From fa3dc1ffe7baf0ee76d1d3f90e01dcec41237ee7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 15:36:55 +0100 Subject: [PATCH 01/59] add empty requirements file for cuda --- env-files/torch/requirements-cuda.txt | 2 ++ 1 file changed, 2 insertions(+) create mode 100644 env-files/torch/requirements-cuda.txt diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt new file mode 100644 index 000000000..780454964 --- /dev/null +++ b/env-files/torch/requirements-cuda.txt @@ -0,0 +1,2 @@ +numpy<2.0.0 +torch==2.4 From e9babf9c84c96199be215ca49c8dae88db9db5e0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 17:10:26 +0100 Subject: [PATCH 02/59] add requirements files and update pyproject toml --- env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 6 +++-- env-files/torch/requirements-macos.txt | 5 ++++ pyproject.toml | 34 +++++++++++++++++--------- 4 files changed, 31 insertions(+), 14 deletions(-) create mode 100644 env-files/torch/requirements-cpu.txt create mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt new file mode 100644 index 000000000..e69de29bb diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt index 780454964..00d03da8a 100644 --- a/env-files/torch/requirements-cuda.txt +++ b/env-files/torch/requirements-cuda.txt @@ -1,2 +1,4 @@ -numpy<2.0.0 -torch==2.4 + +torch==2.4.* +torchvision +torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt new file mode 100644 index 000000000..38a99869c --- /dev/null +++ b/env-files/torch/requirements-macos.txt @@ -0,0 +1,5 @@ +torch==2.4.* +torchvision +torchaudio +py-cpuinfo +prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' diff --git a/pyproject.toml b/pyproject.toml index b5a8af05f..7f920e858 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,24 +42,16 @@ dependencies = [ # "prov4ml@git+https://github.com/HPCI-Lab/ProvML@main", # Prov4ML # "prov4ml@git+https://github.com/matbun/ProvML@main", "pandas", - "seaborn" + "seaborn", + "deepspeed", + "py-cpuinfo", + "numpy<2.0.0", ] # dynamic = ["version", "description"] [project.optional-dependencies] - -# Torch should be already installed, but it is specified here to -# prevent itwinai dependencies from cheing its version. torch = ["lightning==2.*", "torchmetrics"] -# torch-cpu = [ -# "torch==2.1.*", -# "torchvision", -# "torchaudio", -# "lightning", -# "torchmetrics", -# "deepspeed", -# ] dev = [ "pytest>=7.4.2", "pytest-mock>=3.11.1", @@ -69,6 +61,21 @@ dev = [ "isort", "tensorflow==2.16.*", # needed by tests on tensorboard ] +linux = [] +macos = [ + "torch==2.4.*", + "torchvision", + "torchaudio", + "py-cpuinfo", +] +cuda = [ + # "torch==2.4.* @ https://download.pytorch.org/whl/cu121", + # "torchvision @ https://download.pytorch.org/whl/cu121", + # "torchaudio @ https://download.pytorch.org/whl/cu121", + "py-cpuinfo", + "horovod" +] + [project.urls] Homepage = "https://www.intertwin.eu/" @@ -96,3 +103,6 @@ markers = [ [tool.isort] profile = "black" known_first_party = ["itwinai"] + +# [[tool.uv.index]] +# url = "https://download.pytorch.org/whl/cpu" From e994bf41e38ed1b1b48bb23cf1e21e96a12d7557 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 18:02:14 +0100 Subject: [PATCH 03/59] update pyproject --- pyproject.toml | 21 +++------------------ 1 file changed, 3 insertions(+), 18 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 7f920e858..9c324574b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -46,6 +46,9 @@ dependencies = [ "deepspeed", "py-cpuinfo", "numpy<2.0.0", + "torch==2.4.*", + "torchvision", + "torchaudio", ] # dynamic = ["version", "description"] @@ -61,21 +64,6 @@ dev = [ "isort", "tensorflow==2.16.*", # needed by tests on tensorboard ] -linux = [] -macos = [ - "torch==2.4.*", - "torchvision", - "torchaudio", - "py-cpuinfo", -] -cuda = [ - # "torch==2.4.* @ https://download.pytorch.org/whl/cu121", - # "torchvision @ https://download.pytorch.org/whl/cu121", - # "torchaudio @ https://download.pytorch.org/whl/cu121", - "py-cpuinfo", - "horovod" -] - [project.urls] Homepage = "https://www.intertwin.eu/" @@ -103,6 +91,3 @@ markers = [ [tool.isort] profile = "black" known_first_party = ["itwinai"] - -# [[tool.uv.index]] -# url = "https://download.pytorch.org/whl/cpu" From 4b32a050b062e6d53d5547e06e17aacbb388650e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:23:54 +0100 Subject: [PATCH 04/59] update installation in pyproject.toml --- env-files/torch/generic_torch.sh | 14 +++-------- env-files/torch/install-horovod.sh | 34 ++++++++++++++++++++++++++ env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 4 --- env-files/torch/requirements-macos.txt | 5 ---- pyproject.toml | 9 +++++++ 6 files changed, 47 insertions(+), 19 deletions(-) create mode 100755 env-files/torch/install-horovod.sh delete mode 100644 env-files/torch/requirements-cpu.txt delete mode 100644 env-files/torch/requirements-cuda.txt delete mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index 2b5287277..500cad08d 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -127,17 +127,11 @@ else export HOROVOD_GPU_ALLREDUCE=NCCL export HOROVOD_NCCL_LINK=SHARED export HOROVOD_NCCL_HOME=$EBROOTNCCL - - # Host language vars - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 - else - # CPU only installation - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 fi + # Host language vars + export HOROVOD_WITH_PYTORCH=1 + export HOROVOD_WITHOUT_TENSORFLOW=1 + export HOROVOD_WITHOUT_MXNET=1 # # need to modify for torch 2.1.0 # git clone --recurse-submodules https://github.com/horovod/horovod.git diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh new file mode 100755 index 000000000..2a6c679d8 --- /dev/null +++ b/env-files/torch/install-horovod.sh @@ -0,0 +1,34 @@ +#!/bin/bash + +# Job configuration +#SBATCH --job-name=setup_venv +#SBATCH --account=intertwin +#SBATCH --output=logs_slurm/job.out +#SBATCH --error=logs_slurm/job.err +#SBATCH --time=00:10:00 + +# Resources allocation +#SBATCH --partition=develbooster +#SBATCH --nodes=1 +#SBATCH --gres=gpu + +ml --force purge +ml Stages/2024 GCC OpenMPI CUDA/12 cuDNN MPI-settings/CUDA +ml Python CMake HDF5 PnetCDF libaio mpi4py + +source .venv/bin/activate +export LDSHARED="$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 + +uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt deleted file mode 100644 index e69de29bb..000000000 diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt deleted file mode 100644 index 00d03da8a..000000000 --- a/env-files/torch/requirements-cuda.txt +++ /dev/null @@ -1,4 +0,0 @@ - -torch==2.4.* -torchvision -torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt deleted file mode 100644 index 38a99869c..000000000 --- a/env-files/torch/requirements-macos.txt +++ /dev/null @@ -1,5 +0,0 @@ -torch==2.4.* -torchvision -torchaudio -py-cpuinfo -prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' diff --git a/pyproject.toml b/pyproject.toml index 9c324574b..a62da6dfb 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,11 +39,14 @@ dependencies = [ "typer>=0.9.0", "wheel", "pydantic", + "packaging", # "prov4ml@git+https://github.com/HPCI-Lab/ProvML@main", # Prov4ML # "prov4ml@git+https://github.com/matbun/ProvML@main", "pandas", "seaborn", "deepspeed", + # "setuptools", + # "horovod", "py-cpuinfo", "numpy<2.0.0", "torch==2.4.*", @@ -64,6 +67,12 @@ dev = [ "isort", "tensorflow==2.16.*", # needed by tests on tensorboard ] +macos = [ + "prov4ml[apple]@git+https://github.com/matbun/ProvML" +] +linux = [ + "prov4ml[linux]@git+https://github.com/matbun/ProvML" +] [project.urls] Homepage = "https://www.intertwin.eu/" From 39e580162e26b752e2c9b50e46de483d6f9a85d4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:41:23 +0100 Subject: [PATCH 05/59] update readme and horovod installation script --- README.md | 26 ++++++++++++++++++++++++++ env-files/torch/install-horovod.sh | 2 +- 2 files changed, 27 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index bdd31ca1b..470611adb 100644 --- a/README.md +++ b/README.md @@ -131,6 +131,32 @@ git clone [--recurse-submodules] git@github.com:interTwin-eu/itwinai.git You can create the Python virtual environments using our predefined Makefile targets. +#### Installation with pip or uv +You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. +For MacOS, you would e.g. use no wheel. For cuda: +``` +pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +``` +For CPU: +``` +pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu +``` +With no wheel (e.g. MacOS): +``` +pip install . --no-cache-dir +``` + +If you want to use `uv`, which will significantly speed up the installation, you can +prepend `uv` to the `pip` command and it will work in the same way. This assumes that +you already have `uv` installed on your system. An example: +``` +uv pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +``` + +> [!NOTE] +> It is possible to not use `--no-cache-dir` on a local computer, but on HPC systems we +> recommend using it in order to not fill up your `.cache` directory. + #### PyTorch (+ Lightning) virtual environment Makefile targets for environment installation: diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh index 2a6c679d8..da602b924 100755 --- a/env-files/torch/install-horovod.sh +++ b/env-files/torch/install-horovod.sh @@ -14,7 +14,7 @@ ml --force purge ml Stages/2024 GCC OpenMPI CUDA/12 cuDNN MPI-settings/CUDA -ml Python CMake HDF5 PnetCDF libaio mpi4py +ml Python CMake HDF5 PnetCDF libaio mpi4py git source .venv/bin/activate export LDSHARED="$CC -shared" && From c9d786b8f7bc63a1948d7dc3daac6d8912bc7be6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:46:20 +0100 Subject: [PATCH 06/59] update readme with horovod explanation --- README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index 470611adb..8765f01c9 100644 --- a/README.md +++ b/README.md @@ -153,6 +153,13 @@ you already have `uv` installed on your system. An example: uv pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` +This does not install `Horovod`, however, as it requires a specialized +[script](env-files/torch/install-horovod.sh). If you do not require Cuda, then you +can install `Horovod` with the last part of the aforementioned script, i.e.: +``` +pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git +``` + > [!NOTE] > It is possible to not use `--no-cache-dir` on a local computer, but on HPC systems we > recommend using it in order to not fill up your `.cache` directory. From 8932f36f6488f11b485edf5996cfd9faac1ef3ef Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 10:32:16 +0100 Subject: [PATCH 07/59] update horovod installation script --- ...d.sh => install-horovod-deepspeed-cuda.sh} | 22 +- uv.lock | 6656 +++++++++++++++++ 2 files changed, 6674 insertions(+), 4 deletions(-) rename env-files/torch/{install-horovod.sh => install-horovod-deepspeed-cuda.sh} (58%) create mode 100644 uv.lock diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh similarity index 58% rename from env-files/torch/install-horovod.sh rename to env-files/torch/install-horovod-deepspeed-cuda.sh index da602b924..2b0719510 100755 --- a/env-files/torch/install-horovod.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -3,9 +3,9 @@ # Job configuration #SBATCH --job-name=setup_venv #SBATCH --account=intertwin -#SBATCH --output=logs_slurm/job.out -#SBATCH --error=logs_slurm/job.err -#SBATCH --time=00:10:00 +#SBATCH --output=horovod_ds_installation.out +#SBATCH --error=horovod_ds_installation.err +#SBATCH --time=00:30:00 # Resources allocation #SBATCH --partition=develbooster @@ -14,9 +14,11 @@ ml --force purge ml Stages/2024 GCC OpenMPI CUDA/12 cuDNN MPI-settings/CUDA -ml Python CMake HDF5 PnetCDF libaio mpi4py git +ml Python CMake HDF5 PnetCDF libaio mpi4py git Clang source .venv/bin/activate + +# Horovod variables export LDSHARED="$CC -shared" && export CMAKE_CXX_STANDARD=17 @@ -32,3 +34,15 @@ export HOROVOD_WITHOUT_TENSORFLOW=1 export HOROVOD_WITHOUT_MXNET=1 uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git + +# 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 + +uv pip install --no-cache-dir --no-build-isolation deepspeed diff --git a/uv.lock b/uv.lock new file mode 100644 index 000000000..979a00165 --- /dev/null +++ b/uv.lock @@ -0,0 +1,6656 @@ +version = 1 +requires-python = ">=3.10" +resolution-markers = [ + "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 >= '3.13' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.13' 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targets. You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. For MacOS, you would e.g. use no wheel. For cuda: ``` -pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` For CPU: ``` -pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu +pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu ``` With no wheel (e.g. MacOS): ``` -pip install . --no-cache-dir +pip install -e . --no-cache-dir ``` +> [!NOTE] +> We use `-e` here because we are in development mode and thus want any changes to +> immediately be applied to our venv. + If you want to use `uv`, which will significantly speed up the installation, you can prepend `uv` to the `pip` command and it will work in the same way. This assumes that you already have `uv` installed on your system. An example: From 0d588ad44299038badfdf122ee2b0faca00bbb45 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 14:12:51 +0100 Subject: [PATCH 09/59] fix linter readme errors --- README.md | 23 ++++++++++++++--------- 1 file changed, 14 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index d0d61f708..d307076aa 100644 --- a/README.md +++ b/README.md @@ -133,34 +133,39 @@ Python virtual environments using our predefined Makefile targets. #### Installation with pip or uv You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. -For MacOS, you would e.g. use no wheel. For cuda: -``` +For macOS, you would e.g. use no wheel. For cuda: + +```bash pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` For CPU: -``` + +```bash pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu ``` With no wheel (e.g. MacOS): -``` + +```bash pip install -e . --no-cache-dir ``` > [!NOTE] -> We use `-e` here because we are in development mode and thus want any changes to -> immediately be applied to our venv. +> We use `-e` here because we are in development mode and thus want any changes to +> immediately be applied to our venv. If you want to use `uv`, which will significantly speed up the installation, you can prepend `uv` to the `pip` command and it will work in the same way. This assumes that you already have `uv` installed on your system. An example: -``` + +```bash uv pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` This does not install `Horovod`, however, as it requires a specialized -[script](env-files/torch/install-horovod.sh). If you do not require Cuda, then you +[script](env-files/torch/install-horovod-deepspeed-cuda.sh). If you do not require Cuda, then you can install `Horovod` with the last part of the aforementioned script, i.e.: -``` + +```bash pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git ``` From 750618f38d11246a4b5bd509d0f9bcf15ffa9704 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 14:23:30 +0100 Subject: [PATCH 10/59] add more info to readme --- README.md | 28 ++++++++++++++++++---------- 1 file changed, 18 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index d307076aa..d781fb084 100644 --- a/README.md +++ b/README.md @@ -133,40 +133,48 @@ Python virtual environments using our predefined Makefile targets. #### Installation with pip or uv You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. -For macOS, you would e.g. use no wheel. For cuda: +For macOS, you would e.g. use no wheel. This can be done by adding +`--extra-index-url https://download.pytorch.org/whl/` at the end of your +`pip install` statement. For example, if you want to download using the cuda wheel +you would do the following: ```bash pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` -For CPU: + +If you want to use the CPU wheel instead, you would do the following: ```bash pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu ``` -With no wheel (e.g. MacOS): + +If you use linux or macOS, make sure to add this to your installation with extras. +For example, if you want to install for macOS as a developer, you would want to add +the `dev` extra and the `macos` extra as follows: ```bash -pip install -e . --no-cache-dir +pip install -e ".[dev,macos]" --no-cache-dir ``` > [!NOTE] -> We use `-e` here because we are in development mode and thus want any changes to -> immediately be applied to our venv. +> We use `-e` here because we are in development mode and thus want any changes we make +> to immediately be applied to our venv without having to reinstall. If you want to use `uv`, which will significantly speed up the installation, you can prepend `uv` to the `pip` command and it will work in the same way. This assumes that you already have `uv` installed on your system. An example: ```bash -uv pip install . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +uv pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` -This does not install `Horovod`, however, as it requires a specialized -[script](env-files/torch/install-horovod-deepspeed-cuda.sh). If you do not require Cuda, then you -can install `Horovod` with the last part of the aforementioned script, i.e.: +This 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 ``` > [!NOTE] From 00f44543fa0edb40b68f9834f1b465613edfc6d8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 14:26:51 +0100 Subject: [PATCH 11/59] =?UTF-8?q?trailing=20whitespace=20=F0=9F=99=83?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 17 +++++++++-------- 1 file changed, 9 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index d781fb084..dd74966a0 100644 --- a/README.md +++ b/README.md @@ -132,11 +132,12 @@ You can create the Python virtual environments using our predefined Makefile targets. #### Installation with pip or uv + You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. -For macOS, you would e.g. use no wheel. This can be done by adding -`--extra-index-url https://download.pytorch.org/whl/` at the end of your -`pip install` statement. For example, if you want to download using the cuda wheel -you would do the following: +For macOS, you would e.g. use no wheel. This can be done by adding +`--extra-index-url https://download.pytorch.org/whl/` at the end of your +`pip install` statement. For example, if you want to download using the cuda wheel +you would do the following: ```bash pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 @@ -148,8 +149,8 @@ If you want to use the CPU wheel instead, you would do the following: pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu ``` -If you use linux or macOS, make sure to add this to your installation with extras. -For example, if you want to install for macOS as a developer, you would want to add +If you use linux or macOS, make sure to add this to your installation with extras. +For example, if you want to install for macOS as a developer, you would want to add the `dev` extra and the `macos` extra as follows: ```bash @@ -168,8 +169,8 @@ you already have `uv` installed on your system. An example: uv pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 ``` -This 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 +This 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 From ae89e0c8720cbb4f068d031229493f4466361225 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 14:32:12 +0100 Subject: [PATCH 12/59] =?UTF-8?q?trailing=20whitespace=20=F0=9F=99=83=20(a?= =?UTF-8?q?gain)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index dd74966a0..36f256dcf 100644 --- a/README.md +++ b/README.md @@ -159,7 +159,7 @@ pip install -e ".[dev,macos]" --no-cache-dir > [!NOTE] > We use `-e` here because we are in development mode and thus want any changes we make -> to immediately be applied to our venv without having to reinstall. +> to immediately be applied to our venv without having to reinstall. If you want to use `uv`, which will significantly speed up the installation, you can prepend `uv` to the `pip` command and it will work in the same way. This assumes that From 149a5366da74fc3c1ccefc08750f4ada287de605 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 15:41:10 +0100 Subject: [PATCH 13/59] add draft of table of contents to readme --- README.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/README.md b/README.md index 36f256dcf..8791d1586 100644 --- a/README.md +++ b/README.md @@ -16,6 +16,16 @@ See the latest version of our docs [here](https://itwinai.readthedocs.io/). If you are a **developer**, please refer to the [developers installation guide](#installation-for-developers). +## Table of contents +1. [User Installation](#user-installation) + 1. [Python virtual environment](#python-virtual-environment) + 1. [Laptop or GPU node](#laptop-or-gpu-node) + 2. [HPC environment](#hpc-environment) + 1. [PyTorch environment](#pytorch-environment) + 2. [Tensorflow environment](#tensorflow-environment) + 2. [Install itwinai for users](#install-itwinai-for-users) +2. [Installation for developers](#installation-for-developers) + ## User installation Requirements: From 337ebd9274c24a1bbe34800498172e3eb64d44e4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 15:50:18 +0100 Subject: [PATCH 14/59] update readme toc --- README.md | 31 ++++++++++++++++++++++--------- 1 file changed, 22 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index 8791d1586..e3f086894 100644 --- a/README.md +++ b/README.md @@ -16,15 +16,28 @@ See the latest version of our docs [here](https://itwinai.readthedocs.io/). If you are a **developer**, please refer to the [developers installation guide](#installation-for-developers). -## Table of contents -1. [User Installation](#user-installation) - 1. [Python virtual environment](#python-virtual-environment) - 1. [Laptop or GPU node](#laptop-or-gpu-node) - 2. [HPC environment](#hpc-environment) - 1. [PyTorch environment](#pytorch-environment) - 2. [Tensorflow environment](#tensorflow-environment) - 2. [Install itwinai for users](#install-itwinai-for-users) -2. [Installation for developers](#installation-for-developers) +- [itwinai](#itwinai) + - [User installation](#user-installation) + - [Python virtual environment](#python-virtual-environment) + - [Laptop or GPU node](#laptop-or-gpu-node) + - [HPC environment](#hpc-environment) + - [PyTorch environment](#pytorch-environment) + - [TensorFlow environment](#tensorflow-environment) + - [Install itwinai for users](#install-itwinai-for-users) + - [Installation for developers](#installation-for-developers) + - [Clone the itwinai repository](#clone-the-itwinai-repository) + - [Install itwinai environment](#install-itwinai-environment) + - [Installation with pip or uv](#installation-with-pip-or-uv) + - [PyTorch (+ Lightning) virtual environment](#pytorch--lightning-virtual-environment) + - [TensorFlow virtual environment](#tensorflow-virtual-environment) + - [Activate itwinai environment on HPC](#activate-itwinai-environment-on-hpc) + - [Load modules before PyTorch virtual environment](#load-modules-before-pytorch-virtual-environment) + - [Load modules before TensorFlow virtual environment](#load-modules-before-tensorflow-virtual-environment) + - [Test with `pytest`](#test-with-pytest) + - [Working with Docker containers](#working-with-docker-containers) + - [Terminology Recap](#terminology-recap) + - [Image Names and Their Purpose](#image-names-and-their-purpose) + - [Micromamba installation (deprecated)](#micromamba-installation-deprecated) ## User installation From 7b1cff94db27b4752e552a4efbb2a3e5972694bb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 15:51:19 +0100 Subject: [PATCH 15/59] update readme toc again --- README.md | 43 +++++++++++++++++++++---------------------- 1 file changed, 21 insertions(+), 22 deletions(-) diff --git a/README.md b/README.md index e3f086894..ba3901fe7 100644 --- a/README.md +++ b/README.md @@ -16,28 +16,27 @@ See the latest version of our docs [here](https://itwinai.readthedocs.io/). If you are a **developer**, please refer to the [developers installation guide](#installation-for-developers). -- [itwinai](#itwinai) - - [User installation](#user-installation) - - [Python virtual environment](#python-virtual-environment) - - [Laptop or GPU node](#laptop-or-gpu-node) - - [HPC environment](#hpc-environment) - - [PyTorch