl/cu121" +explicit = true # Ruff configuration: https://docs.astral.sh/ruff/configuration/ [tool.ruff] diff --git a/src/itwinai/torch/distributed.py b/src/itwinai/torch/distributed.py index f356bbb4..e3fea41a 100644 --- a/src/itwinai/torch/distributed.py +++ b/src/itwinai/torch/distributed.py @@ -318,7 +318,9 @@ def create_dataloader( shuffle=shuffle, ) elif not isinstance(sampler, DistributedSampler): - raise RuntimeError("User-provided sampler must implement DistributedSampler.") + raise RuntimeError( + "User-provided sampler must implement DistributedSampler." + ) # shuffle and batch_sampler must be unset return DataLoader( dataset=dataset, @@ -695,7 +697,9 @@ def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: dist.gather_object(obj, dst=dst_rank) @check_initialized - def gather(self, tensor: torch.Tensor, dst_rank: int = 0) -> Optional[List[torch.Tensor]]: + def gather( + self, tensor: torch.Tensor, dst_rank: int = 0 + ) -> Optional[List[torch.Tensor]]: """Gathers a tensor from the whole group in a list (to all workers). @@ -874,7 +878,9 @@ def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[list[Any]]: return result @check_initialized - def gather(self, tensor: torch.Tensor, dst_rank: int = 0) -> Optional[List[torch.Tensor]]: + def gather( + self, tensor: torch.Tensor, dst_rank: int = 0 + ) -> Optional[List[torch.Tensor]]: """Gathers a tensor from the whole group in a list (to all workers). Under the hood it relies on allgather as gather is not supported by Horovod. diff --git a/src/itwinai/torch/profiling/profiler.py b/src/itwinai/torch/profiling/profiler.py index ccebc3ac..9f003b3b 100644 --- a/src/itwinai/torch/profiling/profiler.py +++ b/src/itwinai/torch/profiling/profiler.py @@ -107,7 +107,6 @@ def profiled_method(self: TorchTrainer, *args, **kwargs) -> Any: # Extracting and storing the profiling data key_averages = profiler.key_averages() - # strategy.barrier() profiling_dataframe = gather_profiling_data(key_averages=key_averages) profiling_dataframe["strategy"] = strategy_name profiling_dataframe["num_gpus"] = num_gpus_global diff --git a/tests/conftest.py b/tests/conftest.py index 0575e30e..b1975f17 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -8,6 +8,7 @@ # -------------------------------------------------------------------------------------- import os +from pathlib import Path import pytest @@ -20,11 +21,8 @@ def torch_env() -> str: Returns absolute path to torch virtual environment. """ - if os.environ.get("TORCH_ENV") is None: - env_p = "./.venv-pytorch" - else: - env_p = str(os.environ.get("TORCH_ENV")) - return os.path.abspath(env_p) + env_path = Path(os.environ.get("TORCH_ENV", "./.venv-pytorch")) + return str(env_path.resolve()) @pytest.fixture @@ -35,8 +33,5 @@ def tf_env() -> str: Returns absolute path to torch virtual environment. """ - if os.environ.get("TF_ENV") is None: - env_p = "./.venv-tf" - else: - env_p = str(os.environ.get("TF_ENV")) - return os.path.abspath(env_p) + env_path = Path(os.environ.get("TF_ENV", "./.venv-tf")) + return str(env_path.resolve()) diff --git a/tests/use-cases/test_3dgan.py b/tests/use-cases/test_3dgan.py index c813522a..b7968a2a 100644 --- a/tests/use-cases/test_3dgan.py +++ b/tests/use-cases/test_3dgan.py @@ -38,10 +38,7 @@ def test_3dgan_train(torch_env, install_requirements): downloading it again. """ install_requirements(CERN_PATH, torch_env) - if os.environ.get("CERN_DATASET"): - dataset_path = os.environ.get("CERN_DATASET") - else: - dataset_path = DEFAULT_DATASET_PATH + dataset_path = os.environ.get("CERN_DATASET", DEFAULT_DATASET_PATH) conf = (CERN_PATH / "config.yaml").resolve() cmd = ( f"{torch_env}/bin/itwinai exec-pipeline " @@ -72,10 +69,7 @@ def test_3dgan_inference( install_requirements(CERN_PATH, torch_env) # Test inference - if os.environ.get("CERN_DATASET"): - dataset_path = os.environ.get("CERN_DATASET") - else: - dataset_path = DEFAULT_DATASET_PATH + dataset_path = os.environ.get("CERN_DATASET", DEFAULT_DATASET_PATH) conf = (CERN_PATH / "config.yaml").resolve() exec = (CERN_PATH / "create_inference_sample.py").resolve() diff --git a/tests/use-cases/test_cyclones.py b/tests/use-cases/test_cyclones.py index b8b1c64d..c05e3d63 100644 --- a/tests/use-cases/test_cyclones.py +++ b/tests/use-cases/test_cyclones.py @@ -43,12 +43,11 @@ def test_cyclones_train_tf(tf_env, install_requirements): """ # TODO: create a small sample dataset for tests only install_requirements(CYCLONES_PATH, tf_env) - if os.environ.get("CMCCC_DATASET"): - dataset_path = os.environ.get("CMCCC_DATASET") - else: - dataset_path = "./data/tmp_data" - pipe = os.path.join(os.path.abspath(CYCLONES_PATH), "pipeline.yaml") - train = os.path.join(os.path.abspath(CYCLONES_PATH), "train.py") - cmd = f"{tf_env}/bin/python {train} " f"-p {pipe} --data_path {dataset_path}" + + dataset_path = os.environ.get("CMCCC_DATASET", "./data/tmp_data") + pipe = CYCLONES_PATH / "pipeline.yaml" + train = CYCLONES_PATH / "train.py" + + cmd = f"{tf_env}/bin/python {train.resolve()} " f"-p {pipe.resolve()} --data_path {dataset_path}" with tempfile.TemporaryDirectory() as tmpdirname: subprocess.run(cmd.split(), check=True, cwd=tmpdirname) diff --git a/tests/use-cases/test_mnist.py b/tests/use-cases/test_mnist.py index 98e0d943..7d6fe753 100644 --- a/tests/use-cases/test_mnist.py +++ b/tests/use-cases/test_mnist.py @@ -59,10 +59,8 @@ def test_mnist_train_torch(torch_env, install_requirements): """ install_requirements(TORCH_PATH, torch_env) - if os.environ.get("MNIST_DATASET"): - dataset_path = os.environ.get("MNIST_DATASET") - else: - dataset_path = DEFAULT_MNIST_DATASET + dataset_path = os.environ.get("MNIST_DATASET", DEFAULT_MNIST_DATASET) + conf = (TORCH_PATH / "config.yaml").resolve() cmd = ( f"{torch_env}/bin/itwinai exec-pipeline " @@ -108,10 +106,7 @@ def test_mnist_train_torch_lightning(torch_env, install_requirements): """ install_requirements(LIGHTNING_PATH, torch_env) - if os.environ.get("MNIST_DATASET"): - dataset_path = os.environ.get("MNIST_DATASET") - else: - dataset_path = DEFAULT_MNIST_DATASET + dataset_path = os.environ.get("MNIST_DATASET", DEFAULT_MNIST_DATASET) conf = (LIGHTNING_PATH / "config.yaml").resolve() cmd = ( f"{torch_env}/bin/itwinai exec-pipeline " @@ -128,7 +123,7 @@ def test_mnist_train_tf(tf_env, install_requirements): Test MNIST tensorflow trainer by running it end-to-end. """ install_requirements(TF_PATH, tf_env) - conf = os.path.join(os.path.abspath(TF_PATH), "pipeline.yaml") - cmd = f"{tf_env}/bin/itwinai exec-pipeline " f"--config {conf} --pipe-key pipeline" + conf = TF_PATH / "pipeline.yaml" + cmd = f"{tf_env}/bin/itwinai exec-pipeline " f"--config {conf.resolve()} --pipe-key pipeline" with tempfile.TemporaryDirectory() as temp_dir: subprocess.run(cmd.split(), check=True, cwd=temp_dir) diff --git a/tutorials/distributed-ml/torch-scaling-test/README.md b/tutorials/distributed-ml/torch-scaling-test/README.md index 1d61ab5e..81adfa0d 100644 --- a/tutorials/distributed-ml/torch-scaling-test/README.md +++ b/tutorials/distributed-ml/torch-scaling-test/README.md @@ -34,9 +34,8 @@ python ddp_trainer.py -c config/base.yaml -c config/ddp.yaml --log-int 42 ## Run a single training Training runs are meant to be submitted via SLURM, from a unified job script file: -`slurm.sh`. -You can select the distributed training algorithm and provide the command to execute -setting SLURM environment variables using the `--export` option: +`slurm.sh`. You can select the distributed training algorithm and provide the command +to execute setting SLURM environment variables using the `--export` option: ```bash # Launch a distributed training setup with Torch DDP diff --git a/use-cases/eurac/config.yaml b/use-cases/eurac/config.yaml index a384efce..571a6fe1 100644 --- a/use-cases/eurac/config.yaml +++ b/use-cases/eurac/config.yaml @@ -18,7 +18,7 @@ tmp_stats: /p/scratch/intertwin/datasets/eurac/stats experiment: "drought use case lstm" run_name: "alps_test" -epochs: 4 +epochs: 5 random_seed: 1010 lr: 0.001 batch_size: 256 diff --git a/use-cases/eurac/requirements.txt b/use-cases/eurac/requirements.txt index 2d134c28..5b35ca1b 100644 --- a/use-cases/eurac/requirements.txt +++ b/use-cases/eurac/requirements.txt @@ -4,3 +4,4 @@ tqdm cf_xarray requests aiohttp +ray diff --git a/use-cases/eurac/trainer.py b/use-cases/eurac/trainer.py index 30b57c7b..223cafe0 100644 --- a/use-cases/eurac/trainer.py +++ b/use-cases/eurac/trainer.py @@ -37,7 +37,6 @@ NonDistributedStrategy, TorchDDPStrategy, ) -from itwinai.torch.monitoring.monitoring import measure_gpu_utilization from itwinai.torch.profiling.profiler import profile_torch_trainer from itwinai.torch.trainer import TorchTrainer from itwinai.torch.type import Metric diff --git a/use-cases/virgo/trainer.py b/use-cases/virgo/trainer.py index 69ee7964..b249bd0a 100644 --- a/use-cases/virgo/trainer.py +++ b/use-cases/virgo/trainer.py @@ -14,10 +14,8 @@ import time from pathlib import Path from timeit import default_timer as timer -from typing import Dict, Literal, Optional, Union, Tuple, Any +from typing import Any, Dict, Literal, Optional, Tuple, Union -from itwinai.distributed import suppress_workers_print -from itwinai.torch.profiling.profiler import profile_torch_trainer import numpy as np import torch import torch.nn as nn @@ -25,9 +23,11 @@ from torch.utils.data import Dataset, TensorDataset from tqdm import tqdm +from itwinai.distributed import suppress_workers_print from itwinai.loggers import EpochTimeTracker, Logger from itwinai.torch.config import TrainingConfiguration from itwinai.torch.distributed import DeepSpeedStrategy +from itwinai.torch.profiling.profiler import profile_torch_trainer from itwinai.torch.trainer import TorchTrainer from src.model import Decoder, Decoder_2d_deep, GeneratorResNet, UNet from src.utils import init_weights @@ -43,10 +43,9 @@ class VirgoTrainingConfiguration(TrainingConfiguration): #: Generator to train. Defaults to "unet". generator: Literal["simple", "deep", "resnet", "unet"] = "unet" - class NoiseGeneratorTrainer(TorchTrainer): def __init__( - self, + self, num_epochs: int = 2, config: Union[Dict, TrainingConfiguration] | None = None, strategy: Optional[Literal["ddp", "deepspeed", "horovod"]] = "ddp", diff --git a/uv.lock b/uv.lock new file mode 100644 index 00000000..86ba2e1a --- /dev/null +++ b/uv.lock @@ -0,0 +1,9274 @@ +version = 1 +requires-python = ">=3.10" +resolution-markers = [ + "python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system == 'Darwin' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version < '3.11' and platform_system == 'Darwin' and sys_platform == 'linux'", + "python_full_version < '3.11' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version < '3.11' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version == '3.11.*' and platform_system == 'Darwin' and sys_platform == 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version == '3.11.*' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version >= '3.12' and platform_system != 'Darwin' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version >= '3.12' and platform_system == 'Darwin' and sys_platform == 'linux'", + "python_full_version >= '3.12' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version >= '3.12' and platform_system != 'Windows' and sys_platform == 'linux'", + "python_full_version < '3.11' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version == '3.11.*' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.12' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version < '3.11' and platform_system == 'Windows' and sys_platform == 'linux'", + "python_full_version < '3.11' and 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