environment](#pytorch-environment) - - [TensorFlow environment](#tensorflow-environment) - - [Install itwinai for users](#install-itwinai-for-users) - - [Installation for developers](#installation-for-developers) - - [Clone the itwinai repository](#clone-the-itwinai-repository) - - [Install itwinai environment](#install-itwinai-environment) - - [Installation with pip or uv](#installation-with-pip-or-uv) - - [PyTorch (+ Lightning) virtual environment](#pytorch--lightning-virtual-environment) - - [TensorFlow virtual environment](#tensorflow-virtual-environment) - - [Activate itwinai environment on HPC](#activate-itwinai-environment-on-hpc) - - [Load modules before PyTorch virtual environment](#load-modules-before-pytorch-virtual-environment) - - [Load modules before TensorFlow virtual environment](#load-modules-before-tensorflow-virtual-environment) - - [Test with `pytest`](#test-with-pytest) - - [Working with Docker containers](#working-with-docker-containers) - - [Terminology Recap](#terminology-recap) - - [Image Names and Their Purpose](#image-names-and-their-purpose) - - [Micromamba installation (deprecated)](#micromamba-installation-deprecated) +- [User installation](#user-installation) + - [Python virtual environment](#python-virtual-environment) + - [Laptop or GPU node](#laptop-or-gpu-node) + - [HPC environment](#hpc-environment) + - [PyTorch environment](#pytorch-environment) + - [TensorFlow environment](#tensorflow-environment) + - [Install itwinai for users](#install-itwinai-for-users) +- [Installation for developers](#installation-for-developers) + - [Clone the itwinai repository](#clone-the-itwinai-repository) + - [Install itwinai environment](#install-itwinai-environment) + - [Installation with pip or uv](#installation-with-pip-or-uv) + - [PyTorch (+ Lightning) virtual environment](#pytorch--lightning-virtual-environment) + - [TensorFlow virtual environment](#tensorflow-virtual-environment) + - [Activate itwinai environment on HPC](#activate-itwinai-environment-on-hpc) + - [Load modules before PyTorch virtual environment](#load-modules-before-pytorch-virtual-environment) + - [Load modules before TensorFlow virtual environment](#load-modules-before-tensorflow-virtual-environment) + - [Test with `pytest`](#test-with-pytest) +- [Working with Docker containers](#working-with-docker-containers) + - [Terminology Recap](#terminology-recap) + - [Image Names and Their Purpose](#image-names-and-their-purpose) + - [Micromamba installation (deprecated)](#micromamba-installation-deprecated) ## User installation From 245782647f59d1d039415c3719c65895bf353070 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 16:03:48 +0100 Subject: [PATCH 16/59] add section about uv lock to readme --- README.md | 14 ++++++++++++-- 1 file changed, 12 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ba3901fe7..4c00b5745 100644 --- a/README.md +++ b/README.md @@ -150,8 +150,7 @@ 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. +You can create the Python virtual environments using our predefined Makefile targets. #### Installation with pip or uv @@ -204,6 +203,17 @@ pip install --no-cache-dir --no-build-isolation deepspeed > It is possible to not use `--no-cache-dir` on a local computer, but on HPC systems we > recommend using it in order to not fill up your `.cache` directory. +##### Installation using `uv.lock` +The `uv.lock` file provides more information about the exact versions of the libraries +that are used and thus could be better to install from. If you have `uv` installed, +all you need to do is `uv sync` and it will match your `.venv` directory. If you have +installed new packages and wish to update the `uv.lock` file, you can do so with +`uv lock`. + +> [!WARNING] +> Even if you have a venv activated while running `uv sync`, the packages will not +> be installed there unless the venv's directory is called exactly `.venv`. + #### PyTorch (+ Lightning) virtual environment Makefile targets for environment installation: From 49409630672e1ac0e17f2730c9e60328484bed21 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Wed, 13 Nov 2024 16:04:45 +0100 Subject: [PATCH 17/59] update toc of readme --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 4c00b5745..7fc633466 100644 --- a/README.md +++ b/README.md @@ -27,6 +27,7 @@ If you are a **developer**, please refer to the [developers installation guide]( - [Clone the itwinai repository](#clone-the-itwinai-repository) - [Install itwinai environment](#install-itwinai-environment) - [Installation with pip or uv](#installation-with-pip-or-uv) + - [Installation using `uv.lock`](#installation-using-uvlock) - [PyTorch (+ Lightning) virtual environment](#pytorch--lightning-virtual-environment) - [TensorFlow virtual environment](#tensorflow-virtual-environment) - [Activate itwinai environment on HPC](#activate-itwinai-environment-on-hpc) From ddc7d130d0cd1bb2e1ac13b8eaf4622505399b22 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 17:22:27 +0100 Subject: [PATCH 18/59] fix errors in readme --- README.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 7fc633466..c7af00bce 100644 --- a/README.md +++ b/README.md @@ -205,11 +205,12 @@ pip install --no-cache-dir --no-build-isolation deepspeed > recommend using it in order to not fill up your `.cache` directory. ##### Installation using `uv.lock` -The `uv.lock` file provides more information about the exact versions of the libraries + +The `uv.lock` file provides more precise information about the versions of the libraries that are used and thus could be better to install from. If you have `uv` installed, -all you need to do is `uv sync` and it will match your `.venv` directory. If you have -installed new packages and wish to update the `uv.lock` file, you can do so with -`uv lock`. +all you need to do is `uv sync` and it will make your `.venv` directory match the +spec in the `uv.lock` file. If you want to add new packages to the `uv.lock` file, you +can do so with the `uv lock` command. > [!WARNING] > Even if you have a venv activated while running `uv sync`, the packages will not From abff6c1f6fe1448c0176a2f3844f8ab65d045a3c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 17:22:51 +0100 Subject: [PATCH 19/59] add version numbers to packages in pyproject.toml --- pyproject.toml | 50 ++++++++++++++++++++++++-------------------------- 1 file changed, 24 insertions(+), 26 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index a62da6dfb..160dfe601 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,42 +30,38 @@ classifiers = [ ] dependencies = [ - "wandb", - "mlflow", - "jsonargparse[signatures]", - "pyyaml", - "omegaconf", "rich>=13.5.3", "typer>=0.9.0", - "wheel", - "pydantic", - "packaging", - # "prov4ml@git+https://github.com/HPCI-Lab/ProvML@main", # Prov4ML - # "prov4ml@git+https://github.com/matbun/ProvML@main", - "pandas", - "seaborn", - "deepspeed", - # "setuptools", - # "horovod", - "py-cpuinfo", "numpy<2.0.0", - "torch==2.4.*", - "torchvision", - "torchaudio", + "wandb>=0.18.7", + "mlflow>=2.17.2", + "wheel>=0.45.0", + "seaborn>=0.13.2", + "py-cpuinfo>=9.0.0", + "packaging>=24.2", + "pydantic>=2.9.2", + "pyyaml>=6.0.2", + "omegaconf>=2.3.0", + "jsonargparse[signatures]>=4.34.0", + "matplotlib>=3.9.2", ] -# dynamic = ["version", "description"] - [project.optional-dependencies] -torch = ["lightning==2.*", "torchmetrics"] +torch = [ + "torch==2.4.*", + "lightning==2.*", + "torchmetrics>=1.6.0", + "torchvision>=0.19.1", + "torchaudio>=2.4.1", +] 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 + "tensorflow==2.16.*", # needed by tests on tensorboard + "ipykernel>=6.29.5", + "ipython>=8.29.0", + "isort>=5.13.2", ] macos = [ "prov4ml[apple]@git+https://github.com/matbun/ProvML" @@ -100,3 +96,5 @@ markers = [ [tool.isort] profile = "black" known_first_party = ["itwinai"] + + From 4eb5352f067c6d34aa6ddcd10dc5d7c45d1d806f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 17:23:19 +0100 Subject: [PATCH 20/59] remove uv.lock (for now) --- uv.lock | 6656 ------------------------------------------------------- 1 file changed, 6656 deletions(-) delete mode 100644 uv.lock diff --git a/uv.lock b/uv.lock deleted file mode 100644 index 979a00165..000000000 --- a/uv.lock +++ /dev/null @@ -1,6656 +0,0 @@ -version = 1 -requires-python = ">=3.10" -resolution-markers = [ - 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1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index c7af00bce..07a0a6dd1 100644 --- a/README.md +++ b/README.md @@ -37,7 +37,6 @@ If you are a **developer**, please refer to the [developers installation guide]( - [Working with Docker containers](#working-with-docker-containers) - [Terminology Recap](#terminology-recap) - [Image Names and Their Purpose](#image-names-and-their-purpose) - - [Micromamba installation (deprecated)](#micromamba-installation-deprecated) ## User installation From eb163ef0efdf7c5a5a4f83a02c93ee68a8d8123b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 18:03:39 +0100 Subject: [PATCH 22/59] put toc in html comment --- README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/README.md b/README.md index 07a0a6dd1..8ce55efa2 100644 --- a/README.md +++ b/README.md @@ -16,6 +16,10 @@ See the latest version of our docs [here](https://itwinai.readthedocs.io/). If you are a **developer**, please refer to the [developers installation guide](#installation-for-developers). + ## User installation From a99a67429d41064acb5816d0bd53263f9af61e7b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 18:33:51 +0100 Subject: [PATCH 23/59] remove toc, remove ds and horovod from reqs, add docs comment to pyproj --- README.md | 27 --------------------------- docs/requirements.txt | 5 +++-- pyproject.toml | 25 ++++++++++++++++++------- 3 files changed, 21 insertions(+), 36 deletions(-) diff --git a/README.md b/README.md index 8ce55efa2..6e6910285 100644 --- a/README.md +++ b/README.md @@ -16,33 +16,6 @@ See the latest version of our docs [here](https://itwinai.readthedocs.io/). If you are a **developer**, please refer to the [developers installation guide](#installation-for-developers). - - ## User installation Requirements: diff --git a/docs/requirements.txt b/docs/requirements.txt index 9527683fe..9f2b61b83 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -2,8 +2,8 @@ sphinx-rtd-theme==2.0.0 nbsphinx==0.9.4 myst-parser==2.0.0 -git+https://github.com/thomas-bouvier/horovod.git@compile-cpp17 -deepspeed +# git+https://github.com/thomas-bouvier/horovod.git@compile-cpp17 +# deepspeed IPython # local path to itwinai module, assuming that pip install -r docs/requirements.txt is run form the repository root # If needed, you can add optional dependencies, like: ".[dev]" @@ -11,3 +11,4 @@ IPython prov4ml[linux]@git+https://github.com/matbun/ProvML@main .[torch] +# NOTE: You also need 'pandoc', which on mac is just 'brew install pandoc' diff --git a/pyproject.toml b/pyproject.toml index 160dfe601..d2c91a3f8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,13 +55,13 @@ torch = [ "torchaudio>=2.4.1", ] dev = [ - "pytest>=7.4.2", - "pytest-mock>=3.11.1", - "pytest-cov>=4.1.0", - "tensorflow==2.16.*", # needed by tests on tensorboard - "ipykernel>=6.29.5", - "ipython>=8.29.0", - "isort>=5.13.2", + "pytest>=7.4.2", + "pytest-mock>=3.11.1", + "pytest-cov>=4.1.0", + "tensorflow==2.16.*", # needed by tests on tensorboard + "ipykernel>=6.29.5", + "ipython>=8.29.0", + "isort>=5.13.2", ] macos = [ "prov4ml[apple]@git+https://github.com/matbun/ProvML" @@ -70,6 +70,17 @@ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] +# If we ever wanna put the docs requirements in this file instead +# Would let us do 'pip install ".[torch,docs,linux]"' instead of the multiple +# requirements files +# docs = [ +# "sphinx-rtd-theme==2.0.0", +# "nbsphinx==0.9.4", +# "myst-parser==2.0.0", +# "IPython", +# "tensorflow==2.16.*", +# ] + [project.urls] Homepage = "https://www.intertwin.eu/" Documentation = "https://itwinai.readthedocs.io/" From 61e8574119bed9666bb5caeeb1dc2ce1cb0a3f6c Mon Sep 17 00:00:00 2001 From: Matteo Bunino <48362942+matbun@users.noreply.github.com> Date: Thu, 14 Nov 2024 14:13:39 +0100 Subject: [PATCH 24/59] 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 --- .github/linters/.hadolint.yaml | 6 + .github/workflows/pytest.yml | 2 +- README.md | 58 +--- env-files/tensorflow/Dockerfile | 45 ++- env-files/tensorflow/create_container_env.sh | 19 -- env-files/tensorflow/generic_tf.sh | 4 +- env-files/torch/Dockerfile | 84 +++-- env-files/torch/createEnvVega.sh | 1 + env-files/torch/create_container_env.sh | 73 ----- env-files/torch/generic_torch.sh | 8 +- env-files/torch/jupyter/Dockerfile | 257 +++++++++++++++ env-files/torch/jupyter/README.md | 30 ++ env-files/torch/jupyter/asyncssh_config.py | 53 ++++ env-files/torch/jupyter/configure.py | 138 ++++++++ .../torch/jupyter/ipython_kernel_config.json | 7 + env-files/torch/jupyter/setup.sh | 21 ++ env-files/torch/requirements/README.md | 4 + .../torch/requirements/cmcc-requirements.txt | 12 + env-files/torch/requirements/requirements.txt | 1 + pyproject.toml | 16 +- src/itwinai/cli.py | 5 + src/itwinai/loggers.py | 29 +- src/itwinai/torch/distributed.py | 297 +++++++----------- tests/components/test_components.py | 9 +- tests/components/test_pipe_parser.py | 4 +- tests/components/test_pipeline.py | 9 +- tests/conftest.py | 1 + tests/test_loggers.py | 12 +- tests/test_utils.py | 2 +- tests/torch/conftest.py | 38 +++ tests/torch/distribtued_decorator.py | 6 +- tests/torch/runall.sh | 63 ++++ tests/torch/slurm.vega.sh | 237 ++++++++++++++ tests/torch/test_config.py | 3 +- tests/torch/test_distribtued_training.py | 25 -- tests/torch/test_distributed.py | 282 +++++++++++++++++ tests/torch/test_torch_trainer.py | 87 +++++ tests/torch/torch_dist_trainer.py | 62 ---- 38 files changed, 1522 insertions(+), 488 deletions(-) create mode 100644 .github/linters/.hadolint.yaml delete mode 100644 env-files/tensorflow/create_container_env.sh delete mode 100644 env-files/torch/create_container_env.sh create mode 100644 env-files/torch/jupyter/Dockerfile create mode 100644 env-files/torch/jupyter/README.md create mode 100644 env-files/torch/jupyter/asyncssh_config.py create mode 100644 env-files/torch/jupyter/configure.py create mode 100644 env-files/torch/jupyter/ipython_kernel_config.json create mode 100644 env-files/torch/jupyter/setup.sh create mode 100644 env-files/torch/requirements/README.md create mode 100644 env-files/torch/requirements/cmcc-requirements.txt create mode 100644 env-files/torch/requirements/requirements.txt create mode 100644 tests/torch/conftest.py create mode 100644 tests/torch/runall.sh create mode 100644 tests/torch/slurm.vega.sh delete mode 100644 tests/torch/test_distribtued_training.py create mode 100644 tests/torch/test_distributed.py create mode 100644 tests/torch/test_torch_trainer.py delete mode 100644 tests/torch/torch_dist_trainer.py diff --git a/.github/linters/.hadolint.yaml b/.github/linters/.hadolint.yaml new file mode 100644 index 000000000..7ff322014 --- /dev/null +++ b/.github/linters/.hadolint.yaml @@ -0,0 +1,6 @@ +failure-threshold: warning +ignored: + - DL3008 # Pin versions in apt get install. + - DL3013 # Pin versions in pip. TODO: remove. + - DL4001 # Either use Wget or Curl but not both + - DL3003 # Use WORKDIR to switch to a directory \ No newline at end of file diff --git a/.github/workflows/pytest.yml b/.github/workflows/pytest.yml index d5b98751f..a82f82361 100644 --- a/.github/workflows/pytest.yml +++ b/.github/workflows/pytest.yml @@ -34,5 +34,5 @@ jobs: # Default environment names are ".venv-pytorch" and ".venv-tf" - name: Run pytest for workflows shell: bash -l {0} - run: .venv-pytorch/bin/pytest -v ./tests/ -m "not slurm" + run: .venv-pytorch/bin/pytest -v ./tests/ -m "not hpc" diff --git a/README.md b/README.md index 6e6910285..7d3ef07ca 100644 --- a/README.md +++ b/README.md @@ -59,8 +59,8 @@ environment for PyTorch: ```bash ml --force purge - ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/11.7 - ml GCCcore/11.3.0 NCCL/2.12.12-GCCcore-11.3.0-CUDA-11.7.0 cuDNN + ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/12.3 + ml GCCcore/11.3.0 NCCL cuDNN/8.9.7.29-CUDA-12.3.0 UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 ``` ##### TensorFlow environment @@ -80,8 +80,8 @@ environment for TensorFlow: ```bash ml --force purge - ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/11.7 - ml GCCcore/11.3.0 NCCL/2.12.12-GCCcore-11.3.0-CUDA-11.7.0 cuDNN + ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/12.3 + ml GCCcore/11.3.0 NCCL cuDNN/8.9.7.29-CUDA-12.3.0 UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 ``` ### Install itwinai for users @@ -289,8 +289,8 @@ Commands to be executed before activating the python virtual environment: ```bash ml --force purge - ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/11.7 - ml GCCcore/11.3.0 NCCL/2.12.12-GCCcore-11.3.0-CUDA-11.7.0 cuDNN + ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/12.3 + ml GCCcore/11.3.0 NCCL cuDNN/8.9.7.29-CUDA-12.3.0 UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 ``` - When not on an HPC: do nothing. @@ -323,8 +323,8 @@ Commands to be executed before activating the python virtual environment: ```bash ml --force purge - ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/11.7 - ml GCCcore/11.3.0 NCCL/2.12.12-GCCcore-11.3.0-CUDA-11.7.0 cuDNN + ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI CUDA/12.3 + ml GCCcore/11.3.0 NCCL cuDNN/8.9.7.29-CUDA-12.3.0 UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 ``` - When not on an HPC: do nothing. @@ -408,14 +408,16 @@ For example, in `ghcr.io/intertwin-eu/itwinai:0.2.2-torch2.6-jammy`: The `TAG` follows the convention: ```text -X.Y.Z-[torch|tf]x.y-distro +[jlab-]X.Y.Z-(torch|tf)x.y-distro ``` Where: - `X.Y.Z` is the **itwinai version** +- `(torch|tf)` is an exclusive OR between "torch" and "tf". You can pick one or the other, but not both. - `x.y` is the **version of the ML framework** (e.g., PyTorch or TensorFlow) - `distro` is the OS distro in the container (e.g., Ubuntu Jammy) +- `jlab-` is prepended to the tag of images including JupyterLab ### Image Names and Their Purpose @@ -424,42 +426,10 @@ We use different image names to group similar images under the same namespace: - **`itwinai`**: Production images. These should be well-maintained and orderly. - **`itwinai-dev`**: Development images. Tags can vary, and may include random hashes. -- **`itwinai-cvmfs`**: Images that need to be made available through CVMFS. +- **`itwinai-cvmfs`**: Images that need to be made available through CVMFS via +[Unpacker](https://gitlab.cern.ch/unpacked/sync). > [!WARNING] > It is very important to keep the number of tags for `itwinai-cvmfs` as low > as possible. Tags should only be created under this namespace when strictly -> necessary. Otherwise, this could cause issues for the converter. - - +> necessary. Otherwise, this could cause issues for the Unpacker. diff --git a/env-files/tensorflow/Dockerfile b/env-files/tensorflow/Dockerfile index 14142e0cb..0b52a0fdd 100644 --- a/env-files/tensorflow/Dockerfile +++ b/env-files/tensorflow/Dockerfile @@ -6,24 +6,39 @@ ARG IMG_TAG=24.08-tf2-py3 FROM nvcr.io/nvidia/tensorflow:${IMG_TAG} -WORKDIR /usr/src/app +# Fix: https://github.com/hadolint/hadolint/wiki/DL4006 +SHELL ["/bin/bash", "-o", "pipefail", "-c"] + +LABEL org.opencontainers.image.source="https://github.com/interTwin-eu/itwinai" +LABEL org.opencontainers.image.description="Base itwinai image with tensorflow dependencies and CUDA drivers" +LABEL org.opencontainers.image.licenses=MIT +LABEL maintainer="Matteo Bunino - matteo.bunino@cern.ch" + +ENV DEBIAN_FRONTEND=noninteractive + +WORKDIR /app + +RUN apt-get update && apt-get install -y \ + # Needed by Prov4ML/yProvML to generate provenance graph + dot2tex \ + && apt-get clean -y && rm -rf /var/lib/apt/lists/* + +RUN pip install --no-cache-dir --upgrade pip \ + && pip install --no-cache-dir \ + tf_keras==2.16.* \ + "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" \ + ray[tune] # Install itwinai -COPY pyproject.toml ./ -COPY src ./ -COPY env-files/tensorflow/create_container_env.sh ./ -RUN bash create_container_env.sh +COPY pyproject.toml pyproject.toml +COPY src src +RUN pip install --no-cache-dir . \ + && itwinai sanity-check --tensorflow --optional-deps ray -# Create non-root user -RUN groupadd -g 10001 jovyan \ - && useradd -m -u 10000 -g jovyan jovyan \ - && chown -R jovyan:jovyan /usr/src/app -USER jovyan:jovyan +# Additional pip deps +ARG REQUIREMENTS=env-files/torch/requirements/requirements.txt +COPY "${REQUIREMENTS}" additional-requirements.txt +RUN pip install --no-cache-dir -r additional-requirements.txt # ENTRYPOINT [ "/bin/sh" ] # CMD [ ] - -LABEL org.opencontainers.image.source=https://github.com/interTwin-eu/itwinai -LABEL org.opencontainers.image.description="Base itwinai image with tensorflow dependencies and CUDA drivers" -LABEL org.opencontainers.image.licenses=MIT -LABEL maintainer="Matteo Bunino - matteo.bunino@cern.ch" \ No newline at end of file diff --git a/env-files/tensorflow/create_container_env.sh b/env-files/tensorflow/create_container_env.sh deleted file mode 100644 index 65ec53121..000000000 --- a/env-files/tensorflow/create_container_env.sh +++ /dev/null @@ -1,19 +0,0 @@ -#!/bin/bash - -# Install dependencies in container, assuming that the container image -# is from NGC and tensorflow is already installed - -pip install --no-cache-dir --upgrade pip - -# WHEN USING TF >= 2.16: -# install legacy version of keras (2.16) -# Since TF 2.16, keras updated to 3.3, -# which leads to an error when more than 1 node is used -# https://keras.io/getting_started/ -pip install --no-cache-dir tf_keras==2.16.* || exit 1 - -# Install Pov4ML -pip install --no-cache-dir "prov4ml[linux]@git+https://github.com/matbun/ProvML@main" || exit 1 - -# itwinai -pip --no-cache-dir install . || exit 1 diff --git a/env-files/tensorflow/generic_tf.sh b/env-files/tensorflow/generic_tf.sh index 60d001cd8..008839af8 100644 --- a/env-files/tensorflow/generic_tf.sh +++ b/env-files/tensorflow/generic_tf.sh @@ -88,9 +88,9 @@ pip3 install --no-cache-dir tf_keras==2.16.* # Install Pov4ML if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install "prov4ml[apple]@git+https://github.com/matbun/ProvML@main" || exit 1 + pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 else - pip install "prov4ml[linux]@git+https://github.com/matbun/ProvML@main" || exit 1 + pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 fi # Install itwinai: MUST be last line of the script for the user installation script to work! diff --git a/env-files/torch/Dockerfile b/env-files/torch/Dockerfile index ce6a8baaa..89c5bf296 100644 --- a/env-files/torch/Dockerfile +++ b/env-files/torch/Dockerfile @@ -1,31 +1,75 @@ -ARG IMG_TAG=23.09-py3 +ARG IMG_TAG=24.05-py3 +# ARG IMG_TAG=23.09-py3 # 23.09-py3: https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-23-09.html # 24.04-py3: https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes/rel-24-04.html FROM nvcr.io/nvidia/pytorch:${IMG_TAG} -# https://stackoverflow.com/a/56748289 -ARG IMG_TAG +LABEL org.opencontainers.image.source="https://github.com/interTwin-eu/itwinai" +LABEL org.opencontainers.image.description="Base itwinai image with torch dependencies and CUDA drivers" +LABEL org.opencontainers.image.licenses=MIT +LABEL maintainer="Matteo Bunino - matteo.bunino@cern.ch" + +# Fix: https://github.com/hadolint/hadolint/wiki/DL4006 +SHELL ["/bin/bash", "-o", "pipefail", "-c"] + +ENV DEBIAN_FRONTEND=noninteractive + +WORKDIR /app -WORKDIR /usr/src/app +RUN apt-get update && apt-get install -y \ + # Needed by Prov4ML/yProvML to generate provenance graph + dot2tex \ + && apt-get clean -y && rm -rf /var/lib/apt/lists/* # https://github.com/mpi4py/mpi4py/pull/431 -RUN env SETUPTOOLS_USE_DISTUTILS=local python -m pip install --no-cache-dir mpi4py +RUN pip install --no-cache-dir --upgrade pip \ + && env SETUPTOOLS_USE_DISTUTILS=local python -m pip install --no-cache-dir mpi4py + +# DeepSpeed, Horovod and other deps +ENV HOROVOD_WITH_PYTORCH=1 \ + HOROVOD_WITHOUT_TENSORFLOW=1 \ + HOROVOD_WITHOUT_MXNET=1 \ + CMAKE_CXX_STANDARD=17 \ + HOROVOD_MPI_THREADS_DISABLE=1 \ + HOROVOD_CPU_OPERATIONS=MPI \ + HOROVOD_GPU_ALLREDUCE=NCCL \ + HOROVOD_NCCL_LINK=SHARED \ + # DeepSpeed + # DS_BUILD_CCL_COMM=1 \ + DS_BUILD_UTILS=1 \ + DS_BUILD_AIO=1 \ + DS_BUILD_FUSED_ADAM=1 \ + DS_BUILD_FUSED_LAMB=1 \ + DS_BUILD_TRANSFORMER=1 \ + DS_BUILD_STOCHASTIC_TRANSFORMER=1 \ + DS_BUILD_TRANSFORMER_INFERENCE=1 +# Torch: reuse the global torch in the container +RUN CONTAINER_TORCH_VERSION="$(python -c 'import torch;print(torch.__version__)')" \ + && pip install --no-cache-dir torch=="$CONTAINER_TORCH_VERSION" \ + deepspeed==0.15.* \ + git+https://github.com/horovod/horovod.git@3a31d93 \ + "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" \ + ray[tune] \ + # fix .triton/autotune/Fp16Matmul_2d_kernel.pickle bug + && pver="$(python --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)" \ + && line=$(cat -n "/usr/local/lib/python${pver}/dist-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py" | grep os.rename | awk '{print $1}' | head -n 1) \ + && sed -i "${line}s|^|#|" "/usr/local/lib/python${pver}/dist-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py" # Install itwinai -COPY pyproject.toml ./ -COPY src ./ -COPY env-files/torch/create_container_env.sh ./ -RUN bash create_container_env.sh ${IMG_TAG} - -# Create non-root user -RUN groupadd -g 10001 jovyan \ - && useradd -m -u 10000 -g jovyan jovyan \ - && chown -R jovyan:jovyan /usr/src/app -USER jovyan:jovyan - -LABEL org.opencontainers.image.source=https://github.com/interTwin-eu/itwinai -LABEL org.opencontainers.image.description="Base itwinai image with torch dependencies and CUDA drivers" -LABEL org.opencontainers.image.licenses=MIT -LABEL maintainer="Matteo Bunino - matteo.bunino@cern.ch" +COPY pyproject.toml pyproject.toml +COPY src src +# Torch: reuse the global torch in the container +RUN CONTAINER_TORCH_VERSION="$(python -c 'import torch;print(torch.__version__)')" \ + && pip install --no-cache-dir torch=="$CONTAINER_TORCH_VERSION" \ + .[torch] \ + && itwinai sanity-check --torch \ + --optional-deps deepspeed \ + --optional-deps horovod \ + --optional-deps ray + +# Additional pip deps +ARG REQUIREMENTS=env-files/torch/requirements/requirements.txt +COPY "${REQUIREMENTS}" additional-requirements.txt +RUN pip install --no-cache-dir -r additional-requirements.txt diff --git a/env-files/torch/createEnvVega.sh b/env-files/torch/createEnvVega.sh index 8487d505c..f4275fb3e 100644 --- a/env-files/torch/createEnvVega.sh +++ b/env-files/torch/createEnvVega.sh @@ -19,6 +19,7 @@ ml GCCcore/11.3.0 #ml NCCL/2.12.12-GCCcore-11.3.0-CUDA-11.7.0 ml NCCL ml cuDNN/8.9.7.29-CUDA-12.3.0 +ml UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 # You should have CUDA 12.3 now diff --git a/env-files/torch/create_container_env.sh b/env-files/torch/create_container_env.sh deleted file mode 100644 index 00814c07c..000000000 --- a/env-files/torch/create_container_env.sh +++ /dev/null @@ -1,73 +0,0 @@ -#!/bin/bash - -# Install dependencies in container, assuming that the container image -# is from NGC and pytorch is already installed. - -if [ -z "$1" ]; then - echo "ERROR: NGC tag not specified" - exit 2 -fi - -if [ "$1" == "23.09-py3" ]; then - # Tested for torch==2.1.0 - - pip install --no-cache-dir --upgrade pip - # pip install --no-cache-dir lightning torchmetrics wheel ray ray[tune] - - # DeepSpeed - - # export DS_BUILD_CCL_COMM=1 # temporarily disabled. - # To install it see: - # https://github.com/intel/torch-ccl?tab=readme-ov-file#install-prebuilt-wheel - # https://github.com/oneapi-src/oneCCL?tab=readme-ov-file#installation - - export DS_BUILD_UTILS=1 - export DS_BUILD_AIO=1 - export DS_BUILD_FUSED_ADAM=1 - export DS_BUILD_FUSED_LAMB=1 - export DS_BUILD_TRANSFORMER=1 - export DS_BUILD_STOCHASTIC_TRANSFORMER=1 - export DS_BUILD_TRANSFORMER_INFERENCE=1 - - pip install --no-cache-dir deepspeed || exit 1 - - # fix .triton/autotune/Fp16Matmul_2d_kernel.pickle bug - pver="$(python --version 2>&1 | awk '{print $2}' | cut -f1-2 -d.)" - line=$(cat -n /usr/lib/python${pver}/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py | grep os.rename | awk '{print $1}' | head -n 1) - sed -i "${line}s|^|#|" /usr/lib/python${pver}/site-packages/deepspeed/ops/transformer/inference/triton/matmul_ext.py - - # Horovod - # compiler vars - export LDSHARED="$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=$EBROOTNCCL - - # Host language vars - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 - - # Fix needed to compile horovod with torch >= 2.1 - # https://github.com/horovod/horovod/pull/3998 - # Assume that Horovod env vars are already in the current env! - pip install --no-cache-dir git+https://github.com/horovod/horovod.git || exit 1 - - # Store container torch version - # Enforce that the current version of torch in the container is preserved, otherwise, if updated, Horovod will complain. - CONTAINER_TORCH_VERSION=$(python -c 'import torch;print(torch.__version__)') - - # Install twinai and Pov4ML, forcing pip to preserve current torch version - pip install --no-cache-dir .[torch] "prov4ml[linux]@git+https://github.com/matbun/ProvML" torch==$CONTAINER_TORCH_VERSION --no-cache-dir || exit 1 - -else - echo "ERROR: unrecognized tag." - exit 2 -fi diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index 500cad08d..af700d880 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -77,7 +77,7 @@ else if [[ "$OSTYPE" =~ ^darwin ]] ; then echo 'Installation issues: Skipping Ray installation for MacOS' else - pip install --no-cache-dir ray ray[tune] || exit 1 + pip install --no-cache-dir ray[tune] || exit 1 fi fi @@ -96,7 +96,7 @@ else export DS_BUILD_TRANSFORMER_INFERENCE=1 fi pip install --no-cache-dir py-cpuinfo || exit 1 - pip install --no-cache-dir deepspeed || 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 $1}' | head -n 1) @@ -173,9 +173,9 @@ fi # Install Pov4ML if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install --no-cache-dir "prov4ml[apple]@git+https://github.com/matbun/ProvML" || exit 1 + 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[linux]@git+https://github.com/matbun/ProvML" || exit 1 + pip install --no-cache-dir "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 fi # Install itwinai: MUST be last line of the script for the user installation script to work! diff --git a/env-files/torch/jupyter/Dockerfile b/env-files/torch/jupyter/Dockerfile new file mode 100644 index 000000000..a33df1a57 --- /dev/null +++ b/env-files/torch/jupyter/Dockerfile @@ -0,0 +1,257 @@ +# https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-pytorch-notebook +# https://github.com/jupyter/docker-stacks/wiki + +FROM jupyter/scipy-notebook:python-3.10.11 +# FROM quay.io/jupyter/pytorch-notebook:x86_64-cuda12-python-3.11 +LABEL org.opencontainers.image.source="https://github.com/interTwin-eu/itwinai" +LABEL org.opencontainers.image.description="itwinai image with torch dependencies, CUDA drivers, and Rucio client for jupyterlab singleuser server enabled for interLink offloading" +LABEL org.opencontainers.image.licenses=MIT +LABEL maintainer="Matteo Bunino - matteo.bunino@cern.ch, VRE Team @ CERN 23/24 - E. Garcia, G. Guerrieri" + +# Fix: https://github.com/hadolint/hadolint/wiki/DL4006 +SHELL ["/bin/bash", "-o", "pipefail", "-c"] + +USER $NB_UID + +# jupyterhub must be < 2 +RUN conda install -y -n base mamba \ + && mamba install -y -c conda-forge python-gfal2 \ + nodejs \ + jupyterlab"<4" \ + notebook"<7" \ + jupyterhub"<2" \ + jsonschema \ + jupyterlab_server \ + jupyter_server \ + traitlets \ + nbformat \ + ipykernel \ + PyJWT \ + ipywidgets \ + asyncssh \ + peewee \ + && conda clean --all -f -y + +USER root + +RUN apt-get update -y && apt-get install -y \ + build-essential \ + cmake \ + curl \ + software-properties-common \ + voms-clients-java \ + && rm /opt/conda/bin/voms-proxy-init \ + && ln -s /usr/bin/voms-proxy-init /opt/conda/bin/voms-proxy-init \ + && apt-get clean -y && rm -rf /var/lib/apt/lists/* + + +# ESCAPE grid-security and VOMS setup +RUN wget -q -O - https://dist.eugridpma.info/distribution/igtf/current/GPG-KEY-EUGridPMA-RPM-3 | apt-key add - + +RUN apt-get update \ + && add-apt-repository 'deb http://repository.egi.eu/sw/production/cas/1/current egi-igtf core' \ + && apt-get -y install ca-policy-egi-core \ + && rm -rf /var/lib/apt/lists/* + +RUN mkdir -p /etc/vomses \ + && wget -q https://indigo-iam.github.io/escape-docs/voms-config/voms-escape.cloud.cnaf.infn.it.vomses -O /etc/vomses/voms-escape.cloud.cnaf.infn.it.vomses \ + && mkdir -p /etc/grid-security/vomsdir/escape \ + && wget -q https://indigo-iam.github.io/escape-docs/voms-config/voms-escape.cloud.cnaf.infn.it.lsc -O /etc/grid-security/vomsdir/escape/voms-escape.cloud.cnaf.infn.it.lsc + +# Setup merged CERN CA file on Ubuntu based images. +# This file is contained in the `CERN-bundle.pem` file downloaded using +RUN mkdir /certs \ + && touch /certs/rucio_ca.pem \ + && curl -fsSL 'https://cafiles.cern.ch/cafiles/certificates/CERN%20Root%20Certification%20Authority%202.crt' | openssl x509 -inform DER -out /tmp/cernrootca2.crt \ + && curl -fsSL 'https://cafiles.cern.ch/cafiles/certificates/CERN%20Grid%20Certification%20Authority(1).crt' -o /tmp/cerngridca.crt \ + && curl -fsSL 'https://cafiles.cern.ch/cafiles/certificates/CERN%20Certification%20Authority.crt' -o /tmp/cernca.crt \ + && cat /tmp/cernrootca2.crt >> /certs/rucio_ca.pem \ + && cat /tmp/cerngridca.crt >> /certs/rucio_ca.pem \ + && cat /tmp/cernca.crt >> /certs/rucio_ca.pem \ + && rm /tmp/*.crt \ + && update-ca-certificates + +# # Install trust anchors +# RUN curl https://ca.cern.ch/cafiles/certificates/CERN%20Root%20Certification%20Authority%202.crt -o /etc/pki/ca-trust/source/anchors/1.crt &&\ +# curl https://ca.cern.ch/cafiles/certificates/CERN%20Grid%20Certification%20Authority.crt -o /etc/pki/ca-trust/source/anchors/2.crt &&\ +# curl https://ca.cern.ch/cafiles/certificates/CERN%20Grid%20Certification%20Authority\(1\).crt -o /etc/pki/ca-trust/source/anchors/3.crt &&\ +# curl http://signet-ca.ijs.si/pub/cacert/signet02cacert.crt -o /etc/pki/ca-trust/source/anchors/4.crt &&\ +# curl https://doku.tid.dfn.de/_media/de:dfnpki:ca:tcs-server-certificate-ca-bundle.tar -o geant-bundle.tar &&\ +# tar xf geant-bundle.tar &&\ +# cp tcs-server-certificate-ca-bundle/*.pem /etc/pki/ca-trust/source/anchors/ &&\ +# rm -rf geant-bundle.tar tcs-server-certificate-ca-bundle &&\ +# update-ca-trust + +# Add async ssh script +COPY env-files/torch/jupyter/asyncssh_config.py /opt/ssh/jupyterhub-singleuser +RUN fix-permissions /opt/ssh/jupyterhub-singleuser \ + && chown -R $NB_UID /opt/ssh/jupyterhub-singleuser \ + && chmod +x /opt/ssh/jupyterhub-singleuser + +# Setup extension Rucio instance config +COPY env-files/torch/jupyter/configure.py /opt/setup-rucio-jupyterlab/configure.py +RUN fix-permissions /opt/setup-rucio-jupyterlab/configure.py \ + && chown -R $NB_UID /opt/setup-rucio-jupyterlab/configure.py \ + && chmod +x /opt/setup-rucio-jupyterlab/configure.py + +COPY env-files/torch/jupyter/setup.sh /usr/local/bin/setup.sh +RUN fix-permissions /usr/local/bin/setup.sh \ + && sed -i -e 's/\r$/\n/' /usr/local/bin/setup.sh \ + && chmod +x /usr/local/bin/setup.sh + +RUN mkdir -p /opt/rucio/etc \ + # && touch /opt/rucio/etc/rucio.cfg \ + && fix-permissions /opt/rucio/etc \ + && chown -R ${NB_UID}:${NB_GID} /opt/rucio/etc + +# && /usr/local/bin/setup.sh +#RUN chown -R $NB_UID $HOME/.jupyter/jupyter_notebook_config.json +# && chown -R $NB_UID /etc/jupyter/jupyter_notebook_config.py + + +#ENV IPYTHONDIR=/etc/ipython +#ADD ipython_kernel_config.json /etc/ipython/profile_default/ipython_kernel_config.json +#RUN chown -R $NB_UID /etc/ipython +ENV JUPYTER_ENABLE_LAB=yes + +USER $NB_UID +WORKDIR $HOME + +# Install rucio-jupyterlab with jlab v=3 +RUN pip install --no-cache-dir --upgrade pip \ + && pip install --no-cache-dir rucio-jupyterlab==0.10.0 \ + && jupyter serverextension enable --py rucio_jupyterlab --sys-prefix + +############################# +### itwinai ### +############################# + +USER root + +RUN apt-get update && apt-get install -y \ + # Needed (at least) by horovod wheel builder + build-essential \ + # Needed (at least) by horovod wheel builder + cmake \ + # Needed by Prov4ML/yProvML to generate provenance graph + dot2tex \ + # Needed by OpenMPI for efficient compression at startup + zlib1g \ + # Needed by OpenMPI for efficient compression at startup + zlib1g-dev \ + && apt-get clean -y && rm -rf /var/lib/apt/lists/* + +# OpenMPI +WORKDIR /tmp/ompi +ENV OPENMPI_VERSION=4.1.6 \ + OPENMPI_MINOR=4.1 +ENV OPENMPI_URL="https://download.open-mpi.org/release/open-mpi/v${OPENMPI_MINOR}/openmpi-${OPENMPI_VERSION}.tar.gz" +ENV OPENMPI_DIR=/opt/openmpi-${OPENMPI_VERSION} +ENV PATH="${OPENMPI_DIR}/bin:${PATH}" +ENV LD_LIBRARY_PATH="${OPENMPI_DIR}/lib:${LD_LIBRARY_PATH}" +ENV MANPATH=${OPENMPI_DIR}/share/man:${MANPATH} +RUN wget -q -O openmpi-$OPENMPI_VERSION.tar.gz $OPENMPI_URL && tar xzf openmpi-$OPENMPI_VERSION.tar.gz \ + && cd openmpi-$OPENMPI_VERSION && ./configure --prefix=$OPENMPI_DIR && make install + +# Nvidia software +WORKDIR /tmp/cuda +# CUDA Toolkit: +# - https://developer.nvidia.com/cuda-downloads +# - Installation guide: https://docs.nvidia.com/cuda/cuda-quick-start-guide/index.html#ubuntu +# - cuda-toolkit metapackage: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/#meta-packages +# cuDNN: +# - https://docs.nvidia.com/deeplearning/cudnn/latest/installation/linux.html#installing-cudnn-on-linux +# NCCL: +# - https://docs.nvidia.com/deeplearning/nccl/install-guide/index.html#debian +# *NOTE* to correctly install Apex below, CUDA toolkit version must match with the torch CUDA backend version +ENV CUDA_VERSION=12.4 \ + CUDA_TOOLKIT_VERSION=12-4 \ + CUDA_MAJOR_VERSION=12 +RUN wget -q -O cuda-keyring.deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb \ + && dpkg -i cuda-keyring.deb \ + && apt-get update && apt-get install -y \ + # CUDA toolkit metapackage (does not include the Nvidia driver) + cuda-toolkit-${CUDA_TOOLKIT_VERSION} \ + # cuDNN + cudnn-cuda-${CUDA_MAJOR_VERSION} \ + # NCCL + libnccl2 \ + libnccl-dev \ + # Nvidia driver, as explained here: https://developer.nvidia.com/cuda-downloads + nvidia-open \ + && apt-get clean -y && rm -rf /var/lib/apt/lists/* +ENV PATH=/usr/local/cuda-${CUDA_VERSION}/bin${PATH:+:${PATH}}\ + LD_LIBRARY_PATH=/usr/local/cuda-${CUDA_VERSION}/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}} + +# Cleanup +RUN rm -rf /tmp/* + +USER $NB_UID + +# Torch and smaller deps +RUN pip install --no-cache-dir --upgrade pip \ + # https://github.com/mpi4py/mpi4py/pull/431 + && SETUPTOOLS_USE_DISTUTILS=local python -m pip install --no-cache-dir mpi4py \ + && unset SETUPTOOLS_USE_DISTUTILS \ + # Install torch + && pip install --no-cache-dir \ + 'numpy<2' \ + packaging \ + py-cpuinfo \ + torch==2.4.* torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124 \ + wheel + +# Apex: https://github.com/NVIDIA/apex +# (needed for DeepSpeed *_FUSED optinal build options) +# Note: it will take more than an hour to build +WORKDIR /tmp +RUN git clone https://github.com/NVIDIA/apex && cd apex \ + && pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ \ + && rm -rf /tmp/apex +# Transformer engine: https://docs.nvidia.com/deeplearning/transformer-engine/user-guide/index.html +# (needed for DeepSpeed *TRANSFORMER* optinal build options) +# Note: it will take about half an hour to build +RUN pip install --no-cache-dir transformer_engine[pytorch] + +# DeepSpeed, Horovod and other deps +ENV HOROVOD_WITH_PYTORCH=1 \ + HOROVOD_WITHOUT_TENSORFLOW=1 \ + HOROVOD_WITHOUT_MXNET=1 \ + CMAKE_CXX_STANDARD=17 \ + HOROVOD_MPI_THREADS_DISABLE=1 \ + HOROVOD_CPU_OPERATIONS=MPI \ + HOROVOD_GPU_ALLREDUCE=NCCL \ + HOROVOD_NCCL_LINK=SHARED \ + # DeepSpeed + DS_BUILD_UTILS=1 \ + DS_BUILD_AIO=1 \ + DS_BUILD_FUSED_ADAM=1 \ + DS_BUILD_FUSED_LAMB=1 \ + DS_BUILD_TRANSFORMER=1 \ + DS_BUILD_STOCHASTIC_TRANSFORMER=1 \ + DS_BUILD_TRANSFORMER_INFERENCE=1 +RUN pip install --no-cache-dir \ + deepspeed==0.15.* \ + git+https://github.com/horovod/horovod.git@3a31d93 \ + "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@e99bddba047a1a04ca0387e87cad1ed96d5ab2c5" \ + ray[tune] + + +# Core itwinai lib +WORKDIR "$HOME/itwinai" +COPY pyproject.toml pyproject.toml +COPY src src +RUN pip install --no-cache-dir ".[torch,dev]" \ + && itwinai sanity-check --torch \ + --optional-deps deepspeed \ + --optional-deps horovod \ + --optional-deps ray + +# Additional pip deps +ARG REQUIREMENTS=env-files/torch/requirements/requirements.txt +COPY "${REQUIREMENTS}" additional-requirements.txt +RUN pip install --no-cache-dir -r additional-requirements.txt + +WORKDIR $HOME + +CMD ["setup.sh", "start-notebook.sh"] diff --git a/env-files/torch/jupyter/README.md b/env-files/torch/jupyter/README.md new file mode 100644 index 000000000..c4fb3c83e --- /dev/null +++ b/env-files/torch/jupyter/README.md @@ -0,0 +1,30 @@ +# JupyterLab image for itwinai with Rucio client + +The files in this folder are adapted from the work done by +the [VRE team](https://github.com/vre-hub/environments). + +To build this container, go into the root of itwinai and run + +```bash +docker build -t : -f env-files/torch/jupyter/Dockerfile . +``` + +using your preferred `` and ``. + +## Install custom dependencies + +To install custom dependencies (e.g., use cases packages) you can add them +in a `requirements.txt` file, add it somewhere **in the itwinai directory** and pass +it to the `docker build`: + +```bash +docker build -t : -f env-files/torch/jupyter/Dockerfile \ + --build-arg REQUIREMENTS=path/to/requirements.txt . +``` + +For instance: + +```bash +docker build -t : -f env-files/torch/jupyter/Dockerfile \ + --build-arg REQUIREMENTS=env-files/torch/requirements/cmcc-requirements.txt . +``` diff --git a/env-files/torch/jupyter/asyncssh_config.py b/env-files/torch/jupyter/asyncssh_config.py new file mode 100644 index 000000000..da1877907 --- /dev/null +++ b/env-files/torch/jupyter/asyncssh_config.py @@ -0,0 +1,53 @@ +#!/opt/conda/bin/python +# -*- coding: utf-8 -*- +# +# D. Ciangottini +# +import asyncio +import os +import re +import sys +from subprocess import Popen + +import asyncssh +from jupyterhub.singleuser import main + +ssh_host = os.environ.get("JHUB_HOST") +ssh_url_port = os.environ.get("SSH_PORT") +username = os.environ.get("JUPYTERHUB_USER") +token = os.environ.get("JUPYTERHUB_API_TOKEN") + +fwd_port = os.environ.get("FWD_PORT") + + +async def run_client(): + async with asyncssh.connect( + host=ssh_host, + port=int(ssh_url_port), + username=username, + password=token, + known_hosts=None, + ) as conn: + conn.set_keepalive(interval=14.0, count_max=10) + listener = await conn.forward_remote_port( + "0.0.0.0", + int(fwd_port), + "0.0.0.0", + int(fwd_port), + ) + await listener.wait_closed() + + +if __name__ == '__main__': + print("Connecting ssh...") + loop = asyncio.get_event_loop() + loop.create_task(run_client()) + + print("Configuring Rucio extension...") + p = Popen(['/usr/local/bin/setup.sh']) + while p.poll() is None: + pass + + print("Starting JLAB") + sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) + sys.exit(main()) diff --git a/env-files/torch/jupyter/configure.py b/env-files/torch/jupyter/configure.py new file mode 100644 index 000000000..338167793 --- /dev/null +++ b/env-files/torch/jupyter/configure.py @@ -0,0 +1,138 @@ +#!/usr/bin/env python +# Derived from (restricted access): +# https://gitlab.cern.ch/escape-wp2/docker-images/-/blob/master/datalake-singleuser/bin/configure.py + +import configparser +import json +import os + +# HOME = '/home/jovyan' +# HOME = '/ceph/hpc/home/ciangottinid' + + +def write_jupyterlab_config(): + HOME = os.getenv('HOME', '/ceph/hpc/home/ciangottinid') + + file_path = HOME + '/.jupyter/jupyter_notebook_config.json' + if not os.path.isfile(file_path): + os.makedirs(HOME + '/.jupyter/', exist_ok=True) + else: + config_file = open(file_path, 'r') + config_payload = config_file.read() + config_file.close() + + try: + config_json = json.loads(config_payload) + except Exception: + config_json = {} + +# Looking to the rucio-jupyterlab configuration; +# https://github.com/rucio/jupyterlab-extension/blob/master/rucio_jupyterlab/config/schema.py#L101 +# either ("destination_rse", "rse_mount_path") either ("rucio_ca_cert") are required env +# vars, even if they are defined in the jhub manifest. +# Adding 'rucio_base_url' too - from debugging experience + + # instance_config = { + # "name": os.getenv('RUCIO_NAME', 'default'), + # "display_name": os.getenv('RUCIO_DISPLAY_NAME', 'Default Instance'), + # "rucio_base_url": os.getenv('RUCIO_BASE_URL', 'DEFAULT rucio base url'), + # "rucio_auth_url": os.getenv('RUCIO_AUTH_URL'), + # "rucio_webui_url": os.getenv('RUCIO_WEBUI_URL'), + # "rucio_ca_cert": os.getenv('RUCIO_CA_CERT', 'cacert.pem'), + # "site_name": os.getenv('RUCIO_SITE_NAME'), + # "vo": os.getenv('RUCIO_VO'), + # "voms_enabled": os.getenv('RUCIO_VOMS_ENABLED', '0') == '1', + # "voms_vomses_path": os.getenv('RUCIO_VOMS_VOMSES_PATH'), + # "voms_certdir_path": os.getenv('RUCIO_VOMS_CERTDIR_PATH'), + # "voms_vomsdir_path": os.getenv('RUCIO_VOMS_VOMSDIR_PATH'), + # "destination_rse": os.getenv('RUCIO_DESTINATION_RSE', 'DEFAULT rse destination'), + # "rse_mount_path": os.getenv('RUCIO_RSE_MOUNT_PATH', 'DEFAULT rse mount path'), + # "replication_rule_lifetime_days": int(os.getenv( + # 'RUCIO_REPLICATION_RULE_LIFETIME_DAYS')) if os.getenv( + # 'RUCIO_REPLICATION_RULE_LIFETIME_DAYS') else None, + # "path_begins_at": int(os.getenv('RUCIO_PATH_BEGINS_AT', '0')), + # "mode": os.getenv('RUCIO_MODE', 'replica'), + # "wildcard_enabled": os.getenv('RUCIO_WILDCARD_ENABLED', '0') == '1', + # "oidc_auth": os.getenv('RUCIO_OIDC_AUTH'), + # "oidc_env_name": os.getenv('RUCIO_OIDC_ENV_NAME'), + # "oidc_file_name": os.getenv('RUCIO_OIDC_FILE_NAME'), + # } + + # instance_config = {k: v for k, + # v in instance_config.items() if v is not None} + # config_json['RucioConfig'] = { + # 'instances': [instance_config], + # "default_instance": os.getenv('RUCIO_DEFAULT_INSTANCE',), + # "default_auth_type": os.getenv('RUCIO_DEFAULT_AUTH_TYPE'), + # } + + # Debugging and hardcoding from here + + instance_config = { + "name": "rucio-intertwin-testbed.desy.de", + "display_name": "interTwinRUCIO", + "rucio_base_url": "https://rucio-intertwin-testbed.desy.de", + "rucio_auth_url": "https://rucio-intertwin-testbed-auth.desy.de", + "rucio_ca_cert": "/opt/conda/lib/python3.9/site-packages/certifi/cacert.pem", + "site_name": "VEGA", + "voms_enabled": os.getenv('RUCIO_VOMS_ENABLED', '0') == '1', + "destination_rse": "VEGA-DCACHE", + "rse_mount_path": "/dcache/sling.si/projects/intertwin", + "path_begins_at": 4, + "mode": "replica", + # "mode": "download", + "wildcard_enabled": os.getenv('RUCIO_WILDCARD_ENABLED', '0') == '0', + "oidc_auth": "env", + "oidc_env_name": "RUCIO_ACCESS_TOKEN" + } + + instance_config = {k: v for k, + v in instance_config.items() if v is not None} + config_json['RucioConfig'] = { + 'instances': [instance_config], + "default_instance": os.getenv('RUCIO_DEFAULT_INSTANCE', + 'rucio-intertwin-testbed.desy.de'), + "default_auth_type": os.getenv('RUCIO_DEFAULT_AUTH_TYPE', 'oidc'), + } + + # up to here + + config_file = open(file_path, 'w') + config_file.write(json.dumps(config_json, indent=2)) + config_file.close() + + +def write_rucio_config(): + + rucio_config = configparser.ConfigParser() + + client_config = { + 'rucio_host': os.getenv('RUCIO_BASE_URL', + 'https://rucio-intertwin-testbed.desy.de'), + 'auth_host': os.getenv('RUCIO_AUTH_URL', + 'https://rucio-intertwin-testbed-auth.desy.de'), + 'ca_cert': os.getenv('RUCIO_CA_CERT', '/certs/rucio_ca.pem'), + 'auth_type': os.getenv('RUCIO_AUTH_TYPE', 'oidc'), # 'x509' or 'oidc' + # This is the RUCIO account name, need to be mapped from idp + 'account': os.getenv('RUCIO_ACCOUNT', '$RUCIO_ACCOUNT'), + 'oidc_polling': 'true', + 'oidc_scope': 'openid profile offline_access eduperson_entitlement', + # 'username': os.getenv('RUCIO_USERNAME', ''), + # 'password': os.getenv('RUCIO_PASSWORD', ''), + 'auth_token_file_path': '/tmp/rucio_oauth.token', + 'request_retries': 3, + 'protocol_stat_retries': 6 + } + client_config = dict((k, v) for k, v in client_config.items() if v) + rucio_config['client'] = client_config + + if not os.path.isfile('/opt/rucio/etc/rucio.cfg'): + os.makedirs('/opt/rucio/etc/', exist_ok=True) + + with open('/opt/rucio/etc/rucio.cfg', 'w') as f: + rucio_config.write(f) + + +if __name__ == '__main__': + write_jupyterlab_config() + # write_rucio_config() diff --git a/env-files/torch/jupyter/ipython_kernel_config.json b/env-files/torch/jupyter/ipython_kernel_config.json new file mode 100644 index 000000000..07c930f89 --- /dev/null +++ b/env-files/torch/jupyter/ipython_kernel_config.json @@ -0,0 +1,7 @@ +{ + "IPKernelApp": { + "extensions": [ + "rucio_jupyterlab.kernels.ipython" + ] + } +} \ No newline at end of file diff --git a/env-files/torch/jupyter/setup.sh b/env-files/torch/jupyter/setup.sh new file mode 100644 index 000000000..15712916d --- /dev/null +++ b/env-files/torch/jupyter/setup.sh @@ -0,0 +1,21 @@ +#!/bin/bash +set -e +python /opt/setup-rucio-jupyterlab/configure.py + +# Creation of the rucio.cfg file +mkdir -p /certs /tmp; +echo -n $RUCIO_ACCESS_TOKEN > /tmp/rucio_oauth.token; +# mkdir -p /opt/rucio/etc; +# echo "[client]" >> /opt/rucio/etc/rucio.cfg; +# echo "rucio_host = https://rucio-intertwin-testbed.desy.de" >> /opt/rucio/etc/rucio.cfg; +# echo "auth_host = https://rucio-intertwin-testbed-auth.desy.de" >> /opt/rucio/etc/rucio.cfg; +# #echo "ca_cert = /certs/rucio_ca.pem" >> /opt/rucio/etc/rucio.cfg; +# echo "ca_cert = /opt/conda/lib/python3.9/site-packages/certifi/cacert.pem" >> /opt/rucio/etc/rucio.cfg; +# echo "account = $JUPYTERHUB_USER" >> /opt/rucio/etc/rucio.cfg; +# echo "auth_type = oidc" >> /opt/rucio/etc/rucio.cfg; +# echo "oidc_audience = rucio-testbed" >> /opt/rucio/etc/rucio.cfg; +# echo "oidc_polling = true" >> /opt/rucio/etc/rucio.cfg; +# echo "oidc_scope = openid profile offline_access eduperson_entitlement" >> /opt/rucio/etc/rucio.cfg; +# echo "auth_token_file_path = /tmp/rucio_oauth.token" >> /opt/rucio/etc/rucio.cfg; + +exec "$@" \ No newline at end of file diff --git a/env-files/torch/requirements/README.md b/env-files/torch/requirements/README.md new file mode 100644 index 000000000..dc7a72547 --- /dev/null +++ b/env-files/torch/requirements/README.md @@ -0,0 +1,4 @@ +# Additional requirements + +This folder contains additional (optional) python dependencies, for instance +interTwin use cases specific dependencies. diff --git a/env-files/torch/requirements/cmcc-requirements.txt b/env-files/torch/requirements/cmcc-requirements.txt new file mode 100644 index 000000000..6127f3199 --- /dev/null +++ b/env-files/torch/requirements/cmcc-requirements.txt @@ -0,0 +1,12 @@ +cartopy +joblib +lightning +matplotlib +munch +pandas +requests +tqdm +timm +toml +xarray +zarr \ No newline at end of file diff --git a/env-files/torch/requirements/requirements.txt b/env-files/torch/requirements/requirements.txt new file mode 100644 index 000000000..20bd8ee52 --- /dev/null +++ b/env-files/torch/requirements/requirements.txt @@ -0,0 +1 @@ +# Addtional requirements go here diff --git a/pyproject.toml b/pyproject.toml index d2c91a3f8..b0fe42dc1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,21 +8,16 @@ build-backend = "setuptools.build_meta" [project] name = "itwinai" -version = "0.2.2" +version = "0.2.3" description = "AI and ML workflows module for scientific digital twins." readme = "README.md" requires-python = ">=3.10" license = { file = "LICENSE" } keywords = ["ml", "ai", "hpc"] -authors = [ - { name = "Matteo Bunino", email = "matteo.bunino@cern.ch" }, - { name = "Rakesh Sarma", email = "r.sarma@fz-juelich.de" }, -] maintainers = [ { name = "Matteo Bunino", email = "matteo.bunino@cern.ch" }, - { name = "Rakesh Sarma", email = "r.sarma@fz-juelich.de" }, - { name = "Mario Ruettgers", email = "m.ruettgers@fz-juelich.de" }, - { name = "Kalliopi Tsolaki", email = "kalliopi.tsolaki@cern.ch" }, + { name = "Jarl Sondre Sæther", email = "jarl.sondre.saether@cern.ch" }, + { name = "Anna Lappe", email = "anna.elisa.lappe@cern.ch" }, ] classifiers = [ "Development Status :: 4 - Beta", @@ -99,7 +94,10 @@ itwinai = "itwinai.cli:app" [tool.pytest.ini_options] markers = [ "integration: integration tests (deselect with '-m \"not integration\"')", - "slurm: needs SLURM and HPC resources (multiple GPUs/nodes). (deselect with '-m \"not slurm\"')", + "hpc: needs SLURM and HPC resources (multiple GPUs/nodes). (deselect with '-m \"not hpc\"')", + "torch_dist: runs with torch DDP distributed strategy. (deselect with '-m \"not torch_dist\"')", + "deepspeed_dist: runs with torch DeepSpeed distributed strategy. (deselect with '-m \"not deepspeed_dist\"')", + "horovod_dist: runs with torch Horovod distributed strategy. (deselect with '-m \"not horovod_dist\"')", "functional: functional tests. (deselect with '-m \"not functional\"')", "memory_heavy: high memory footprint. (deselect with '-m \"not heavy_memory\"')", ] diff --git a/src/itwinai/cli.py b/src/itwinai/cli.py index 922ffb686..574fb8f8a 100644 --- a/src/itwinai/cli.py +++ b/src/itwinai/cli.py @@ -269,11 +269,13 @@ def sanity_check( Optional[bool], typer.Option(help=("Check also itwinai.tensorflow modules.")) ] = False, all: Annotated[Optional[bool], typer.Option(help=("Check all modules."))] = False, + optional_deps: List[str] = typer.Option(None, help="List of optional dependencies."), ): """Run sanity checks on the installation of itwinai and its dependencies by trying to import itwinai modules. By default, only itwinai core modules (neither torch, nor tensorflow) are tested.""" from itwinai.tests.sanity_check import ( + run_sanity_check, sanity_check_all, sanity_check_slim, sanity_check_tensorflow, @@ -290,6 +292,9 @@ def sanity_check( else: sanity_check_slim() + if optional_deps is not None: + run_sanity_check(optional_deps) + @app.command() def exec_pipeline( diff --git a/src/itwinai/loggers.py b/src/itwinai/loggers.py index 5012f2383..7b3356208 100644 --- a/src/itwinai/loggers.py +++ b/src/itwinai/loggers.py @@ -50,6 +50,8 @@ by :class:`~itwinai.loggers.Prov4MLLogger`. * - ``execution_time`` - Execution time, used by :class:`~itwinai.loggers.Prov4MLLogger`. + * - ``prov_documents`` + - Provenance documents, used by :class:`~itwinai.loggers.Prov4MLLogger`. .. _More info: https://docs.wandb.ai/ref/python/watch @@ -480,13 +482,11 @@ def __init__( self.run_description = run_description self.run_name = run_name - if self.tracking_uri is None: - # Default MLFLow tracking URI - saved_abs_path = os.path.abspath(self.savedir) - self.tracking_uri = pathlib.Path(saved_abs_path).as_uri() - - # TODO: for pytorch lightning: - # mlflow.pytorch.autolog() + self.tracking_uri = ( + self.tracking_uri + or os.environ.get('MLFLOW_TRACKING_URI') + or pathlib.Path(os.path.abspath(self.savedir)).as_uri() + ) def create_logger_context(self, rank: Optional[int] = None) -> mlflow.ActiveRun: """ @@ -514,6 +514,10 @@ def create_logger_context(self, rank: Optional[int] = None) -> mlflow.ActiveRun: self.active_run: mlflow.ActiveRun = mlflow.start_run( description=self.run_description, run_name=self.run_name ) + + # TODO: for pytorch lightning: + # mlflow.pytorch.autolog() + return self.active_run def destroy_logger_context(self): @@ -1133,6 +1137,17 @@ def log( prov4ml.log_dataset(dataset=item, label=identifier) else: prov4ml.log_param(key=identifier, value=item) + elif kind == "prov_documents": + prov_docs = prov4ml.log_provenance_documents( + create_graph=True, + create_svg=True + ) + + # Upload to MLFlow + if mlflow.active_run() is not None: + for f in prov_docs: + if f: + mlflow.log_artifact(f) class EpochTimeTracker: diff --git a/src/itwinai/torch/distributed.py b/src/itwinai/torch/distributed.py index 42a5cf066..26949335b 100644 --- a/src/itwinai/torch/distributed.py +++ b/src/itwinai/torch/distributed.py @@ -1,6 +1,7 @@ import abc +import functools import os -from typing import Any, Iterable, List, Literal, Optional, Tuple, Union +from typing import Any, Callable, Iterable, List, Literal, Optional, Tuple, Union import torch import torch.distributed as dist @@ -22,7 +23,23 @@ def distributed_resources_available() -> bool: Returns: bool: env can support distributed ML. """ - return torch.cuda.is_available() and torch.cuda.device_count() > 1 + force_dist_env = int(os.environ.get('ITWINAI_FORCE_DIST', '0')) + return force_dist_env or torch.cuda.is_available() and torch.cuda.device_count() > 1 + + +def check_initialized(method: Callable) -> Callable: + """Decorator for strategy methods to check whether the strategy + was correctly initialized before calling the method.""" + + @functools.wraps(method) + def wrapper(self: 'TorchDistributedStrategy', *args, **kwargs): + if not self.is_initialized: + raise UninitializedStrategyError(( + f"{self.__class__.__name__} has not been initialized. " + "Use the init method.")) + return method(self, *args, **kwargs) + + return wrapper class TorchDistributedStrategy(DistributedStrategy): @@ -41,29 +58,19 @@ class TorchDistributedStrategy(DistributedStrategy): name: str @property + @check_initialized def is_main_worker(self) -> bool: """Checks if local worker has global rank equal to zero. Returns: bool: True if main worker. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.global_rank() == 0 @abc.abstractmethod def init(self) -> None: """Initializes the chosen distributed backend""" - # @abc.abstractmethod - # def distributed_engine( - # self, model: nn.Module, optimizer: Optimizer, - # lr_scheduler: Optional[LRScheduler] = None - # ) -> ModelEngine: - # """Build a distributed model engine.""" - @abc.abstractmethod def distributed( self, @@ -108,16 +115,13 @@ def local_rank(self) -> int: int: local rank. """ + @check_initialized def device(self) -> str: """Device used by local worker. Returns: str: torch device in the form 'cuda:N'. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return f"cuda:{self.local_rank()}" def set_device(self): @@ -126,6 +130,7 @@ def set_device(self): # Needed by torch.distributed.gather_object torch.cuda.set_device(self.local_rank()) + @check_initialized def create_dataloader( self, dataset: Dataset[T_co], @@ -286,10 +291,6 @@ def create_dataloader( .. _Dataset Types: https://pytorch.org/docs/stable/data.html#dataset-types """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if batch_sampler is not None: print("WARNING: batch_sampler is ignored by TorchDistributedStrategy") @@ -396,7 +397,9 @@ def init(self) -> None: which is already initialized. """ if not distributed_resources_available(): - raise RuntimeError("Trying to run distributed on insufficient resources.") + raise RuntimeError( + "Trying to run distributed on insufficient resources." + ) if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") dist.init_process_group(backend=self.backend) @@ -404,30 +407,7 @@ def init(self) -> None: self.set_device() - # def distributed_engine( - # self, model: nn.Module, optimizer: Optimizer, - # lr_scheduler: Optional[LRScheduler] = None, - # mixed_precision: bool = False - # ) -> ModelEngine: - # """Build a distributed model engine.""" - # if torch.cuda.is_available(): - # # device = self.dist_lrank() - # model = model.to(self.dist_device()) - # dist_model = torch.nn.parallel.DistributedDataParallel( - # model, - # device_ids=[self.dist_device()], - # output_device=self.dist_device() - # ) - # else: - # dist_model = model - - # model_engine = DDPModelEngine( - # dist_model, optimizer, lr_scheduler, - # mixed_precision=mixed_precision - # ) - - # return model_engine - + @check_initialized def distributed( self, model: nn.Module, @@ -437,10 +417,6 @@ def distributed( **kwargs, ) -> Tuple[nn.Module, Optimizer, Optional[LRScheduler]]: """Setup model, optimizer and scheduler for distributed.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if torch.cuda.is_available(): # device = self.dist_lrank() model = model.to(self.device()) @@ -455,18 +431,16 @@ def distributed( return dist_model, optimizer, lr_scheduler + @check_initialized def global_world_size(self) -> int: """Returns the total number of processes (global world size). Returns: int: global world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_world_size() + @check_initialized def local_world_size(self) -> int: """Returns the local number of workers available per node, which is usually the number of GPUs available. @@ -474,12 +448,9 @@ def local_world_size(self) -> int: Returns: int: local world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return torch.cuda.device_count() + @check_initialized def global_rank(self) -> int: """Returns the global rank of the current process, where rank ranges from 0 to world_size. @@ -487,34 +458,25 @@ def global_rank(self) -> int: Returns: int: global rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_rank() + @check_initialized def local_rank(self) -> int: """Returns the local rank of the current process. Returns: int: local rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_rank() % torch.cuda.device_count() + @check_initialized def clean_up(self) -> None: """Destroys the current process group.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if torch.cuda.is_available(): dist.barrier() dist.destroy_process_group() + @check_initialized def allgather_obj(self, obj: Any) -> List[Any]: """All-gathers any object from the whole group in a list (to all workers). @@ -526,14 +488,11 @@ def allgather_obj(self, obj: Any) -> List[Any]: List[Any]: List of gathered objects. """ # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) res = [None] * self.global_world_size() dist.all_gather_object(res, obj) return res + @check_initialized def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: """Gathers any object from the whole group in a list (to all workers). @@ -548,10 +507,6 @@ def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: or ``None`` on non-destination ranks. """ # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if self.global_rank() == dst_rank: res = [None] * self.global_world_size() dist.gather_object(obj, res, dst=dst_rank) @@ -559,12 +514,9 @@ 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]: # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) # Ensure that the tensor is on the correct device (CUDA) tensor = tensor.to(self.device()) @@ -614,16 +566,19 @@ def init(self) -> None: self.deepspeed = deepspeed if not distributed_resources_available(): - raise RuntimeError("Trying to run distributed on insufficient resources.") + raise RuntimeError( + "Trying to run distributed on insufficient resources." + ) if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") # https://github.com/Lightning-AI/pytorch-lightning/issues/13567 - ompi_lrank = os.environ.get("OMPI_COMM_WORLD_LOCAL_RANK") - os.environ["OMPI_COMM_WORLD_LOCAL_RANK"] = os.environ.get( - "LOCAL_RANK", ompi_lrank - ) + # This block of code should be removed as some point + if os.environ.get('LOCAL_RANK'): + os.environ['OMPI_COMM_WORLD_LOCAL_RANK'] = os.environ.get( + 'LOCAL_RANK' + ) # https://deepspeed.readthedocs.io/en/latest/initialize.html#training-initialization self.deepspeed.init_distributed(dist_backend=self.backend) @@ -631,6 +586,7 @@ def init(self) -> None: self.set_device() + @check_initialized def distributed( self, model: nn.Module, @@ -640,10 +596,6 @@ def distributed( **init_kwargs, ) -> Tuple[nn.Module, Optimizer, Optional[LRScheduler]]: """Setup model, optimizer and scheduler for distributed.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) distrib_model, optimizer, _, lr_scheduler = self.deepspeed.initialize( model=model, @@ -655,18 +607,16 @@ def distributed( ) return distrib_model, optimizer, lr_scheduler + @check_initialized def global_world_size(self) -> int: """Returns the total number of processes (global world size). Returns: int: global world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_world_size() + @check_initialized def local_world_size(self) -> int: """Returns the local number of workers available per node, which is usually the number of GPUs available. @@ -674,12 +624,9 @@ def local_world_size(self) -> int: Returns: int: local world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return torch.cuda.device_count() + @check_initialized def global_rank(self) -> int: """Returns the global rank of the current process, where rank ranges from 0 to world_size. @@ -687,32 +634,23 @@ def global_rank(self) -> int: Returns: int: global rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_rank() + @check_initialized def local_rank(self) -> int: """Returns the local rank of the current process. Returns: int: local rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return dist.get_rank() % torch.cuda.device_count() + @check_initialized def clean_up(self) -> None: """Destroys the current process group.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) # deepspeed.sys.exit() # disabled as it kills the execution + @check_initialized def allgather_obj(self, obj: Any) -> List[Any]: """All-gathers any object from the whole group in a list (to all workers). @@ -724,14 +662,11 @@ def allgather_obj(self, obj: Any) -> List[Any]: List[Any]: List of gathered objects. """ # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) res = [None] * self.global_world_size() dist.all_gather_object(res, obj) return res + @check_initialized def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: """Gathers any object from the whole group in a list (to all workers). @@ -746,10 +681,6 @@ def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: or ``None`` on non-destination ranks. """ # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if self.global_rank() == dst_rank: res = [None] * self.global_world_size() dist.gather_object(obj, res, dst=dst_rank) @@ -757,12 +688,21 @@ def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[List[Any]]: dist.gather_object(obj, dst=dst_rank) - def gather(self, tensor: torch.Tensor, dst_rank: int = 0) -> Optional[List]: + @check_initialized + 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). + + Args: + obj (Any): object to gather from all workers. + dst_rank (int): rank of the worker on which the objects list + are gathered. + + Returns: + Optional[List[torch.Tensor]]: list of tensors gathered from all workers + or ``None`` on non-destination ranks. + """ # https://pytorch.org/docs/stable/distributed.html#collective-functions - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) # Ensure that the tensor is on the correct device (CUDA) tensor = tensor.to(self.device()) @@ -797,7 +737,9 @@ def init(self) -> None: already initialized. """ if not distributed_resources_available(): - raise RuntimeError("Trying to run distributed on insufficient resources.") + raise RuntimeError( + "Trying to run distributed on insufficient resources." + ) if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") @@ -810,6 +752,7 @@ def init(self) -> None: self.set_device() + @check_initialized def distributed( self, model: nn.Module, @@ -818,10 +761,6 @@ def distributed( **optim_kwargs, ) -> Tuple[nn.Module, Optimizer, Optional[LRScheduler]]: """Setup model, optimizer and scheduler for distributed.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) model.to(self.device()) @@ -854,18 +793,16 @@ def _broadcast_params(self, model: nn.Module, optimizer: optim.Optimizer) -> Non self.hvd.broadcast_parameters(model.state_dict(), root_rank=0) self.hvd.broadcast_optimizer_state(optimizer, root_rank=-0) + @check_initialized def global_world_size(self) -> int: """Returns the total number of processes (global world size). Returns: int: global world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.hvd.size() + @check_initialized def local_world_size(self) -> int: """Returns the local number of workers available per node, which is usually the number of GPUs available. @@ -873,12 +810,9 @@ def local_world_size(self) -> int: Returns: int: local world size. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.hvd.local_size() + @check_initialized def global_rank(self) -> int: """Returns the global rank of the current process, where rank ranges from 0 to world_size. @@ -886,84 +820,75 @@ def global_rank(self) -> int: Returns: int: global rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.hvd.rank() + @check_initialized def local_rank(self) -> int: """Returns the local rank of the current process. Returns: int: local rank. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.hvd.local_rank() + @check_initialized def clean_up(self) -> None: """Shuts Horovod down.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) self.hvd.shutdown() + @check_initialized def allgather_obj(self, obj: Any) -> list[Any]: - """All-gathers scalar objects across all workers to a - list with size(#worker), uses horovod communicator + """All-gathers any object from the whole group + in a list (to all workers). Args: - obj (Any): object in a worker. + obj (Any): Object to gather from all workers. Returns: - list: gathered list with size(#worker). + List[Any]: List of gathered objects. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) return self.hvd.allgather_object(obj) - def gather_obj(self, obj: Any, dst_rank: int = 0) -> list[Any]: - """The same as ``allgather_obj``, as gather is not supported - by Horovod. + @check_initialized + def gather_obj(self, obj: Any, dst_rank: int = 0) -> Optional[list[Any]]: + """Gathers any object from the whole group in a list + (to all workers). Under the hood it relies on allgather as gather is + not supported by Horovod. Args: - obj (Any): object in a worker. - dst_rank (int): ignored. + obj (Any): object to gather from all workers. + dst_rank (int): rank of the worker on which the objects list + are gathered. Returns: - list: gathered list with size(#worker). + Optional[List[Any]]: list of objects gathered from all workers + or ``None`` on non-destination ranks. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) - return self.allgather_obj(obj) + result = self.allgather_obj(obj) + if self.global_rank() == dst_rank: + # Return only if on rank == dst_rank + return result - def gather(self, tensor: torch.Tensor, dst_rank: int = 0): - """The same as ``allgather_obj``, as gather is not supported - by Horovod. + @check_initialized + 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. Args: - tensor (Any): object in a worker. - dst_rank (int): ignored. + obj (Any): object to gather from all workers. + dst_rank (int): rank of the worker on which the objects list + are gathered. Returns: - list: gathered list with size(#worker). + Optional[List[torch.Tensor]]: list of tensors gathered from all workers + or ``None`` on non-destination ranks. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) - - # Moving all the tensors to CPU before returning result = self.allgather_obj(tensor) - return [val.cpu() for val in result] + if self.global_rank() == dst_rank: + # Return only if on rank == dst_rank + # Moving all the tensors to CPU before returning + return [val.cpu() for val in result] class NonDistributedStrategy(TorchDistributedStrategy): @@ -991,20 +916,18 @@ def init(self) -> None: self.set_device() self.is_initialized = True + @check_initialized def device(self) -> str: """Device used by local worker. Returns: str: cpu device if CUDA is not available. """ - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if torch.cuda.is_available(): return super().device() return "cpu" + @check_initialized def distributed( self, model: nn.Module, @@ -1013,10 +936,6 @@ def distributed( **kwargs, ) -> Tuple[nn.Module, Optimizer, Optional[LRScheduler]]: """Do nothing and return model, optimizer and scheduler.""" - if not self.is_initialized: - raise UninitializedStrategyError( - "Strategy has not been initialized. Use the init method." - ) if torch.cuda.is_available(): model = model.cuda() return model, optimizer, lr_scheduler diff --git a/tests/components/test_components.py b/tests/components/test_components.py index 890188d7c..f61e982ea 100644 --- a/tests/components/test_components.py +++ b/tests/components/test_components.py @@ -1,11 +1,14 @@ import pytest -from itwinai.components import Trainer, Adapter +from itwinai.components import Adapter, Trainer from itwinai.pipeline import Pipeline +from itwinai.serialization import SerializationError from itwinai.tests import ( - FakeGetterExec, FakeSplitterExec, FakeTrainerExec, FakeSaverExec + FakeGetterExec, + FakeSaverExec, + FakeSplitterExec, + FakeTrainerExec, ) -from itwinai.serialization import SerializationError def test_serializable(): diff --git a/tests/components/test_pipe_parser.py b/tests/components/test_pipe_parser.py index f26d105db..381a64f15 100644 --- a/tests/components/test_pipe_parser.py +++ b/tests/components/test_pipe_parser.py @@ -1,9 +1,9 @@ -import yaml import pytest +import yaml from itwinai.components import BaseComponent from itwinai.parser import ConfigParser, add_replace_field -from itwinai.tests import FakeTrainer, FakePreproc, FakeSaver +from itwinai.tests import FakePreproc, FakeSaver, FakeTrainer def test_add_replace_field(): diff --git a/tests/components/test_pipeline.py b/tests/components/test_pipeline.py index a61198b60..c11b95009 100644 --- a/tests/components/test_pipeline.py +++ b/tests/components/test_pipeline.py @@ -1,10 +1,13 @@ -import yaml import pytest +import yaml -from itwinai.pipeline import Pipeline from itwinai.parser import ConfigParser +from itwinai.pipeline import Pipeline from itwinai.tests import ( - FakeGetterExec, FakeSplitterExec, FakeTrainerExec, FakeSaverExec + FakeGetterExec, + FakeSaverExec, + FakeSplitterExec, + FakeTrainerExec, ) diff --git a/tests/conftest.py b/tests/conftest.py index 5082f31b6..936922aa0 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,4 +1,5 @@ import os + import pytest diff --git a/tests/test_loggers.py b/tests/test_loggers.py index 06d737a6f..ac365820c 100644 --- a/tests/test_loggers.py +++ b/tests/test_loggers.py @@ -1,16 +1,18 @@ -import pytest import shutil +from unittest.mock import MagicMock, patch + import numpy as np -from unittest.mock import patch, MagicMock +import pytest from itwinai.loggers import ( ConsoleLogger, + LoggersCollection, MLFlowLogger, - WandBLogger, + Prov4MLLogger, TensorBoardLogger, - LoggersCollection, - Prov4MLLogger + WandBLogger, ) + # from prov4ml.provenance.context import Context diff --git a/tests/test_utils.py b/tests/test_utils.py index 5fb7b9367..7dc59a57b 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -2,7 +2,7 @@ Tests for itwinai.utils module. """ -from itwinai.utils import flatten_dict, SignatureInspector +from itwinai.utils import SignatureInspector, flatten_dict def test_flatten_dict(): diff --git a/tests/torch/conftest.py b/tests/torch/conftest.py new file mode 100644 index 000000000..faedda2d1 --- /dev/null +++ b/tests/torch/conftest.py @@ -0,0 +1,38 @@ +from typing import Generator + +import pytest +import torch + +from itwinai.torch.distributed import ( + DeepSpeedStrategy, + HorovodStrategy, + TorchDDPStrategy, + TorchDistributedStrategy, +) + + +@pytest.fixture(scope='package') +def ddp_strategy() -> Generator[TorchDistributedStrategy, None, None]: + """Instantiate Torch's DistributedDataParallel strategy.""" + strategy = TorchDDPStrategy(backend='nccl' if torch.cuda.is_available() else 'gloo') + strategy.init() + yield strategy + strategy.clean_up() + + +@pytest.fixture(scope='package') +def deepspeed_strategy() -> Generator[DeepSpeedStrategy, None, None]: + """Instantiate DeepSpeed strategy.""" + strategy = DeepSpeedStrategy(backend='nccl' if torch.cuda.is_available() else 'gloo') + strategy.init() + yield strategy + strategy.clean_up() + + +@pytest.fixture(scope='package') +def horovod_strategy() -> Generator[HorovodStrategy, None, None]: + """Instantiate Horovod strategy.""" + strategy = HorovodStrategy() + strategy.init() + yield strategy + strategy.clean_up() diff --git a/tests/torch/distribtued_decorator.py b/tests/torch/distribtued_decorator.py index fd0861545..1f4681a36 100644 --- a/tests/torch/distribtued_decorator.py +++ b/tests/torch/distribtued_decorator.py @@ -8,12 +8,12 @@ """ import torch -from torch import nn import torch.nn.functional as F -from torch.utils.data import DataLoader -from torchvision import transforms, datasets import torch.optim as optim +from torch import nn from torch.optim.lr_scheduler import StepLR +from torch.utils.data import DataLoader +from torchvision import datasets, transforms from itwinai.torch.trainer import distributed diff --git a/tests/torch/runall.sh b/tests/torch/runall.sh new file mode 100644 index 000000000..224781322 --- /dev/null +++ b/tests/torch/runall.sh @@ -0,0 +1,63 @@ +#!/bin/bash + +# -------------------------------------------------------------------------------------- +# Part of the interTwin Project: https://www.intertwin.eu/ +# +# Created by: Matteo Bunino +# +# Credit: +# - Matteo Bunino - CERN +# -------------------------------------------------------------------------------------- + +# DISCLAIMER: +# this script is here to support the development, so it may not be maintained and it may be a bit "rough". +# Do not mind it too much. + +# Python virtual environment +PYTHON_VENV="../../.venv-pytorch" + +# Clear SLURM logs (*.out and *.err files) +rm -rf logs_slurm +mkdir logs_slurm +rm -rf logs_torchrun logs_mpirun logs_srun + +# Adapt with a path reachable by you +export MNIST_PATH="/ceph/hpc/data/st2301-itwin-users/mbunino/mnist" #"/p/project1/intertwin/smalldata/mnist" + +# Containers +# - itwinai_torch.sif: cmcc jlab container (OMPI v5) +# - itwinai_torch2.sif: itwinai 0.2.2.dev torch2.4 (OMPI v4.1) +# - itwinai_torch3.sif: itwinai 0.2.2.dev2 torch2.4 - force distributed (OMPI v4.1) +# - itwinai_torch4.sif: cmcc jlab container (OMPI v4.1) +# - /ceph/hpc/data/st2301-itwin-users/mbunino/jlab_simple_reconstructed_nv_itwinai.sif: jlab container recostructed from simple (OMPI v4.1) +export CONTAINER_PATH="/ceph/hpc/data/st2301-itwin-users/mbunino/jlab_simple_reconstructed_nv_itwinai.sif" + +# Disable pytest ANSI coloring +export NO_COLOR=1 + +export DIST_MODE="ddp" +export RUN_NAME="ddp-itwinai" +export COMMAND='pytest -v -m torch_dist' +sbatch \ + --job-name="$RUN_NAME-n$N" \ + --output="logs_slurm/job-$RUN_NAME-n$N.out" \ + --error="logs_slurm/job-$RUN_NAME-n$N.err" \ + slurm.vega.sh + +export DIST_MODE="deepspeed" +export RUN_NAME="ds-itwinai" +export COMMAND='pytest -v -m deepspeed_dist' +sbatch \ + --job-name="$RUN_NAME-n$N" \ + --output="logs_slurm/job-$RUN_NAME-n$N.out" \ + --error="logs_slurm/job-$RUN_NAME-n$N.err" \ + slurm.vega.sh + +export DIST_MODE="horovod" +export RUN_NAME="horovod-itwinai" +export COMMAND="pytest -v -m horovod_dist" +sbatch \ + --job-name="$RUN_NAME-n$N" \ + --output="logs_slurm/job-$RUN_NAME-n$N.out" \ + --error="logs_slurm/job-$RUN_NAME-n$N.err" \ + slurm.vega.sh \ No newline at end of file diff --git a/tests/torch/slurm.vega.sh b/tests/torch/slurm.vega.sh new file mode 100644 index 000000000..b44da5b76 --- /dev/null +++ b/tests/torch/slurm.vega.sh @@ -0,0 +1,237 @@ +#!/bin/bash + +# SLURM jobscript for Vega systems + +# Job configuration +#SBATCH --job-name=3dgan_training +#SBATCH --account=s24r05-03-users +#SBATCH --mail-user= +#SBATCH --mail-type=ALL +#SBATCH --output=job.out +#SBATCH --error=job.err +#SBATCH --time=00:10:00 + +# Resources allocation +#SBATCH --partition=gpu +#SBATCH --nodes=2 +#SBATCH --gpus-per-node=4 +#SBATCH --cpus-per-gpu=4 +#SBATCH --ntasks-per-node=1 +# SBATCH --mem-per-gpu=10G +#SBATCH --exclusive + +# gres options have to be disabled for deepv +#SBATCH --gres=gpu:4 + +echo "DEBUG: SLURM_SUBMIT_DIR: $SLURM_SUBMIT_DIR" +echo "DEBUG: SLURM_JOB_ID: $SLURM_JOB_ID" +echo "DEBUG: SLURM_JOB_NODELIST: $SLURM_JOB_NODELIST" +echo "DEBUG: SLURM_NNODES: $SLURM_NNODES" +echo "DEBUG: SLURM_NTASKS: $SLURM_NTASKS" +echo "DEBUG: SLURM_TASKS_PER_NODE: $SLURM_TASKS_PER_NODE" +echo "DEBUG: SLURM_SUBMIT_HOST: $SLURM_SUBMIT_HOST" +echo "DEBUG: SLURMD_NODENAME: $SLURMD_NODENAME" +echo "DEBUG: CUDA_VISIBLE_DEVICES: $CUDA_VISIBLE_DEVICES" + +ml --force purge +ml Python CMake/3.24.3-GCCcore-11.3.0 mpi4py OpenMPI/4.1.5-GCC-12.3.0 CUDA/12.3 +ml GCCcore/11.3.0 NCCL cuDNN/8.9.7.29-CUDA-12.3.0 +ml UCX-CUDA/1.15.0-GCCcore-13.2.0-CUDA-12.3.0 + +# ml Python +module unload OpenSSL + +source ~/.bashrc + +# Setup env for distributed ML +export CUDA_VISIBLE_DEVICES="0,1,2,3" +export OMP_NUM_THREADS=1 +if [ "$SLURM_CPUS_PER_GPU" -gt 0 ] ; then + export OMP_NUM_THREADS=$SLURM_CPUS_PER_GPU +fi + +# Launch distributed job in container with torchrun +torchrun_launcher () +{ + # Avoid propagating PYTHONPATH to the singularity container, as it breaks the import of packages inside the container + # https://docs.sylabs.io/guides/4.1/user-guide/environment_and_metadata.html#environment-from-the-host + unset PYTHONPATH + + # --no-python is needed when running commands which are not python scripts (e.g., pytest, itwinai) + # --redirects=\$(((SLURM_NODEID)) && echo "3" || echo "1:3,2:3,3:3"): redirect stdout and stderr to + # torchrun logs dir for workers having rank !=0 + srun --cpu-bind=none --ntasks-per-node=1 \ + singularity exec --nv $CONTAINER_PATH /bin/bash -c "torchrun \ + --log_dir='logs_torchrun' \ + --nnodes=$SLURM_NNODES \ + --nproc_per_node=$SLURM_GPUS_PER_NODE \ + --node-rank=$SLURM_NODEID \ + --rdzv_id=$SLURM_JOB_ID \ + --rdzv_conf=is_host=\$(((SLURM_NODEID)) && echo 0 || echo 1) \ + --rdzv_backend=c10d \ + --rdzv_endpoint=$(scontrol show hostnames "$SLURM_JOB_NODELIST" | head -n 1):29500 \ + --no-python \ + --redirects=\$(((SLURM_NODEID)) && echo "3" || echo "1:3,2:3,3:3") \ + ${1}" +} + +# Launch distribtued job in container with mpirun +mpirun_launcher () +{ + # https://doc.vega.izum.si/mpi/#multi-node-jobs + export UCX_TLS=self,sm,rc,ud + export OMPI_MCA_PML="ucx" + export OMPI_MCA_osc="ucx" + + # Get the node list from Slurm + NODELIST=$(scontrol show hostnames "$SLURM_NODELIST") + SLOTS_PER_NODE=${SLURM_GPUS_PER_NODE:-1} + + # Create the string for horovodrun format, e.g., "node1:4,node2:4,..." + HOSTFILE="" + for NODE in $NODELIST; do + if [ -z "$HOSTFILE" ]; then + # First node, no comma + HOSTFILE="$NODE:$SLOTS_PER_NODE" + else + # Subsequent nodes, prepend comma + HOSTFILE="$HOSTFILE,$NODE:$SLOTS_PER_NODE" + fi + done + + # Display the generated hostfile (optional) + echo "Generated host string: $HOSTFILE" + + # Calculate the total number of processes (GPUs in this case) + TOTAL_PROCESSES=$(($SLURM_GPUS_PER_NODE * $SLURM_NNODES)) + + # Calculate the total number of processes (GPUs in this case) + echo "SLURM_GPUS_PER_NODE: $SLURM_GPUS_PER_NODE" + echo "SLURM_NNODES: $SLURM_NNODES" + echo "TOTAL_MPI_PROCESSES: $TOTAL_PROCESSES" + echo "SLURM_CPUS_PER_GPU: $SLURM_CPUS_PER_GPU" + echo + + # # Get OpenMPI installation prefixes (locally and in container) + # OMPI_CONTAINER="$(singularity exec ${CONTAINER_PATH} /bin/bash -c 'ompi_info' | grep Prefix | awk '{ print $2 }')" + # OMPI_HOST="$(ompi_info | grep Prefix | awk '{ print $2 }')" + # # If you want to explicitly mount host OpenMPI in container use --bind "${OMPI_HOST}":"${OMPI_CONTAINER}" + + # Avoid propagating PYTHONPATH to the singularity container, as it breaks the import of packages inside the container + # https://docs.sylabs.io/guides/4.1/user-guide/environment_and_metadata.html#environment-from-the-host + unset PYTHONPATH + + # Create mpirun logs folder + mkdir -p "logs_mpirun/$SLURM_JOB_ID" + + # https://doc.vega.izum.si/mpi/#multi-node-jobs + # "if [ $OMPI_COMM_WORLD_RANK -ne 0 ]; then exec > "logs_mpirun/$SLURM_JOB_ID/rank.$OMPI_COMM_WORLD_RANK" 2>&1; fi; exec" redirects stdout and stderr of ranks != 0 + # Logs of the main woker (rank == 0) will be incorportated into the standard SLURM out and err files + mpirun -H "${HOSTFILE}" -np $TOTAL_PROCESSES --oversubscribe -mca pml ucx -mca btl ^uct,tcp,openib,vader --bind-to core \ + singularity exec --nv \ + "${CONTAINER_PATH}" /bin/bash -c \ + 'echo "Rank: $OMPI_COMM_WORLD_RANK, lrank: $OMPI_COMM_WORLD_LOCAL_RANK, Size: $OMPI_COMM_WORLD_SIZE, LD_LIBRARY_PATH=$LD_LIBRARY_PATH" && \ + if [ $OMPI_COMM_WORLD_RANK -ne 0 ]; then exec > "logs_mpirun/$SLURM_JOB_ID/rank.$OMPI_COMM_WORLD_RANK" 2>&1; fi; exec '"${1}" +} + +# Launch distribtued job in container with srun +srun_launcher () +{ + # Avoid propagating PYTHONPATH to the singularity container, as it breaks the import of packages inside the container + # https://docs.sylabs.io/guides/4.1/user-guide/environment_and_metadata.html#environment-from-the-host + unset PYTHONPATH + + # Create mpirun logs folder + mkdir -p "logs_srun/$SLURM_JOB_ID" + + # # Get OpenMPI installation prefixes (locally and in container) + # OMPI_CONTAINER="$(singularity exec ${CONTAINER_PATH} /bin/bash -c 'ompi_info' | grep Prefix | awk '{ print $2 }')" + # OMPI_HOST="$(ompi_info | grep Prefix | awk '{ print $2 }')" + # # If you want to explicitly mount host OpenMPI in container use --bind "${OMPI_HOST}":"${OMPI_CONTAINER}" + + # "if [ $SLURM_PROCID -ne 0 ]; then exec > "logs_srun/$SLURM_JOB_ID/rank.$SLURM_PROCID" 2>&1; fi; exec" redirects stdout and stderr of ranks != 0 + # Logs of the main woker (rank == 0) will be incorportated into the standard SLURM out and err files + srun --mpi=pmix_v3 --cpu-bind=none --ntasks-per-node=$SLURM_GPUS_PER_NODE --cpus-per-task=$SLURM_CPUS_PER_GPU --ntasks=$(($SLURM_GPUS_PER_NODE * $SLURM_NNODES)) \ + singularity exec --nv \ + "${CONTAINER_PATH}" /bin/bash -c \ + 'echo "Rank: $SLURM_PROCID, LD_LIBRARY_PATH=$LD_LIBRARY_PATH" && \ + if [ $SLURM_PROCID -ne 0 ]; then exec > "logs_srun/$SLURM_JOB_ID/rank.$SLURM_PROCID" 2>&1; fi; exec '"${1}" +} + +# Dual echo on both stdout and stderr +decho () +{ + echo "$@" + >&2 echo "$@" +} + + +###################### Initial checks ###################### + +# Env vairables check +if [ -z "$DIST_MODE" ]; then + >&2 echo "ERROR: env variable DIST_MODE is not set. Allowed values are 'horovod', 'ddp' or 'deepspeed'" + exit 1 +fi +if [ -z "$RUN_NAME" ]; then + >&2 echo "WARNING: env variable RUN_NAME is not set. It's a way to identify some specific run of an experiment." + RUN_NAME=$DIST_MODE +fi +if [ -z "$COMMAND" ]; then + >&2 echo "ERROR: env variable COMMAND is not set. It's the python command to execute." + exit 1 +fi +if [ -z "$CONTAINER_PATH" ]; then + >&2 echo "WARNING: env variable CONTAINER_PATH is not set. It's the path to a singularity container." + exit 1 +fi + +# OpenMPI version +HOST_OMPI_V="$(ompi_info --parsable | grep ompi:version:full: | cut -d':' -f4 | cut -d'.' -f1,2)" +CONTAINER_OMPI_V="$(singularity exec $CONTAINER_PATH ompi_info --parsable | grep ompi:version:full: | cut -d':' -f4 | cut -d'.' -f1,2)" + +if [ "$HOST_OMPI_V" != "$CONTAINER_OMPI_V" ]; then + >&2 echo "ERROR: Host OpenMPI minor version ($HOST_OMPI_V) does not match with container's OpenMPI minor version ($CONTAINER_OMPI_V). This may cause problems." + exit 1 +fi +echo -e "\nHost and container's OpenMPI minor versions match: ($HOST_OMPI_V) - ($CONTAINER_OMPI_V)\n" + +# Get GPUs info per node +srun --cpu-bind=none --ntasks-per-node=1 bash -c 'echo -e "NODE hostname: $(hostname)\n$(nvidia-smi)\n\n"' + +# Print env variables +echo "RUN_NAME: $RUN_NAME" +echo "DIST_MODE: $DIST_MODE" +echo "CONTAINER_PATH: $CONTAINER_PATH" +echo "COMMAND: $COMMAND" + +###################### Execute command ###################### + +if [ "${DIST_MODE}" == "ddp" ] ; then + + decho -e "\nLaunching DDP strategy with torchrun" + torchrun_launcher "${COMMAND}" + +elif [ "${DIST_MODE}" == "deepspeed" ] ; then + + decho -e "\nLaunching DeepSpeed strategy with torchrun" + torchrun_launcher "${COMMAND}" + + decho -e "\nLaunching DeepSpeed strategy with mpirun" + mpirun_launcher "python -m ${COMMAND}" + + decho -e "\nLaunching DeepSpeed strategy with srun" + srun_launcher "python -m ${COMMAND}" + +elif [ "${DIST_MODE}" == "horovod" ] ; then + + decho -e "\nLaunching Horovod strategy with mpirun" + mpirun_launcher "python -m ${COMMAND}" + + decho -e "\nLaunching Horovod strategy with srun" + srun_launcher "python -m ${COMMAND}" + +else + >&2 echo "ERROR: unrecognized \$DIST_MODE env variable" + exit 1 +fi diff --git a/tests/torch/test_config.py b/tests/torch/test_config.py index 8a81578ac..701d521e7 100644 --- a/tests/torch/test_config.py +++ b/tests/torch/test_config.py @@ -1,7 +1,8 @@ import pytest -from itwinai.torch.config import TrainingConfiguration from pydantic import ValidationError +from itwinai.torch.config import TrainingConfiguration + def test_values_parsing(): """Check dynamic override and creation of new entries.""" diff --git a/tests/torch/test_distribtued_training.py b/tests/torch/test_distribtued_training.py deleted file mode 100644 index f09f27205..000000000 --- a/tests/torch/test_distribtued_training.py +++ /dev/null @@ -1,25 +0,0 @@ -"""Test distributed training strategies.""" - -import subprocess -import pytest - - -@pytest.mark.slurm -def test_distributed_decorator(torch_env): - """Test function decorator. Needs torchrun cmd.""" - cmd = (f"{torch_env}/bin/torchrun " - " --nnodes=1 --nproc_per_node=2 --rdzv_id=100 " - "--rdzv_backend=c10d --rdzv_endpoint=localhost:29400 " - "tests/torch/distribtued_decorator.py") - subprocess.run(cmd.split(), check=True) - - -@pytest.mark.skip(reason="TorchTrainer not implemented yet") -@pytest.mark.slurm -def test_distributed_trainer(torch_env): - """Test vanilla torch distributed trainer. Needs torchrun cmd.""" - cmd = (f"{torch_env}/bin/torchrun " - "--nnodes=1 --nproc_per_node=2 --rdzv_id=100 " - "--rdzv_backend=c10d --rdzv_endpoint=localhost:29400 " - "tests/torch/torch_dist_trainer.py") - subprocess.run(cmd.split(), check=True) diff --git a/tests/torch/test_distributed.py b/tests/torch/test_distributed.py new file mode 100644 index 000000000..09793b00b --- /dev/null +++ b/tests/torch/test_distributed.py @@ -0,0 +1,282 @@ +"""Test distributed training strategies.""" + +from typing import Any +from unittest.mock import patch + +import pytest +import torch +import torch.nn as nn +from torch.nn import Linear +from torch.optim import SGD, Optimizer +from torch.utils.data import DataLoader, Dataset, DistributedSampler + +from itwinai.torch.distributed import ( + DeepSpeedStrategy, + HorovodStrategy, + TorchDDPStrategy, + TorchDistributedStrategy, +) +from itwinai.torch.type import DistributedStrategyError, UninitializedStrategyError + + +class DummyDataset(Dataset): + def __init__(self, size=100): + self.size = size + self.data = torch.randn(size, 10) + self.targets = torch.randint(0, 2, (size,)) + + def __len__(self): + return self.size + + def __getitem__(self, idx): + return self.data[idx], self.targets[idx] + + +class BaseTestDistributedStrategy: + @pytest.fixture(scope='module') + def strategy(self): + """To be overridden by subclasses with the specific strategy.""" + raise NotImplementedError + + @pytest.fixture + def simple_model(self): + return Linear(10, 2) + + @pytest.fixture + def optimizer(self, simple_model: nn.Module): + return SGD(simple_model.parameters(), lr=0.01) + + @pytest.fixture + def dataset(self): + return DummyDataset() + + def test_cluster_properties(self, strategy: TorchDistributedStrategy): + """Test that ranks and other simple properties are computed correctly.""" + assert strategy.is_initialized + assert isinstance(strategy.device(), str) + assert isinstance(strategy.is_main_worker, bool) + assert strategy.global_world_size() >= 1 + assert strategy.local_world_size() >= 1 + assert strategy.global_rank() >= 0 + assert strategy.local_rank() >= 0 + + def test_init_exceptions( + self, + strategy: TorchDistributedStrategy, + simple_model: nn.Module, + optimizer: Any + ): + """Check that the init method cannot be called twice and that the other methods raise + and exception if called when the strategy is not initialized.""" + # Test re-initialization + with pytest.raises(DistributedStrategyError) as init_exc: + strategy.init() + assert "already initialized" in init_exc.value + + # Test initialized flag + strategy.is_initialized = False + + with pytest.raises(UninitializedStrategyError): + strategy.distributed(simple_model, optimizer) + with pytest.raises(UninitializedStrategyError): + strategy.global_rank() + with pytest.raises(UninitializedStrategyError): + strategy.local_rank() + with pytest.raises(UninitializedStrategyError): + strategy.local_world_size() + with pytest.raises(UninitializedStrategyError): + strategy.global_world_size() + with pytest.raises(UninitializedStrategyError): + strategy.device() + with pytest.raises(UninitializedStrategyError): + strategy.is_main_worker + x = torch.ones(2) + with pytest.raises(UninitializedStrategyError): + strategy.gather(x) + with pytest.raises(UninitializedStrategyError): + strategy.allgather_obj(x) + with pytest.raises(UninitializedStrategyError): + strategy.gather_obj(x) + with pytest.raises(UninitializedStrategyError): + strategy.clean_up() + + strategy.is_initialized = True + + def test_dataloader(self, strategy: TorchDistributedStrategy, dataset: Dataset): + """Check that the dataloader is distributed correctly.""" + dataloader = strategy.create_dataloader(dataset, batch_size=16, shuffle=True) + assert isinstance(dataloader, DataLoader) + assert isinstance(dataloader.sampler, DistributedSampler) + assert dataloader.sampler.rank == strategy.global_rank() + assert dataloader.sampler.num_replicas == strategy.global_world_size() + + def test_gather_operations(self, strategy): + """Test collective operations.""" + # Test tensor gather + local_tensor = torch.tensor([strategy.global_rank()], device=strategy.device()) + gathered = strategy.gather(local_tensor) + if strategy.is_main_worker: + assert len(gathered) == strategy.global_world_size() + else: + assert gathered is None + + # Test tensor gather from CPU + my_tensor = torch.ones(10) * strategy.global_rank() + tensors = strategy.gather(my_tensor, dst_rank=0) + if strategy.is_main_worker: + assert torch.stack(tensors).sum() == sum( + range(strategy.global_world_size())) * 10 + else: + assert tensors is None + + # Test object gather + local_obj = {"rank": strategy.global_rank()} + gathered_obj = strategy.gather_obj(local_obj) + if strategy.is_main_worker: + assert len(gathered_obj) == strategy.global_world_size() + else: + assert gathered_obj is None + + # Test allgather + all_gathered = strategy.allgather_obj(local_obj) + assert len(all_gathered) == strategy.global_world_size() + + def test_ranks(self, strategy): + """Check that the values of the ranks are as expected.""" + nnodes = strategy.global_world_size() // strategy.local_world_size() + + # Test local ranks + lranks = strategy.gather_obj(strategy.local_rank(), dst_rank=0) + if strategy.is_main_worker: + assert len(lranks) == strategy.global_world_size() + assert sum(lranks) == sum(range(strategy.local_world_size())) * nnodes + else: + assert lranks is None + + # Test global ranks + granks = strategy.gather_obj(strategy.global_rank(), dst_rank=0) + if strategy.is_main_worker: + assert len(granks) == strategy.global_world_size() + assert sum(granks) == sum(range(strategy.global_world_size())) + else: + assert granks is None + + +@pytest.mark.hpc +@pytest.mark.torch_dist +class TestTorchDDPStrategy(BaseTestDistributedStrategy): + @pytest.fixture(scope='module') + def strategy(self, ddp_strategy) -> TorchDDPStrategy: + return ddp_strategy + + def test_init(self, strategy: TorchDDPStrategy): + """Test specific initialization of TorchDDPStrategy.""" + assert strategy.backend in ['nccl', 'gloo'] + + # Test initialization + init_path = 'torch.distributed.init_process_group' + with patch(init_path, autospec=True) as mock_init_torch: + strategy = TorchDDPStrategy( + backend='nccl' if torch.cuda.is_available() else 'gloo' + ) + strategy.init() + mock_init_torch.assert_called_once() + + def test_distributed_model( + self, + strategy: TorchDDPStrategy, + simple_model: nn.Module, + optimizer: Optimizer + ): + """Test NN model distribution.""" + from torch.nn.parallel import DistributedDataParallel + dist_model, dist_optimizer, _ = strategy.distributed(simple_model, optimizer) + assert isinstance(dist_model, DistributedDataParallel) + assert hasattr(dist_model, 'module') or isinstance(dist_model, nn.Module) + assert isinstance(dist_optimizer, Optimizer) + + +@pytest.mark.hpc +@pytest.mark.deepspeed_dist +class TestDeepSpeedStrategy(BaseTestDistributedStrategy): + @pytest.fixture(scope='module') + def strategy(self, deepspeed_strategy) -> DeepSpeedStrategy: + return deepspeed_strategy + + def test_init(self, strategy: DeepSpeedStrategy): + """Test specific initialization of DeepSpeedStrategy.""" + assert strategy.backend in ['nccl', 'gloo', 'mpi'] + assert hasattr(strategy, 'deepspeed'), ( + "Lazy import of deepspeed not found in strategy class." + ) + + # Test initialization + init_path = 'deepspeed.init_distributed' + with patch(init_path, autospec=True) as mock_init_ds: + strategy = DeepSpeedStrategy( + backend='nccl' if torch.cuda.is_available() else 'gloo' + ) + strategy.init() + mock_init_ds.assert_called_once() + + def test_distributed_model( + self, + strategy: DeepSpeedStrategy, + simple_model: nn.Module, + optimizer: Optimizer + ): + """Test NN model distribution.""" + from deepspeed.runtime.engine import DeepSpeedEngine + ds_config = { + "train_batch_size": 16, + "fp16": {"enabled": False}, + "optimizer": { + "type": "SGD", + "params": { + "lr": 0.001 + } + } + } + + dist_model, dist_optimizer, _ = strategy.distributed( + simple_model, + optimizer=optimizer, + config=ds_config + ) + assert hasattr(dist_model, 'module') + assert isinstance(dist_model, DeepSpeedEngine) + assert dist_optimizer is not None + assert isinstance(dist_optimizer, Optimizer) + + +@pytest.mark.hpc +@pytest.mark.horovod_dist +class TestHorovodStrategy(BaseTestDistributedStrategy): + @pytest.fixture(scope='module') + def strategy(self, horovod_strategy) -> HorovodStrategy: + return horovod_strategy + + def test_init(self, strategy): + assert strategy.is_initialized + assert hasattr(strategy, 'hvd'), ( + "Lazy import of horovod not found in strategy class." + ) + + # Test initialization + init_path = 'horovod.torch.init' + with patch(init_path, autospec=True) as mock_init_ds: + strategy = HorovodStrategy() + strategy.init() + mock_init_ds.assert_called_once() + + def test_distributed_model(self, strategy, simple_model, optimizer): + dist_model, dist_optimizer, _ = strategy.distributed( + simple_model, + optimizer=optimizer, + op=strategy.hvd.Average + ) + assert isinstance(dist_model, nn.Module) + assert isinstance(dist_optimizer, Optimizer) + assert hasattr(dist_optimizer, 'synchronize'), ( + "synchronize() method not found for Horovod optimizer" + ) diff --git a/tests/torch/test_torch_trainer.py b/tests/torch/test_torch_trainer.py new file mode 100644 index 000000000..471a59b2b --- /dev/null +++ b/tests/torch/test_torch_trainer.py @@ -0,0 +1,87 @@ +import logging +import os + +import pytest +import torch.nn.functional as F +from torch import nn +from torchvision import datasets, transforms + +from itwinai.torch.trainer import TorchTrainer + +MNIST_PATH = "mnist_dataset" + + +class Net(nn.Module): + + def __init__(self): + super(Net, self).__init__() + self.conv1 = nn.Conv2d(1, 10, kernel_size=5) + self.conv2 = nn.Conv2d(10, 20, kernel_size=5) + self.conv2_drop = nn.Dropout2d() + self.fc1 = nn.Linear(320, 50) + self.fc2 = nn.Linear(50, 10) + + def forward(self, x): + x = F.relu(F.max_pool2d(self.conv1(x), 2)) + x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2)) + x = x.view(-1, 320) + x = F.relu(self.fc1(x)) + x = F.dropout(x, training=self.training) + x = self.fc2(x) + return F.log_softmax(x, dim=0) + + +@pytest.fixture(scope='module') +def mnist_datasets(): + """Parse MNIST datasets.""" + if not os.environ.get('MNIST_PATH'): + logging.warning("MNIST dataset not found locally. I have to download it!") + + dataset_path = os.environ.get('MNIST_PATH', MNIST_PATH) + train_set = datasets.MNIST( + dataset_path, + train=True, + download=True, + transform=transforms.Compose([ + transforms.ToTensor(), + transforms.Normalize((0.1307,), (0.3081,)) + ])) + val_set = datasets.MNIST( + dataset_path, + train=False, + download=False, + transform=transforms.Compose([ + transforms.ToTensor(), + transforms.Normalize((0.1307,), (0.3081,)) + ])) + return train_set, val_set + + +@pytest.mark.hpc +@pytest.mark.parametrize( + 'strategy_name,strategy_fixture', + [ + pytest.param('ddp', 'ddp_strategy', marks=pytest.mark.torch_dist), + pytest.param('deepspeed', 'deepspeed_strategy', marks=pytest.mark.deepspeed_dist), + pytest.param('horovod', 'horovod_strategy', marks=pytest.mark.horovod_dist) + ] +) +def test_distributed_trainer_mnist(mnist_datasets, request, strategy_name, strategy_fixture): + """Test TorchTrainer on MNIST with different distributed strategies.""" + training_config = dict( + optimizer='sgd', + loss='nllloss' + ) + trainer = TorchTrainer( + model=Net(), + config=training_config, + epochs=2, + strategy=strategy_name, + checkpoint_every=1 + ) + + strategy_instance = request.getfixturevalue(strategy_fixture) + trainer.strategy = strategy_instance # Patch the strategy with the fixture instance + + train_set, val_set = mnist_datasets + trainer.execute(train_set, val_set) diff --git a/tests/torch/torch_dist_trainer.py b/tests/torch/torch_dist_trainer.py deleted file mode 100644 index 63871f4a3..000000000 --- a/tests/torch/torch_dist_trainer.py +++ /dev/null @@ -1,62 +0,0 @@ -""" -Test Trainer class. To run this script, use the following command: - ->>> torchrun --nnodes=1 --nproc_per_node=2 --rdzv_id=100 --rdzv_backend=c10d \ - --rdzv_endpoint=localhost:29400 torch_dist_trainer.py - -""" - -from torch import nn -import torch.nn.functional as F -from torch.utils.data import DataLoader -from torchvision import transforms, datasets - -from itwinai.torch.trainer import TorchTrainer - - -class Net(nn.Module): - - def __init__(self): - super(Net, self).__init__() - self.conv1 = nn.Conv2d(1, 10, kernel_size=5) - self.conv2 = nn.Conv2d(10, 20, kernel_size=5) - self.conv2_drop = nn.Dropout2d() - self.fc1 = nn.Linear(320, 50) - self.fc2 = nn.Linear(50, 10) - - def forward(self, x): - x = F.relu(F.max_pool2d(self.conv1(x), 2)) - x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2)) - x = x.view(-1, 320) - x = F.relu(self.fc1(x)) - x = F.dropout(x, training=self.training) - x = self.fc2(x) - return F.log_softmax(x, dim=0) - - -if __name__ == '__main__': - train_set = datasets.MNIST( - '.tmp/', train=True, download=True, - transform=transforms.Compose([ - transforms.ToTensor(), - transforms.Normalize((0.1307,), (0.3081,)) - ])) - val_set = datasets.MNIST( - '.tmp/', train=False, download=True, - transform=transforms.Compose([ - transforms.ToTensor(), - transforms.Normalize((0.1307,), (0.3081,)) - ])) - train_dataloder = DataLoader(train_set, batch_size=32, pin_memory=True) - validation_dataloader = DataLoader(val_set, batch_size=32, pin_memory=True) - trainer = TorchTrainer( - model=Net(), - loss=nn.NLLLoss(), - optimizer_class='torch.optim.SGD', - optimizer_kwargs=dict(lr=1e-3), - epochs=2, - strategy='ddp', - backend='nccl', - checkpoint_every=1 - ) - trainer.execute(args=[train_dataloder, validation_dataloader]) From d38385e0b2ef981dad8febc8acbb3125ca9aa75a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 09:09:11 +0100 Subject: [PATCH 25/59] Virgo HDF5 file format (#240) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * 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> --- .github/linters/.ruff.toml | 11 + .github/workflows/lint.yml | 4 +- pyproject.toml | 19 +- src/itwinai/torch/profiling/profiler.py | 36 +-- use-cases/eurac/config.yaml | 2 +- use-cases/eurac/runall.sh | 8 +- use-cases/eurac/slurm.sh | 2 +- use-cases/eurac/trainer.py | 4 +- use-cases/virgo/config.yaml | 19 +- use-cases/virgo/data.py | 256 +++++++++--------- use-cases/virgo/hpo.py | 1 - use-cases/virgo/runall.sh | 14 +- use-cases/virgo/slurm.sh | 5 +- use-cases/virgo/src/dataset.py | 4 +- use-cases/virgo/src/model.py | 3 +- use-cases/virgo/src/utils.py | 2 +- .../concat_hdf5_dataset_files.py | 93 +++++++ .../data_generation_hdf5.sh | 27 ++ .../virgo/synthetic-data-gen/file_gen_hdf5.py | 244 +++++++++++++++++ .../synthetic_data_gen/data_generation.sh | 26 -- .../virgo/synthetic_data_gen/file_gen.py | 134 --------- use-cases/virgo/trainer.py | 162 ++++++----- 22 files changed, 659 insertions(+), 417 deletions(-) create mode 100644 .github/linters/.ruff.toml create mode 100644 use-cases/virgo/synthetic-data-gen/concat_hdf5_dataset_files.py create mode 100644 use-cases/virgo/synthetic-data-gen/data_generation_hdf5.sh create mode 100644 use-cases/virgo/synthetic-data-gen/file_gen_hdf5.py delete mode 100644 use-cases/virgo/synthetic_data_gen/data_generation.sh delete mode 100644 use-cases/virgo/synthetic_data_gen/file_gen.py diff --git a/.github/linters/.ruff.toml b/.github/linters/.ruff.toml new file mode 100644 index 000000000..e0a978c8e --- /dev/null +++ b/.github/linters/.ruff.toml @@ -0,0 +1,11 @@ +line-length = 95 + +[lint] +select = ["E", "F", "I"] +ignore = ["E203"] + +[format] +quote-style = "double" +indent-style = "space" +skip-magic-trailing-comma = false +line-ending = "auto" diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml index 099fe44b3..e8d0816f5 100644 --- a/.github/workflows/lint.yml +++ b/.github/workflows/lint.yml @@ -35,10 +35,10 @@ jobs: DEFAULT_BRANCH: main GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} MARKDOWN_CONFIG_FILE: .markdownlint.json - PYTHON_FLAKE8_CONFIG_FILE: .flake8 JSCPD_CONFIG_FILE: .jscpd.json - PYTHON_ISORT_CONFIG_FILE: .isort.cfg + PYTHON_RUFF_CONFIG_FILE: .ruff.toml + VALIDATE_PYTHON: true VALIDATE_PYTHON_BLACK: false VALIDATE_PYTHON_MYPY: false VALIDATE_PYTHON_PYLINT: false diff --git a/pyproject.toml b/pyproject.toml index b0fe42dc1..020d78378 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -102,8 +102,21 @@ markers = [ "memory_heavy: high memory footprint. (deselect with '-m \"not heavy_memory\"')", ] -[tool.isort] -profile = "black" -known_first_party = ["itwinai"] +# [tool.isort] +# profile = "black" +# known_first_party = ["itwinai"] +# Ruff configuration: https://docs.astral.sh/ruff/configuration/ +[tool.ruff] +line-length = 95 +[tool.ruff.lint] +select = ["E", "F", "I", "W"] +ignore = ["E203"] +fixable = ["ALL"] + +[tool.ruff.format] +quote-style = "double" +indent-style = "space" +skip-magic-trailing-comma = false +line-ending = "auto" diff --git a/src/itwinai/torch/profiling/profiler.py b/src/itwinai/torch/profiling/profiler.py index 4d35d9b5f..249707fd4 100644 --- a/src/itwinai/torch/profiling/profiler.py +++ b/src/itwinai/torch/profiling/profiler.py @@ -35,12 +35,9 @@ def gather_profiling_data(key_averages: Iterable) -> pd.DataFrame: { "name": event.key, "node_id": event.node_id, - # "self_cpu_time_total": event.self_cpu_time_total, - # "cpu_time_total": event.cpu_time_total, - # "cpu_time_total_str": event.cpu_time_total_str, - "self_cuda_time_total": event.self_cuda_time_total, - "cuda_time_total": event.cuda_time_total, - "cuda_time_total_str": event.cuda_time_total_str, + "self_cuda_time_total": event.self_device_time_total, + "cuda_time_total": event.device_time_total, + "cuda_time_total_str": event.device_time_total_str, "calls": event.count, } ) @@ -91,32 +88,25 @@ def profiled_method(self: TorchTrainer, *args, **kwargs) -> Any: wait_epochs=self.profiling_wait_epochs, warmup_epochs=self.profiling_warmup_epochs, ) - - profiler = profile( - activities=[ProfilerActivity.CUDA], # , ProfilerActivity.CPU], - # with_modules=True, + with profile( + activities=[ProfilerActivity.CUDA], schedule=schedule( wait=wait_epochs, warmup=warmup_epochs, active=active_epochs, ), - ) - profiler.start() - - self.profiler = profiler - try: + ) as profiler: result = method(self, *args, **kwargs) - finally: - profiler.stop() - strategy = self.strategy - strategy_name = strategy.name + strategy = self.strategy + strategy_name = strategy.name + + global_rank = strategy.global_rank() + num_gpus_global = strategy.global_world_size() - global_rank = strategy.global_rank() - num_gpus_global = strategy.global_world_size() + # Extracting and storing the profiling data + key_averages = profiler.key_averages() - # Extracting and storing the profiling data - key_averages = profiler.key_averages() profiling_dataframe = gather_profiling_data(key_averages=key_averages) profiling_dataframe["strategy"] = strategy_name profiling_dataframe["num_gpus"] = num_gpus_global diff --git a/use-cases/eurac/config.yaml b/use-cases/eurac/config.yaml index 47b7101f1..8160f1d13 100644 --- a/use-cases/eurac/config.yaml +++ b/use-cases/eurac/config.yaml @@ -6,7 +6,7 @@ tmp_stats: /p/scratch/intertwin/datasets/eurac/stats experiment: "drought use case lstm" run_name: "alps_test" -epochs: 3 +epochs: 5 random_seed: 1010 lr: 0.001 batch_size: 256 diff --git a/use-cases/eurac/runall.sh b/use-cases/eurac/runall.sh index 03a4798da..e32cf28f7 100755 --- a/use-cases/eurac/runall.sh +++ b/use-cases/eurac/runall.sh @@ -18,13 +18,13 @@ if [ -z "$DEBUG" ]; then DEBUG=false fi if [ -z "$PYTHON_VENV" ]; then - PYTHON_VENV="../../envAI_hdfml" + PYTHON_VENV="../../.venv/" fi submit_job () { local mode=$1 sbatch --export=ALL,DIST_MODE="$mode",RUN_NAME="$mode",TIME="$TIME",DEBUG="$DEBUG",PYTHON_VENV=$PYTHON_VENV \ - --job-name="$mode" \ + --job-name="eurac-$mode" \ --output="logs_slurm/job-$mode-n$NUM_NODES.out" \ --error="logs_slurm/job-$mode-n$NUM_NODES.err" \ --nodes="$NUM_NODES" \ @@ -35,5 +35,5 @@ submit_job () { echo "Running distributed training on $NUM_NODES nodes with $NUM_GPUS GPUs per node" submit_job "ddp" -submit_job "deepspeed" -submit_job "horovod" +# submit_job "deepspeed" +# submit_job "horovod" diff --git a/use-cases/eurac/slurm.sh b/use-cases/eurac/slurm.sh index e907e54c0..a3b686595 100644 --- a/use-cases/eurac/slurm.sh +++ b/use-cases/eurac/slurm.sh @@ -10,7 +10,7 @@ #SBATCH --time=01:00:00 # Resources allocation -#SBATCH --partition=batch +#SBATCH --partition=develbooster #SBATCH --nodes=1 #SBATCH --gpus-per-node=4 #SBATCH --cpus-per-gpu=4 diff --git a/use-cases/eurac/trainer.py b/use-cases/eurac/trainer.py index 5d0fbfa7c..3ccf32afb 100644 --- a/use-cases/eurac/trainer.py +++ b/use-cases/eurac/trainer.py @@ -93,7 +93,7 @@ def __init__( self.save_parameters(**self.locals2params(locals())) @suppress_workers_print - # @profile_torch_trainer + @profile_torch_trainer # @measure_gpu_utilization def execute( self, @@ -149,7 +149,7 @@ def set_epoch(self, epoch: int): self.val_loader.sampler.set_epoch(epoch) @profile_torch_trainer - @measure_gpu_utilization + # @measure_gpu_utilization def train(self): """Override version of hython to support distributed strategy.""" # Tracking epoch times for scaling test diff --git a/use-cases/virgo/config.yaml b/use-cases/virgo/config.yaml index 7aa08e336..d1c1f7ece 100644 --- a/use-cases/virgo/config.yaml +++ b/use-cases/virgo/config.yaml @@ -1,7 +1,8 @@ -root_folder: /p/scratch/intertwin/datasets/virgo +hdf5_file_location: /p/scratch/intertwin/datasets/virgo_hdf5/virgo_data.hdf5 +hdf5_dataset_name: virgo_dataset data_root: ./data -epochs: 2 -batch_size: 3 +epochs: 5 +batch_size: 2000 # equivalent to chunk size learning_rate: 0.0001 strategy: ddp checkpoint_path: checkpoints/epoch_{}.pth @@ -16,12 +17,14 @@ training_pipeline: train_proportion: 0.9 validation_proportion: 0.1 rnd_seed: 42 - root_folder: ${root_folder} + hdf5_file_location: ${hdf5_file_location} + chunk_size: ${batch_size} + hdf5_dataset_name: ${hdf5_dataset_name} - class_path: trainer.NoiseGeneratorTrainer init_args: config: generator: simple #unet - batch_size: ${batch_size} + batch_size: 1 optim_lr: ${learning_rate} loss: l1 save_best: true @@ -31,6 +34,8 @@ training_pipeline: checkpoint_path: ${checkpoint_path} random_seed: 17 validation_every: 0 + profiling_wait_epochs: 0 + profiling_warmup_epochs: 0 logger: class_path: itwinai.loggers.LoggersCollection init_args: @@ -42,8 +47,8 @@ training_pipeline: init_args: experiment_name: Noise simulator (Virgo) log_freq: batch - - + + # To use a small dataset that is generated within the pipeline training_pipeline_small: class_path: itwinai.pipeline.Pipeline diff --git a/use-cases/virgo/data.py b/use-cases/virgo/data.py index 62b7b911b..8e850ef42 100644 --- a/use-cases/virgo/data.py +++ b/use-cases/virgo/data.py @@ -1,26 +1,35 @@ +# -------------------------------------------------------------------------------------- +# Part of the interTwin Project: https://www.intertwin.eu/ +# +# Created by: Matteo Bunino +# +# Credit: +# - Matteo Bunino - CERN +# - Anna Elisa Lappe - CERN +# - Jarl Sondre Sæther - CERN +# -------------------------------------------------------------------------------------- + import os +from pathlib import Path from typing import Optional, Tuple +import h5py import pandas as pd import torch from sklearn.model_selection import train_test_split +from torch.utils.data import Dataset, TensorDataset, random_split + +from itwinai.components import DataGetter, DataProcessor, DataSplitter, monitor_exec from src.dataset import ( generate_cut_image_dataset, generate_dataset_aux_channels, generate_dataset_main_channel, normalize_, ) -from torch.utils.data import Dataset, TensorDataset, random_split - -from itwinai.components import DataGetter, DataProcessor, DataSplitter, monitor_exec class TimeSeriesDatasetGenerator(DataGetter): - def __init__( - self, - data_root: str = "data", - name: Optional[str] = None - ) -> None: + def __init__(self, data_root: str = "data", name: Optional[str] = None) -> None: """Initialize the TimeSeriesDatasetGenerator class. Args: @@ -42,98 +51,97 @@ def execute(self) -> pd.DataFrame: pd.DataFrame: dataset of Q-plot images. """ df_aux_ts = generate_dataset_aux_channels( - 1000, 3, duration=16, sample_rate=500, - num_waves_range=(20, 25), noise_amplitude=0.6 + 1000, + 3, + duration=16, + sample_rate=500, + num_waves_range=(20, 25), + noise_amplitude=0.6, ) df_main_ts = generate_dataset_main_channel( df_aux_ts, weights=None, noise_amplitude=0.1 ) # save datasets - save_name_main = 'TimeSeries_dataset_synthetic_main.pkl' - save_name_aux = 'TimeSeries_dataset_synthetic_aux.pkl' + save_name_main = "TimeSeries_dataset_synthetic_main.pkl" + save_name_aux = "TimeSeries_dataset_synthetic_aux.pkl" df_main_ts.to_pickle(os.path.join(self.data_root, save_name_main)) df_aux_ts.to_pickle(os.path.join(self.data_root, save_name_aux)) # Transform to images and save to disk df_ts = pd.concat([df_main_ts, df_aux_ts], axis=1) df = generate_cut_image_dataset( - df_ts, list(df_ts.columns), - num_processes=20, square_size=64 + df_ts, list(df_ts.columns), num_processes=20, square_size=64 ) - save_name = 'Image_dataset_synthetic_64x64.pkl' + save_name = "Image_dataset_synthetic_64x64.pkl" df.to_pickle(os.path.join(self.data_root, save_name)) return df -class SyntheticTimeSeriesDataset(Dataset): - def __init__(self, root_folder: Optional[str] = None,): +class SyntheticTimeSeriesDatasetHDF5(Dataset): + def __init__( + self, + hdf5_file_location: str, + chunk_size: int = 500, + hdf5_dataset_name: str = "virgo_dataset", + ): """Initialize the DataFrameDataset class. Args: - root_folder (str): Location of the pickled DataFrames. + hdf5_file_location: Location of the HDF5 file containing the dataset + chunk_size: How many rows of data points each sample should contain + hdf5_dataset_name: The name of the Dataset object of the HDF5 file """ - - # Ensure the root folder exists - if not os.path.isdir(root_folder): - raise FileNotFoundError(f"Root folder '{root_folder}' not found.") - - # Find all file paths in root folder - self.file_paths = [os.path.join(dirpath, f) - for dirpath, dirs, files in os.walk(root_folder) - for f in files if f.endswith('.pkl')] + file_path = Path(hdf5_file_location) + if not file_path.exists(): + raise ValueError(f"Given file location, {file_path.resolve()} does not exist. ") + self.hdf5_dataset_name = hdf5_dataset_name + self.file_path = file_path + self.chunk_size = chunk_size + with h5py.File(self.file_path, "r") as f: + if self.hdf5_dataset_name not in f: + raise ValueError( + f"The dataset {self.hdf5_dataset_name} does not exist in " + f"the given HDF5 file." + ) + dataset = f[self.hdf5_dataset_name] + self.num_datapoints = dataset.shape[0] + + if self.num_datapoints == 0: + raise ValueError("The given file contains 0 data points!") + + if self.num_datapoints % self.chunk_size != 0: + print( + f"[WARNING]: Number of datapoints, {self.num_datapoints} is not " + f"divisible by the given chunk size, {self.chunk_size}, so the " + f"remainder will be truncated. " + ) + self.length = self.num_datapoints // self.chunk_size + print(f"self.length: {self.length}") def __len__(self): """Return the total number of files in the dataset.""" - return len(self.file_paths) + return self.length - def __getitem__(self, idx): - """ Retrieve a data sample by index, convert to tensor, and normalize. + def __getitem__(self, idx) -> torch.Tensor: + """Retrieve a data sample by index and normalize. Args: idx (int): Index of the file to retrieve. Returns: - torch.Tensor: Concatenated and normalized data tensor - of main and auxiliary channels. + torch.Tensor: Normalized tensor for specific idx """ - # Load a single dataframe from the file - dataframe = pd.read_pickle(self.file_paths[idx]) - - # Convert all data in the DataFrame to torch tensors - df = dataframe.map(lambda x: torch.tensor(x)) - - # Divide Image dataset in main and aux channels. - main_channel = list(df.columns)[0] - aux_channels = list(df.columns)[1:] + if idx >= len(self): + raise ValueError(f"Index {idx} out of bounds for dataset with length {len(self)}!") - # Ensure that there are at least 3 auxiliary channels - if len(aux_channels) < 3: - print(f"Item with the index {idx} only has {len(aux_channels)} channels!") - return None + offset = idx * self.chunk_size + with h5py.File(self.file_path, "r") as f: + dataset = f[self.hdf5_dataset_name] + data = dataset[offset : offset + self.chunk_size] - # Extract the main channel and auxiliary channels - df_aux_all_2d = pd.DataFrame(df[aux_channels]) - df_main_all_2d = pd.DataFrame(df[main_channel]) - - # Stack the main and auxiliary channels into 2D tensors - signal_data_train_2d = torch.stack( - [torch.stack( - [df_main_all_2d[main_channel].iloc[i]]) for i in range(df_main_all_2d.shape[0])]) - - aux_data_train_2d = torch.stack( - [torch.stack( - [df_aux_all_2d.iloc[i, 0], - df_aux_all_2d.iloc[i, 1], - df_aux_all_2d.iloc[i, 2]] - ) for i in range(df_aux_all_2d.shape[0])] - ) - - # Concatenate the main and auxiliary channel tensors - data_tensor = torch.cat([signal_data_train_2d, aux_data_train_2d], dim=1) - - # Normalize and return the concatenated tensor - return normalize_(data_tensor) + data = torch.tensor(data, dtype=torch.float32) + return normalize_(data) class TimeSeriesDatasetSplitter(DataSplitter): @@ -142,9 +150,11 @@ def __init__( train_proportion: int | float, validation_proportion: int | float = 0.0, test_proportion: int | float = 0.0, - root_folder: Optional[str] = None, rnd_seed: Optional[int] = None, - name: Optional[str] = None + name: Optional[str] = None, + hdf5_file_location: str = "data/virgo_data.hdf5", + hdf5_dataset_name: str = "virgo_dataset", + chunk_size: int = 500, ) -> None: """Initialize the splitter for time-series datasets. @@ -156,15 +166,12 @@ def __init__( root_folder (str | None): Folder containing the dataset files. name (str | None): Name of the data splitter. """ - super().__init__( - train_proportion, - validation_proportion, - test_proportion, - name - ) + super().__init__(train_proportion, validation_proportion, test_proportion, name) self.save_parameters(**self.locals2params(locals())) self.rnd_seed = rnd_seed - self.root_folder = root_folder + self.hdf5_file_location = hdf5_file_location + self.hdf5_dataset_name = hdf5_dataset_name + self.chunk_size = chunk_size @monitor_exec def execute(self) -> Tuple[Dataset, Dataset, Dataset]: @@ -177,16 +184,18 @@ def execute(self) -> Tuple[Dataset, Dataset, Dataset]: Tuple[Dataset, Dataset, Dataset]: Training, validation, and test datasets. """ - whole_dataset = SyntheticTimeSeriesDataset(root_folder=self.root_folder) + whole_dataset = SyntheticTimeSeriesDatasetHDF5( + hdf5_file_location=self.hdf5_file_location, + chunk_size=self.chunk_size, + hdf5_dataset_name=self.hdf5_dataset_name, + ) # Split file paths into train, validation, and test sets generator = torch.Generator().manual_seed(self.rnd_seed) [train_dataset, validation_dataset, test_dataset] = random_split( whole_dataset, - [self.train_proportion, - self.validation_proportion, - self.test_proportion], - generator=generator + [self.train_proportion, self.validation_proportion, self.test_proportion], + generator=generator, ) print(f"Shape of item: {train_dataset.__getitem__(idx=5).shape}") return train_dataset, validation_dataset, test_dataset @@ -200,9 +209,9 @@ def __init__( test_proportion: int | float = 0.0, rnd_seed: Optional[int] = None, images_dataset: str = "data/Image_dataset_synthetic_64x64.pkl", - name: Optional[str] = None + name: Optional[str] = None, ) -> None: - """Class for splitting of smaller datasets. Use this class in the pipeline if the + """Class for splitting of smaller datasets. Use this class in the pipeline if the entire dataset can fit into memory. Args: @@ -210,16 +219,13 @@ def __init__( validation_proportion (int | float, optional): _description_. Defaults to 0.0. test_proportion (int | float, optional): _description_. Defaults to 0.0. rnd_seed (Optional[int], optional): _description_. Defaults to None. - images_dataset (str, optional): _description_. + images_dataset (str, optional): _description_. Defaults to "data/Image_dataset_synthetic_64x64.pkl". name (Optional[str], optional): _description_. Defaults to None. """ - super().__init__( - train_proportion, validation_proportion, - test_proportion, name - ) + super().__init__(train_proportion, validation_proportion, test_proportion, name) self.save_parameters(**self.locals2params(locals())) - self.validation_proportion = 1-train_proportion + self.validation_proportion = 1 - train_proportion self.rnd_seed = rnd_seed self.images_dataset = images_dataset @@ -231,10 +237,7 @@ def get_or_load(self, dataset: Optional[pd.DataFrame] = None): return dataset @monitor_exec - def execute( - self, - dataset: Optional[pd.DataFrame] = None - ) -> Tuple: + def execute(self, dataset: Optional[pd.DataFrame] = None) -> Tuple: """Splits a dataset into train, validation and test splits. Args: @@ -257,8 +260,11 @@ def execute( df_aux_all_2d = pd.DataFrame(df[aux_channels]) df_main_all_2d = pd.DataFrame(df[main_channel]) X_train_2d, X_test_2d, y_train_2d, y_test_2d = train_test_split( - df_aux_all_2d, df_main_all_2d, - test_size=self.validation_proportion, random_state=self.rnd_seed) + df_aux_all_2d, + df_main_all_2d, + test_size=self.validation_proportion, + random_state=self.rnd_seed, + ) return (X_train_2d, y_train_2d), (X_test_2d, y_test_2d) @@ -274,9 +280,7 @@ def __init__(self, name: str | None = None) -> None: @monitor_exec def execute( - self, - train_dataset: Tuple, - validation_dataset: Tuple + self, train_dataset: Tuple, validation_dataset: Tuple ) -> Tuple[torch.Tensor, torch.Tensor, None]: """Pre-process datasets: rearrange and normalize before training. @@ -309,20 +313,27 @@ def execute( # ]) # for i in range(X_train.shape[0]) # whole dataset - signal_data_train_2d = torch.stack([ - torch.stack([y_train_2d[main_channel].iloc[i]]) - for i in range(y_train_2d.shape[0]) - ]) - aux_data_train_2d = torch.stack([ - torch.stack( - [X_train_2d.iloc[i][0], X_train_2d.iloc[i][1], - X_train_2d.iloc[i][2]]) - for i in range(X_train_2d.shape[0]) - ]) + signal_data_train_2d = torch.stack( + [ + torch.stack([y_train_2d[main_channel].iloc[i]]) + for i in range(y_train_2d.shape[0]) + ] + ) + aux_data_train_2d = torch.stack( + [ + torch.stack( + [ + X_train_2d.iloc[i][0], + X_train_2d.iloc[i][1], + X_train_2d.iloc[i][2], + ] + ) + for i in range(X_train_2d.shape[0]) + ] + ) # concatenate torch.tensors - train_data_2d = torch.cat( - [signal_data_train_2d, aux_data_train_2d], dim=1) + train_data_2d = torch.cat([signal_data_train_2d, aux_data_train_2d], dim=1) # train_data_small_2d = torch.cat( # [signal_data_train_small_2d, aux_data_train_small_2d], dim=1) @@ -342,20 +353,17 @@ def execute( # ]) # for i in range(X_test.shape[0]) # whole dataset - signal_data_test_2d = torch.stack([ - torch.stack( - [y_test_2d[main_channel].iloc[i]]) - for i in range(y_test_2d.shape[0]) - ]) - aux_data_test_2d = torch.stack([ - torch.stack( - [X_test_2d.iloc[i, 0], X_test_2d.iloc[i, 1], - X_test_2d.iloc[i, 2]]) - for i in range(X_test_2d.shape[0]) - ]) - - test_data_2d = torch.cat( - [signal_data_test_2d, aux_data_test_2d], dim=1) + signal_data_test_2d = torch.stack( + [torch.stack([y_test_2d[main_channel].iloc[i]]) for i in range(y_test_2d.shape[0])] + ) + aux_data_test_2d = torch.stack( + [ + torch.stack([X_test_2d.iloc[i, 0], X_test_2d.iloc[i, 1], X_test_2d.iloc[i, 2]]) + for i in range(X_test_2d.shape[0]) + ] + ) + + test_data_2d = torch.cat([signal_data_test_2d, aux_data_test_2d], dim=1) # test_data_small_2d = torch.cat( # [signal_data_test_small_2d, aux_data_test_small_2d], dim=1) diff --git a/use-cases/virgo/hpo.py b/use-cases/virgo/hpo.py index db3c2b360..cbd46de14 100644 --- a/use-cases/virgo/hpo.py +++ b/use-cases/virgo/hpo.py @@ -1,6 +1,5 @@ import argparse import os -from pathlib import Path from typing import Dict import matplotlib.pyplot as plt diff --git a/use-cases/virgo/runall.sh b/use-cases/virgo/runall.sh index 781b5bbae..c24a6462f 100755 --- a/use-cases/virgo/runall.sh +++ b/use-cases/virgo/runall.sh @@ -9,14 +9,14 @@ else N=$1 fi if [ -z "$2" ] ; then - T="00:30:00" + T="00:20:00" else T=$2 fi # Python virtual environment (no conda/micromamba) -CMD="--nodes=$N --time=$T --account=intertwin --partition=batch slurm.sh" -PYTHON_VENV="../../envAI_hdfml" +CMD="--nodes=$N --time=$T --account=intertwin --partition=develbooster slurm.sh" +PYTHON_VENV="../../.venv/" echo "Distributing training over $N nodes. Timeout set to: $T" # Clear SLURM logs (*.out and *.err files) @@ -32,7 +32,7 @@ DIST_MODE="ddp" RUN_NAME="ddp-itwinai" TRAINING_CMD="$PYTHON_VENV/bin/itwinai exec-pipeline --config config.yaml --pipe-key training_pipeline -o strategy=ddp -o checkpoint_path=checkpoints_ddp/epoch_{}.pth" sbatch --export=ALL,DIST_MODE="$DIST_MODE",RUN_NAME="$RUN_NAME",TRAINING_CMD="$TRAINING_CMD",PYTHON_VENV="$PYTHON_VENV" \ - --job-name="$RUN_NAME-n$N" \ + --job-name="virgo-$RUN_NAME-n$N" \ --output="logs_slurm/job-$RUN_NAME-n$N.out" \ --error="logs_slurm/job-$RUN_NAME-n$N.err" \ $CMD @@ -42,7 +42,7 @@ DIST_MODE="deepspeed" RUN_NAME="deepspeed-itwinai" TRAINING_CMD="$PYTHON_VENV/bin/itwinai exec-pipeline --config config.yaml --pipe-key training_pipeline -o strategy=deepspeed -o checkpoint_path=checkpoints_deepspeed/epoch_{}.pth" sbatch --export=ALL,DIST_MODE="$DIST_MODE",RUN_NAME="$RUN_NAME",TRAINING_CMD="$TRAINING_CMD",PYTHON_VENV="$PYTHON_VENV" \ - --job-name="$RUN_NAME-n$N" \ + --job-name="virgo-$RUN_NAME-n$N" \ --output="logs_slurm/job-$RUN_NAME-n$N.out" \ --error="logs_slurm/job-$RUN_NAME-n$N.err" \ $CMD @@ -52,7 +52,7 @@ DIST_MODE="horovod" RUN_NAME="horovod-itwinai" TRAINING_CMD="$PYTHON_VENV/bin/itwinai exec-pipeline --config config.yaml --pipe-key training_pipeline -o strategy=horovod -o checkpoint_path=checkpoints_horovod/epoch_{}.pth" sbatch --export=ALL,DIST_MODE="$DIST_MODE",RUN_NAME="$RUN_NAME",TRAINING_CMD="$TRAINING_CMD",PYTHON_VENV="$PYTHON_VENV" \ - --job-name="$RUN_NAME-n$N" \ + --job-name="virgo-$RUN_NAME-n$N" \ --output="logs_slurm/job-$RUN_NAME-n$N.out" \ --error="logs_slurm/job-$RUN_NAME-n$N.err" \ - $CMD \ No newline at end of file + $CMD diff --git a/use-cases/virgo/slurm.sh b/use-cases/virgo/slurm.sh index 51397327b..d72a156b9 100644 --- a/use-cases/virgo/slurm.sh +++ b/use-cases/virgo/slurm.sh @@ -5,14 +5,12 @@ # Job configuration #SBATCH --job-name=distributed_training #SBATCH --account=intertwin -#SBATCH --mail-user= -#SBATCH --mail-type=ALL #SBATCH --output=job.out #SBATCH --error=job.err #SBATCH --time=00:30:00 # Resources allocation -#SBATCH --partition=batch +#SBATCH --partition=develbooster #SBATCH --nodes=2 #SBATCH --gpus-per-node=4 #SBATCH --cpus-per-gpu=4 @@ -113,6 +111,7 @@ elif [ "$DIST_MODE" == "deepspeed" ] ; then elif [ "$DIST_MODE" == "horovod" ] ; then echo "HOROVOD training: $TRAINING_CMD" srun --cpu-bind=none --ntasks-per-node=$SLURM_GPUS_PER_NODE --cpus-per-task=$SLURM_CPUS_PER_GPU \ + --ntasks=$(($SLURM_GPUS_PER_NODE * $SLURM_NNODES)) \ $TRAINING_CMD else >&2 echo "ERROR: unrecognized \$DIST_MODE env variable" diff --git a/use-cases/virgo/src/dataset.py b/use-cases/virgo/src/dataset.py index 6e50979de..7d0054552 100644 --- a/use-cases/virgo/src/dataset.py +++ b/use-cases/virgo/src/dataset.py @@ -267,13 +267,13 @@ def generate_cut_image_dataset(df, channels, num_processes=20, square_size=128): DataFrame: Pandas DataFrame containing the q_transform np.array data. """ + # NOTE: When len(df) == 1, this slows down the code considerably... args = [(df.iloc[row], row, channels, square_size) for row in range(df.shape[0])] with multiprocessing.Pool(processes=num_processes) as pool: # Use map to pass multiple arguments to process_image results = list(pool.starmap(process_image, args)) - df = pd.concat(results, ignore_index=True) - return df + return pd.concat(results, ignore_index=True) def show_dataset(df, size, num_plots=10): diff --git a/use-cases/virgo/src/model.py b/use-cases/virgo/src/model.py index cda17bb43..64dbb233a 100644 --- a/use-cases/virgo/src/model.py +++ b/use-cases/virgo/src/model.py @@ -12,9 +12,8 @@ generator to use in training and inference """ -import torch.nn as nn import torch - +import torch.nn as nn # SHALLOW DECODER diff --git a/use-cases/virgo/src/utils.py b/use-cases/virgo/src/utils.py index 8980b843a..dff6fc27a 100644 --- a/use-cases/virgo/src/utils.py +++ b/use-cases/virgo/src/utils.py @@ -1,6 +1,6 @@ -import torch import numpy as np +import torch from gwpy.timeseries import TimeSeries diff --git a/use-cases/virgo/synthetic-data-gen/concat_hdf5_dataset_files.py b/use-cases/virgo/synthetic-data-gen/concat_hdf5_dataset_files.py new file mode 100644 index 000000000..155f92332 --- /dev/null +++ b/use-cases/virgo/synthetic-data-gen/concat_hdf5_dataset_files.py @@ -0,0 +1,93 @@ +# -------------------------------------------------------------------------------------- +# Part of the interTwin Project: https://www.intertwin.eu/ +# +# Created by: Jarl Sondre Sæther +# +# Credit: +# - Jarl Sondre Sæther - CERN +# -------------------------------------------------------------------------------------- + +import argparse +from pathlib import Path + +import h5py +import numpy as np + + +def append_to_hdf5_dataset( + file_path: Path, + dataset_name: str, + array: np.ndarray, + expected_datapoint_shape: tuple, +): + if tuple(array.shape[1:]) != expected_datapoint_shape: + actual_shape_str = ", ".join(str(s) for s in array.shape) + expected_shape_str = ", ".join(str(s) for s in expected_datapoint_shape) + raise ValueError( + f"'array' has an incorrect shape: ({actual_shape_str}). " + f"Should have been (x, {expected_shape_str})." + ) + + # print(f"Appending to file: '{str(file_path.resolve())}'.") + with h5py.File(file_path, "a") as f: + dset = f[dataset_name] + dset.resize(dset.shape[0] + array.shape[0], axis=0) + dset[-array.shape[0] :] = array + + +def main(): + parser = argparse.ArgumentParser(description="Virgo Dataset Generation") + parser.add_argument( + "--dir", type=str, help="Directory containing the HDF5 files to concatenate" + ) + parser.add_argument( + "--save-location", + type=str, + help="Location to save the resulting HDF5 file.", + default="total_virgo_data.hdf5", + ) + args = parser.parse_args() + dir = Path(args.dir) + save_location = Path(args.save_location) + num_aux_channels = 3 + square_size = 64 + dataset_name = "virgo_dataset" + + # Creating empty HDF5 file + datapoint_shape = (num_aux_channels + 1, square_size, square_size) + save_location.parent.mkdir(parents=True, exist_ok=True) + + print(f"Creating/overwriting file: '{save_location.resolve()}'.") + with h5py.File(save_location, "w") as f: + dataset = f.create_dataset( + dataset_name, + shape=(0, *datapoint_shape), + maxshape=(None, *datapoint_shape), + dtype=np.float32, + ) + dataset.attrs["Description"] = ( + "Synthetic time series data for the Virgo use case" + ) + dataset.attrs["main_channel_idx"] = 0 + + # NOTE: This will not necessarily iterate in same order as the suffices of the + # file names + files = [ + entry for entry in dir.iterdir() + if (entry.suffix == ".hdf5" and entry.stem != "virgo_data") + ] + for entry in files: + with h5py.File(entry, "r") as f: + data = f[dataset_name][:] + print(f"Adding {len(data)} rows from entry: {entry}") + + append_to_hdf5_dataset( + file_path=save_location, + dataset_name=dataset_name, + array=data, + expected_datapoint_shape=datapoint_shape, + ) + + +if __name__ == "__main__": + main() diff --git a/use-cases/virgo/synthetic-data-gen/data_generation_hdf5.sh b/use-cases/virgo/synthetic-data-gen/data_generation_hdf5.sh new file mode 100644 index 000000000..09da37341 --- /dev/null +++ b/use-cases/virgo/synthetic-data-gen/data_generation_hdf5.sh @@ -0,0 +1,27 @@ +#!/bin/bash + +#SBATCH --account=intertwin +#SBATCH --output=array-job/job_%a.out +#SBATCH --error=array-job/job_%a.err +#SBATCH --time=00:07:00 +#SBATCH --mem-per-cpu=1G +#SBATCH --partition=develbooster +#SBATCH --array=1-75 +#SBATCH --job-name=generate_virgo_data +#SBATCH --cpus-per-task=26 + +# Load required modules +ml Stages/2024 GCC OpenMPI CUDA/12 MPI-settings/CUDA Python HDF5 PnetCDF libaio mpi4py + +# Activate Python virtual environment +source ../../envAI_juwels/bin/activate + +# Folder in which the datasets will be stored +target_file="/p/scratch/intertwin/datasets/virgo_hdf5/virgo_data_${SLURM_ARRAY_TASK_ID}.hdf5" + +python synthetic-data-gen/file_gen_hdf5.py \ + --num-datapoints 10000 \ + --num-processes 25 \ + --save-frequency 1000 \ + --save-location "$target_file" + diff --git a/use-cases/virgo/synthetic-data-gen/file_gen_hdf5.py b/use-cases/virgo/synthetic-data-gen/file_gen_hdf5.py new file mode 100644 index 000000000..ad49fc677 --- /dev/null +++ b/use-cases/virgo/synthetic-data-gen/file_gen_hdf5.py @@ -0,0 +1,244 @@ +# -------------------------------------------------------------------------------------- +# Part of the interTwin Project: https://www.intertwin.eu/ +# +# Created by: Jarl Sondre Sæther +# +# Credit: +# - Jarl Sondre Sæther - CERN +# - Unknown +# -------------------------------------------------------------------------------------- + +import argparse +import sys +from pathlib import Path +from time import time + +import h5py +import numpy as np +import pandas as pd +from gwpy.timeseries import TimeSeries +from tqdm import tqdm + + +def append_to_hdf5_dataset( + file_path: Path, + dataset_name: str, + array: np.ndarray, + expected_datapoint_shape: tuple, +): + if tuple(array.shape[1:]) != expected_datapoint_shape: + actual_shape_str = ", ".join(str(s) for s in array.shape) + expected_shape_str = ", ".join(str(s) for s in expected_datapoint_shape) + raise ValueError( + f"'array' has an incorrect shape: ({actual_shape_str}). " + f"Should have been (x, {expected_shape_str})." + ) + + print(f"Appending to file: '{str(file_path.resolve())}'.") + with h5py.File(file_path, "a") as f: + dset=f[dataset_name] + dset.resize(dset.shape[0] + array.shape[0], axis=0) + dset[-array.shape[0] :] = array + + +def generate_hdf5_dataset( + output_file: str = "virgo_data.hdf5", + dataset_name: str = "virgo_dataset", + num_datapoints=5, + duration=10, + sample_rate=500, + num_aux_channels=10, + num_waves_range=(10, 15), + noise_amplitude=0.1, + num_processes=4, + square_size=64, + datapoints_per_file=10, + seed=None, +) -> None: + """Generate a folder with num_files pickle files containing synthetic gravitational + waves data. + + Args: + folder_name (string): the path and name where the files will be stored + num_files (int): Number of files which will be created. + duration (float): Duration of the time series data in seconds (default is 6 + seconds). + num_aux_channels (int): Number of auxiliary channels, containing the data from + the auxiliary sensors in the detector which do not go into the strain. + sample_rate (int): Sampling rate of the time series data in samples per second + (default is 500 samples per second). + num_waves_range (tuple): Range for the random number of sine waves to be + generated for each time series. Format: (min_num_waves, max_num_waves) + (default is (10, 15)). + noise_amplitude (float): Amplitude of the smooth random noise added to the + time series data (default is 0.1). + num_processes (int): Number of cores for multiprocess (default 20) + square_size (int): Size in pixels of qplot image (default is 500 samples per + second). + datapoints_per_file (int): number of independent datapoints per pickle file. + """ + sys.path.append(str(Path.cwd().resolve())) + from src.dataset import generate_cut_image_dataset + + if seed is None: + # Since we can't retrieve the seed from numpy, we set it so that we can + # store it in the dataset. More information: + # https://stackoverflow.com/questions/32172054/how-can-i-retrieve-the-current-seed-of-numpys-random-number-generator + seed = np.random.randint(0, 2**32, dtype=np.uint64) + np.random.seed(seed) + + datapoints = [] + + # Creating empty HDF5 file + datapoint_shape = (num_aux_channels + 1, square_size, square_size) + output_file_path = Path(output_file) + output_file_path.parent.mkdir(parents=True, exist_ok=True) + print(f"Creating/overwriting file: '{output_file_path.resolve()}'.") + with h5py.File(output_file_path, "w") as f: + dataset = f.create_dataset( + dataset_name, + shape=(0, *datapoint_shape), + maxshape=(None, *datapoint_shape), + dtype=np.float32, + ) + dataset.attrs["Description"] = ( + "Synthetic time series data for the Virgo use case" + ) + dataset.attrs["main_channel_idx"] = 0 + dataset.attrs["seed"] = str(seed) + + for f in tqdm(range(num_datapoints)): + times = np.linspace(0, duration, duration * sample_rate) + # Initialise the main data as a list of zeros + main_data = np.zeros(len(times)) + dictionary_aux = {} + for i in range(num_aux_channels): + channel_name = "Aux_" + str(i) + + # Initialize an array to store the generated wave data for this row + wave_data = np.zeros(len(times)) + # Determine the number of sine waves to generate for this column randomly + num_waves = np.random.randint(*num_waves_range) + + # Generate each sine wave + for _ in range(num_waves): + # Randomly generate parameters for the sine wave (amplitude, frequency, phase) + amplitude = np.random.uniform(0.5, 2.0) + frequency = np.random.uniform(0.5, 5.0) + phase = np.random.uniform(0, 2 * np.pi) + + # Generate the sine wave and add it to the wave_data + wave_data += amplitude * np.sin(2 * np.pi * frequency * times + phase) + + # Add smooth random noise to the wave data + smooth_noise = np.random.normal(0, noise_amplitude, len(times)) + wave_data += smooth_noise + + coeff = np.random.rand() + + main_data += coeff * wave_data + + # Create a TimeSeries object from the wave data + ts = TimeSeries(wave_data, t0=0, dt=1 / sample_rate) + + dictionary_aux[channel_name] = [ts] + + # Creating the main timeseries + main_data += np.random.normal(0, noise_amplitude) + ts_main = TimeSeries(main_data, dt=1 / sample_rate) + + main_entry = {"Main": [ts_main]} + + dictionary = {**main_entry, **dictionary_aux} + + # turn dictionary into dataframe + df_ts = pd.DataFrame(dictionary) + + datapoints.append(df_ts) + if len(datapoints) % datapoints_per_file == 0: + # Converting to numpy array + df_concat = pd.concat(datapoints) + df_concat = generate_cut_image_dataset( + df=df_concat, + channels=list(df_ts.columns), + num_processes=num_processes, + square_size=square_size, + ) + value_array = df_concat.to_numpy() + value_array = np.stack( + [np.stack(row) for row in value_array], dtype=np.float32 + ) + + append_to_hdf5_dataset( + file_path=output_file_path, + dataset_name=dataset_name, + array=value_array, + expected_datapoint_shape=datapoint_shape, + ) + datapoints = [] + + # Adding any remaining datapoints + if len(datapoints) > 0: + df_concat = pd.concat(datapoints) + df_concat = generate_cut_image_dataset( + df=df_concat, + channels=list(df_concat.columns), + num_processes=num_processes, + square_size=square_size, + ) + value_array = df_concat.to_numpy() + value_array = np.stack([np.stack(row) for row in value_array], dtype=np.float32) + append_to_hdf5_dataset( + file_path=output_file_path, + dataset_name=dataset_name, + array=value_array, + expected_datapoint_shape=datapoint_shape, + ) + datapoints = [] + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser(description="Virgo Dataset Generation") + parser.add_argument( + "--num-datapoints", type=int, help="Number of datapoints to be created." + ) + parser.add_argument( + "--save-frequency", + type=int, + help="How often to save to file while generating. Also saves when finished. ", + default=100, + ) + parser.add_argument( + "--num-processes", + type=int, + help="How many processes to use when generating data", + default=1, + ) + parser.add_argument( + "--save-location", + type=str, + help="Location to save the resulting HDF5 file.", + default="virgo_data.hdf5", + ) + + parser.add_argument("--seed", type=int, help="Seed for random number generator") + + args = parser.parse_args() + + start = time() + generate_hdf5_dataset( + output_file=args.save_location, + num_datapoints=args.num_datapoints, + duration=16, + sample_rate=500, + num_aux_channels=3, + num_waves_range=(10, 15), + noise_amplitude=0.5, + datapoints_per_file=args.save_frequency, + num_processes=args.num_processes, + seed=args.seed, + ) + end = time() + total_time = end - start + print(f"Generation took {total_time:.2f} seconds!") diff --git a/use-cases/virgo/synthetic_data_gen/data_generation.sh b/use-cases/virgo/synthetic_data_gen/data_generation.sh deleted file mode 100644 index 0a7c95e13..000000000 --- a/use-cases/virgo/synthetic_data_gen/data_generation.sh +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash - -#SBATCH --account=intertwin -#SBATCH --output=array_job.out -#SBATCH --error=array_job.err -#SBATCH --time=01:30:00 -#SBATCH --mem-per-cpu=1G -#SBATCH --partition=batch -#SBATCH --array=1-250 -#SBATCH --job-name=generate_virgo_data - -# Load required modules -ml Stages/2024 GCC OpenMPI CUDA/12 MPI-settings/CUDA Python HDF5 PnetCDF libaio mpi4py - -# Activate Python virtual environment -source ../../../envAI_hdfml/bin/activate - -# Folder in which the datasets will be stored -target_folder="/p/scratch/intertwin/datasets/virgo/folder_${SLURM_ARRAY_TASK_ID}" -mkdir -p "$target_folder" - -# Set the number of files to generate. If NUM_FILES is not set, use 100 as the default value. -NUM_FILES=${NUM_FILES:-100} - -# Run the Python script with appropriate arguments -srun python file_gen.py --target_folder_name "$target_folder" --file_number "$NUM_FILES" diff --git a/use-cases/virgo/synthetic_data_gen/file_gen.py b/use-cases/virgo/synthetic_data_gen/file_gen.py deleted file mode 100644 index f9cf5f4b2..000000000 --- a/use-cases/virgo/synthetic_data_gen/file_gen.py +++ /dev/null @@ -1,134 +0,0 @@ -import argparse -from pathlib import Path - -import numpy as np -import pandas as pd -from gwpy.timeseries import TimeSeries - -from ..src.dataset import generate_cut_image_dataset - - -def generate_pkl_dataset( - folder_name='test_folder', - num_files=5, - duration=10, - sample_rate=500, - num_aux_channels=10, - num_waves_range=(10, 15), - noise_amplitude=0.1, - num_processes=4, - square_size=64, - datapoints_per_file=10 -) -> None: - """Generate a folder with num_files pickle files containing synthetic gravitational waves data. - - Args: - folder_name (string): the path and name where the files will be stored - num_files (int): Number of files which will be created. - duration (float): Duration of the time series data in seconds (default is 6 seconds). - num_aux_channels (int): Number of auxiliary channels, containing the data from the auxiliary sensors in the detector which do not go into the strain. - sample_rate (int): Sampling rate of the time series data in samples per second (default is 500 samples per second). - num_waves_range (tuple): Range for the random number of sine waves to be generated for each time series. - Format: (min_num_waves, max_num_waves) (default is (10, 15)). - noise_amplitude (float): Amplitude of the smooth random noise added to the time series data (default is 0.1). - num_processes (int): Number of cores for multiprocess (default 20) - square_size (int): Size in pixels of qplot image (default is 500 samples per second). - datapoints_per_file (int): number of independent datapoints per pickle file. - """ - - datapoints = [] - # Generate time array - Path(folder_name).mkdir(parents=True, exist_ok=True) - for f in range(num_files): - - filename = 'file-'+str(f)+'.pkl' - filepath = folder_name+'/'+filename - - times = np.linspace(0, duration, duration * sample_rate) - - # Initialise the main data as a list of zeros - main_data = np.zeros(len(times)) - dictionary_aux = {} - for i in range(num_aux_channels): - channel_name = "Aux_"+str(i) - - # Initialize an array to store the generated wave data for this row - wave_data = np.zeros(len(times)) - # Determine the number of sine waves to generate for this column randomly - num_waves = np.random.randint(*num_waves_range) - - # Generate each sine wave - for _ in range(num_waves): - # Randomly generate parameters for the sine wave (amplitude, frequency, phase) - amplitude = np.random.uniform(0.5, 2.0) - frequency = np.random.uniform(0.5, 5.0) - phase = np.random.uniform(0, 2*np.pi) - - # Generate the sine wave and add it to the wave_data - wave_data += amplitude * np.sin(2 * np.pi * frequency * times + phase) - - # Add smooth random noise to the wave data - smooth_noise = np.random.normal(0, noise_amplitude, len(times)) - wave_data += smooth_noise - - coeff = np.random.rand() - - main_data += coeff*wave_data - - # Create a TimeSeries object from the wave data - ts = TimeSeries(wave_data, t0=0, dt=1/sample_rate) - - dictionary_aux[channel_name] = [ts] - - # Creating the main timeseries - main_data += np.random.normal(0, noise_amplitude) - ts_main = TimeSeries(main_data, dt=1/sample_rate) - - main_entry = {'Main': [ts_main]} - - dictionary = {**main_entry, **dictionary_aux} - - # turn dictionary into dataframe - df_ts = pd.DataFrame(dictionary) - - # Convert timeseries dataset into q-plot - df = generate_cut_image_dataset(df_ts, list( - df_ts.columns), num_processes=num_processes, square_size=square_size) - - datapoints.append(df) - if len(datapoints) % datapoints_per_file == 0: - # Create a new file when the number of datapoints in the accumulator - # reaches datapoints_per_file. - df_concat = pd.concat(datapoints) - df_concat.to_pickle(filepath) - datapoints = [] - - -if __name__ == "__main__": - parser = argparse.ArgumentParser( - description='Virgo Dataset Generation' - ) - parser.add_argument( - '--target_folder_name', - type=str, - help='The folder to store the dataset.' - ) - parser.add_argument( - '--file_number', - type=int, - help='Number of files which will be created.' - ) - - args = parser.parse_args() - - # Creating the folders with the PKL files of timeseries data - generate_pkl_dataset( - folder_name=args.target_folder_name, - num_files=args.file_number, - duration=16, - sample_rate=500, - num_aux_channels=3, - num_waves_range=(10, 15), - noise_amplitude=0.5, - datapoints_per_file=500 - ) diff --git a/use-cases/virgo/trainer.py b/use-cases/virgo/trainer.py index 2423fdfd4..6f799f0ad 100644 --- a/use-cases/virgo/trainer.py +++ b/use-cases/virgo/trainer.py @@ -1,14 +1,14 @@ import os import time +from pathlib import Path from timeit import default_timer as timer from typing import Dict, Literal, Optional, Union +from itwinai.torch.profiling.profiler import profile_torch_trainer import numpy as np import torch import torch.nn as nn from ray import train -from src.model import Decoder, Decoder_2d_deep, GeneratorResNet, UNet -from src.utils import init_weights from torch.utils.data import Dataset, TensorDataset from tqdm import tqdm @@ -16,32 +16,31 @@ from itwinai.torch.config import TrainingConfiguration from itwinai.torch.distributed import DeepSpeedStrategy from itwinai.torch.trainer import TorchTrainer -from itwinai.torch.monitoring.monitoring import measure_gpu_utilization -from itwinai.torch.profiling.profiler import profile_torch_trainer +from src.model import Decoder, Decoder_2d_deep, GeneratorResNet, UNet +from src.utils import init_weights class VirgoTrainingConfiguration(TrainingConfiguration): """Virgo TrainingConfiguration""" + #: Whether to save best model on validation dataset. Defaults to True. save_best: bool = True - #: Loss function. Defaults to "L1". - loss: Literal["L1", "L2"] = "L1", + #: Loss function. Defaults to "l1". + loss: Literal["l1", "l2"] = ("l1",) #: Generator to train. Defaults to "unet". generator: Literal["simple", "deep", "resnet", "unet"] = "unet" - class NoiseGeneratorTrainer(TorchTrainer): - def __init__( - self, - num_epochs: int = 2, + self, num_epochs: int=2, config: Union[Dict, TrainingConfiguration] | None = None, - strategy: Optional[Literal["ddp", "deepspeed", "horovod"]] = 'ddp', + strategy: Optional[Literal["ddp", "deepspeed", "horovod"]] = "ddp", checkpoint_path: str = "checkpoints/epoch_{}.pth", logger: Optional[Logger] = None, random_seed: Optional[int] = None, name: str | None = None, - validation_every: int = 0 + validation_every: int = 0, + **kwargs, ) -> None: super().__init__( epochs=num_epochs, @@ -50,7 +49,8 @@ def __init__( logger=logger, random_seed=random_seed, name=name, - validation_every=validation_every + validation_every=validation_every, + **kwargs, ) self.save_parameters(**self.locals2params(locals())) # Global training configuration @@ -66,17 +66,16 @@ def create_model_loss_optimizer(self) -> None: generator = self.config.generator.lower() if generator == "simple": self.model = Decoder(3, norm=False) - init_weights(self.model, 'normal', scaling=.02) + init_weights(self.model, "normal", scaling=0.02) elif generator == "deep": self.model = Decoder_2d_deep(3) - init_weights(self.model, 'normal', scaling=.02) + init_weights(self.model, "normal", scaling=0.02) elif generator == "resnet": self.model = GeneratorResNet(3, 12, 1) - init_weights(self.model, 'normal', scaling=.01) + init_weights(self.model, "normal", scaling=0.01) elif generator == "unet": - self.model = UNet( - input_channels=3, output_channels=1, norm=False) - init_weights(self.model, 'normal', scaling=.02) + self.model = UNet(input_channels=3, output_channels=1, norm=False) + init_weights(self.model, "normal", scaling=0.02) else: raise ValueError("Unrecognized generator type! Got", generator) @@ -91,7 +90,8 @@ def create_model_loss_optimizer(self) -> None: # Optimizer self.optimizer = torch.optim.Adam( - self.model.parameters(), lr=self.config.optim_lr) + self.model.parameters(), lr=self.config.optim_lr + ) # IMPORTANT: model, optimizer, and scheduler need to be distributed @@ -115,17 +115,16 @@ def create_dataloaders( self, train_dataset: Dataset, validation_dataset: Dataset | None = None, - test_dataset: Dataset | None = None + test_dataset: Dataset | None = None, ) -> None: - """Override the create_dataloaders function to use the custom_collate function. - """ + """Override the create_dataloaders function to use the custom_collate function.""" # This is the case if a small dataset is used in-memory # - we can use the default collate_fn function if isinstance(train_dataset, TensorDataset): return super().create_dataloaders( train_dataset=train_dataset, validation_dataset=validation_dataset, - test_dataset=test_dataset + test_dataset=test_dataset, ) else: # If we are using a custom dataset for the large dataset, @@ -137,7 +136,7 @@ def create_dataloaders( pin_memory=self.config.pin_gpu_memory, generator=self.torch_rng, shuffle=self.config.shuffle_train, - collate_fn=self.custom_collate + collate_fn=self.custom_collate, ) if validation_dataset is not None: self.validation_dataloader = self.strategy.create_dataloader( @@ -147,7 +146,7 @@ def create_dataloaders( pin_memory=self.config.pin_gpu_memory, generator=self.torch_rng, shuffle=self.config.shuffle_validation, - collate_fn=self.custom_collate + collate_fn=self.custom_collate, ) if test_dataset is not None: self.test_dataloader = self.strategy.create_dataloader( @@ -157,7 +156,7 @@ def create_dataloaders( pin_memory=self.config.pin_gpu_memory, generator=self.torch_rng, shuffle=self.config.shuffle_test, - collate_fn=self.custom_collate + collate_fn=self.custom_collate, ) def custom_collate(self, batch): @@ -171,9 +170,10 @@ def custom_collate(self, batch): return torch.cat(batch) @profile_torch_trainer - @measure_gpu_utilization + # @measure_gpu_utilization def train(self): # Start the timer for profiling + # st = timer() # uncomment all lines relative to accuracy if you want to measure # IOU between generated and real spectrograms. @@ -182,20 +182,27 @@ def train(self): # implemented yet if self.strategy.is_main_worker: - print('TIMER: broadcast:', timer()-st, 's') - print('\nDEBUG: start training') - print('--------------------------------------------------------') - nnod = os.environ.get('SLURM_NNODES', 'unk') - s_name = f"{os.environ.get('DIST_MODE', 'unk')}-torch" + print("TIMER: broadcast:", timer() - st, "s") + print("\nDEBUG: start training") + print("--------------------------------------------------------") + # nnod = os.environ.get('SLURM_NNODES', 'unk') + # s_name = f"{os.environ.get('DIST_MODE', 'unk')}-torch" + # save_path + + num_nodes = int(os.environ.get("SLURM_NNODES", "unk")) + epoch_time_output_dir = Path("scalability-metrics/epoch-time") + epoch_time_file_name = f"epochtime_{self.strategy.name}_{num_nodes}N.csv" + epoch_time_output_path = epoch_time_output_dir / epoch_time_file_name epoch_time_tracker = EpochTimeTracker( - strategy_name=s_name, - save_path=f"epochtime_{s_name}_{nnod}N.csv" + strategy_name=self.strategy.name, + save_path=epoch_time_output_path, + num_nodes=num_nodes, ) loss_plot = [] val_loss_plot = [] acc_plot = [] val_acc_plot = [] - best_val_loss = float('inf') + best_val_loss = float("inf") for epoch in tqdm(range(self.num_epochs)): lt = timer() @@ -226,15 +233,17 @@ def train(self): epoch_loss.append(loss.detach().cpu().numpy()) t_list.append(timer() - t) # itwinai - log loss as metric - self.log(loss.detach().cpu().numpy(), - 'epoch_loss_batch', - kind='metric', - step=epoch*len(self.train_dataloader) + i, - batch_idx=i) + self.log( + loss.detach().cpu().numpy(), + "epoch_loss_batch", + kind="metric", + step=epoch * len(self.train_dataloader) + i, + batch_idx=i, + ) # acc=accuracy(generated.detach().cpu().numpy(),target.detach().cpu().numpy(),20) # epoch_acc.append(acc) if self.strategy.is_main_worker: - print('TIMER: train time', sum(t_list) / len(t_list), 's') + print("TIMER: train time", sum(t_list) / len(t_list), "s") val_loss = [] # val_acc = [] for i, batch in enumerate(self.validation_dataloader): @@ -250,11 +259,13 @@ def train(self): loss = self.loss(generated, target) val_loss.append(loss.detach().cpu().numpy()) # itwinai -log loss as metric - self.log(loss.detach().cpu().numpy(), - 'val_loss_batch', - kind='metric', - step=epoch*len(self.validation_dataloader) + i, - batch_idx=i) + self.log( + loss.detach().cpu().numpy(), + "val_loss_batch", + kind="metric", + step=epoch * len(self.validation_dataloader) + i, + batch_idx=i, + ) # acc=accuracy(generated.detach().cpu().numpy(),target.detach().cpu().numpy(),20) # val_acc.append(acc) loss_plot.append(np.mean(epoch_loss)) @@ -263,10 +274,8 @@ def train(self): # val_acc_plot.append(np.mean(val_acc)) # itwinai - Log metrics/losses - self.log(np.mean(epoch_loss), 'epoch_loss', - kind='metric', step=epoch) - self.log(np.mean(val_loss), 'val_loss', - kind='metric', step=epoch) + self.log(np.mean(epoch_loss), "epoch_loss", kind="metric", step=epoch) + self.log(np.mean(val_loss), "val_loss", kind="metric", step=epoch) # self.log(np.mean(epoch_acc), 'epoch_acc', # kind='metric', step=epoch) # self.log(np.mean(val_acc), 'val_acc', @@ -278,8 +287,11 @@ def train(self): et = time.time() # itwinai - print() in a multi-worker context (distributed) if self.strategy.is_main_worker: - print('epoch: {} loss: {} val loss: {} time:{}s'.format( - epoch, loss_plot[-1], val_loss_plot[-1], et-st)) + print( + "epoch: {} loss: {} val loss: {} time:{}s".format( + epoch, loss_plot[-1], val_loss_plot[-1], et - st + ) + ) # Save checkpoint every #validation_every epochs if self.validation_every and epoch % self.validation_every == 0: @@ -311,43 +323,45 @@ def train(self): if self.config.save_best and avg_loss < best_val_loss: # create checkpoint checkpoint = { - 'epoch': epoch, - 'model_state_dict': self.model.state_dict(), - 'optim_state_dict': self.optimizer.state_dict(), - 'loss': loss_plot[-1], - 'val_loss': val_loss_plot[-1], + "epoch": epoch, + "model_state_dict": self.model.state_dict(), + "optim_state_dict": self.optimizer.state_dict(), + "loss": loss_plot[-1], + "val_loss": val_loss_plot[-1], } # save checkpoint only if it is better than # the previous ones - checkpoint_filename = self.checkpoints_location.format( - epoch) + checkpoint_filename = self.checkpoints_location.format(epoch) torch.save(checkpoint, checkpoint_filename) # itwinai - log checkpoint as artifact - self.log(checkpoint_filename, - os.path.basename(checkpoint_filename), - kind='artifact') + self.log( + checkpoint_filename, + os.path.basename(checkpoint_filename), + kind="artifact", + ) # update best model best_val_loss = val_loss_plot[-1] - best_checkpoint_filename = ( - self.checkpoints_location.format('best') + best_checkpoint_filename = self.checkpoints_location.format( + "best" ) torch.save(checkpoint, best_checkpoint_filename) # itwinai - log checkpoint as artifact - self.log(best_checkpoint_filename, - os.path.basename(best_checkpoint_filename), - kind='artifact') + self.log( + best_checkpoint_filename, + os.path.basename(best_checkpoint_filename), + kind="artifact", + ) # return (loss_plot, val_loss_plot, # acc_plot, val_acc_plot ,acc_plot, val_acc_plot) if self.strategy.is_main_worker: - print('TIMER: epoch time:', timer()-lt, 's') - epoch_time_tracker.add_epoch_time(epoch-1, timer()-lt) + print("TIMER: epoch time:", timer() - lt, "s") + epoch_time_tracker.add_epoch_time(epoch - 1, timer() - lt) # Report training metrics of last epoch to Ray - train.report( - {"loss": np.mean(val_loss), - "train_loss": np.mean(epoch_loss)} - ) + train.report({"loss": np.mean(val_loss), "train_loss": np.mean(epoch_loss)}) + if self.strategy.is_main_worker: + epoch_time_tracker.save() return loss_plot, val_loss_plot, acc_plot, val_acc_plot From c51a1c49feec9067b6828fbcdec82ac1bc92e23f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 17:10:26 +0100 Subject: [PATCH 26/59] add requirements files and update pyproject toml --- env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 4 ++++ env-files/torch/requirements-macos.txt | 5 +++++ 3 files changed, 9 insertions(+) create mode 100644 env-files/torch/requirements-cpu.txt create mode 100644 env-files/torch/requirements-cuda.txt create mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt new file mode 100644 index 000000000..e69de29bb diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt new file mode 100644 index 000000000..00d03da8a --- /dev/null +++ b/env-files/torch/requirements-cuda.txt @@ -0,0 +1,4 @@ + +torch==2.4.* +torchvision +torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt new file mode 100644 index 000000000..38a99869c --- /dev/null +++ b/env-files/torch/requirements-macos.txt @@ -0,0 +1,5 @@ +torch==2.4.* +torchvision +torchaudio +py-cpuinfo +prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' From 76c7863cb29aff396e0d932e477ec5e5bf40814b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:23:54 +0100 Subject: [PATCH 27/59] update installation in pyproject.toml --- env-files/torch/install-horovod.sh | 34 ++++++++++++++++++++++++++ env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 4 --- env-files/torch/requirements-macos.txt | 5 ---- pyproject.toml | 11 --------- 5 files changed, 34 insertions(+), 20 deletions(-) create mode 100755 env-files/torch/install-horovod.sh delete mode 100644 env-files/torch/requirements-cpu.txt delete mode 100644 env-files/torch/requirements-cuda.txt delete mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh new file mode 100755 index 000000000..2a6c679d8 --- /dev/null +++ b/env-files/torch/install-horovod.sh @@ -0,0 +1,34 @@ +#!/bin/bash + +# Job configuration +#SBATCH --job-name=setup_venv +#SBATCH --account=intertwin +#SBATCH --output=logs_slurm/job.out +#SBATCH --error=logs_slurm/job.err +#SBATCH --time=00:10:00 + +# 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 CMake HDF5 PnetCDF libaio mpi4py + +source .venv/bin/activate +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 + +uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt deleted file mode 100644 index e69de29bb..000000000 diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt deleted file mode 100644 index 00d03da8a..000000000 --- a/env-files/torch/requirements-cuda.txt +++ /dev/null @@ -1,4 +0,0 @@ - -torch==2.4.* -torchvision -torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt deleted file mode 100644 index 38a99869c..000000000 --- a/env-files/torch/requirements-macos.txt +++ /dev/null @@ -1,5 +0,0 @@ -torch==2.4.* -torchvision -torchaudio -py-cpuinfo -prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' diff --git a/pyproject.toml b/pyproject.toml index 020d78378..952834f9b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -65,17 +65,6 @@ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] -# If we ever wanna put the docs requirements in this file instead -# Would let us do 'pip install ".[torch,docs,linux]"' instead of the multiple -# requirements files -# docs = [ -# "sphinx-rtd-theme==2.0.0", -# "nbsphinx==0.9.4", -# "myst-parser==2.0.0", -# "IPython", -# "tensorflow==2.16.*", -# ] - [project.urls] Homepage = "https://www.intertwin.eu/" Documentation = "https://itwinai.readthedocs.io/" From 468ef9470dc6dfdeef79fa224523653e66801d74 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 10:18:27 +0100 Subject: [PATCH 28/59] add pytorch extra to horovod and remove redundant script --- .../torch/install-horovod-deepspeed-cuda.sh | 2 +- env-files/torch/install-horovod.sh | 34 ------------------- 2 files changed, 1 insertion(+), 35 deletions(-) delete mode 100755 env-files/torch/install-horovod.sh diff --git a/env-files/torch/install-horovod-deepspeed-cuda.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh index 2b0719510..60e8fa6ec 100755 --- a/env-files/torch/install-horovod-deepspeed-cuda.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -33,7 +33,7 @@ export HOROVOD_WITH_PYTORCH=1 export HOROVOD_WITHOUT_TENSORFLOW=1 export HOROVOD_WITHOUT_MXNET=1 -uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git +uv pip install --no-cache-dir horovod[pytorch] # DeepSpeed variables export DS_BUILD_CCL_COMM=1 diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh deleted file mode 100755 index 2a6c679d8..000000000 --- a/env-files/torch/install-horovod.sh +++ /dev/null @@ -1,34 +0,0 @@ -#!/bin/bash - -# Job configuration -#SBATCH --job-name=setup_venv -#SBATCH --account=intertwin -#SBATCH --output=logs_slurm/job.out -#SBATCH --error=logs_slurm/job.err -#SBATCH --time=00:10:00 - -# 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 CMake HDF5 PnetCDF libaio mpi4py - -source .venv/bin/activate -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 - -uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git From b0cd8ac5450a79ecfbd04b7de3305c98300faddb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 15:03:08 +0100 Subject: [PATCH 29/59] update readme tutorial with pip installation --- README.md | 99 +++++++++++++++++++++++++++++++++---------------------- 1 file changed, 59 insertions(+), 40 deletions(-) diff --git a/README.md b/README.md index 7d3ef07ca..7907ffadc 100644 --- a/README.md +++ b/README.md @@ -128,72 +128,91 @@ 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. +#### Installation using pip -#### Installation with pip or uv +##### Creating a venv -You can install the environment using the Cuda wheel, CPU wheel or no wheel at all. -For macOS, you would e.g. use no wheel. This can be done by adding -`--extra-index-url https://download.pytorch.org/whl/` at the end of your -`pip install` statement. For example, if you want to download using the cuda wheel -you would do the following: +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 -pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +python -m venv ``` -If you want to use the CPU wheel instead, you would do the following: +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 -pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu +python -m venv .venv ``` -If you use linux or macOS, make sure to add this to your installation with extras. -For example, if you want to install for macOS as a developer, you would want to add -the `dev` extra and the `macos` extra as follows: +After this you can activate your venv using the following command: ```bash -pip install -e ".[dev,macos]" --no-cache-dir +source .venv/bin/activate ``` -> [!NOTE] -> We use `-e` here because we are in development mode and thus want any changes we make -> to immediately be applied to our venv without having to reinstall. +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` or `linux` depending on which OS 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 use `uv`, which will significantly speed up the installation, you can -prepend `uv` to the `pip` command and it will work in the same way. This assumes that -you already have `uv` installed on your system. An example: +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 -uv pip install -e . --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cu121 +pip install -e .[torch,dev,linux] \ + --no-cache-dir \ + --extra-index-url https://download.pytorch.org/whl/cu121 ``` -This 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: +If you wanted to install this locally on macOS (i.e. without CUDA) with PyTorch, you +would do the following instead: ```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 +pip install -e .[torch,dev,macos] ``` -> [!NOTE] -> It is possible to not use `--no-cache-dir` on a local computer, but on HPC systems we -> recommend using it in order to not fill up your `.cache` directory. + -##### Installation using `uv.lock` +#### 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: -The `uv.lock` file provides more precise information about the versions of the libraries -that are used and thus could be better to install from. If you have `uv` installed, -all you need to do is `uv sync` and it will make your `.venv` directory match the -spec in the `uv.lock` file. If you want to add new packages to the `uv.lock` file, you -can do so with the `uv lock` command. - -> [!WARNING] -> Even if you have a venv activated while running `uv sync`, the packages will not -> be installed there unless the venv's directory is called exactly `.venv`. +```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 + + + + + + + + + + + + + +#### PyTorch (+ Lightning) virtual environment with makefiles Makefile targets for environment installation: From 0bd9a0a12568c74ed250bf2cb8835098e84b7de8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 15:30:58 +0100 Subject: [PATCH 30/59] add uv tutorial in separate file --- README.md | 46 +++++++++++++++++++---------------- uv-tutorial.md | 65 ++++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 90 insertions(+), 21 deletions(-) create mode 100644 uv-tutorial.md diff --git a/README.md b/README.md index 7907ffadc..d8d04469e 100644 --- a/README.md +++ b/README.md @@ -128,14 +128,18 @@ git clone [--recurse-submodules] git@github.com:interTwin-eu/itwinai.git ### Install itwinai environment +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](/uv-tutorial.md) after reading +the following `pip` tutorial. + #### 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: +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 @@ -148,31 +152,31 @@ you use e.g. `uv`), then I would do: python -m venv .venv ``` -After this you can activate your venv using the following command: +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. +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. +We provide some __extras__ that can be activated depending on which platform you are +using. - `macos` or `linux` depending on which OS you use. Changes the version of `prov4ML`. -- `dev` for development purposes. Includes libraries for testing and tensorboard etc. -- `torch` for installation with PyTorch. +- `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: +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,linux] \ @@ -180,8 +184,8 @@ pip install -e .[torch,dev,linux] \ --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: +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] @@ -190,8 +194,8 @@ pip install -e .[torch,dev,macos] #### 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 +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 diff --git a/uv-tutorial.md b/uv-tutorial.md new file mode 100644 index 000000000..d413b1afb --- /dev/null +++ b/uv-tutorial.md @@ -0,0 +1,65 @@ +# 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 lock file 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). + +### 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 + +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`. + +## 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 +``` + +> [!NOTE] +> This will add the package to your `.venv` venv, so make sure to have symlinked to +> this directory if you haven't already. From 4b1876b343d11a6ce3817cd5d1491f8906d1cb91 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 15:52:29 +0100 Subject: [PATCH 31/59] fix linting errors --- README.md | 3 ++- uv-tutorial.md | 4 +++- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d8d04469e..bc9590ed4 100644 --- a/README.md +++ b/README.md @@ -163,7 +163,7 @@ 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 +We provide some _extras_ that can be activated depending on which platform you are using. - `macos` or `linux` depending on which OS you use. Changes the version of `prov4ML`. @@ -194,6 +194,7 @@ pip install -e .[torch,dev,macos] #### 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: diff --git a/uv-tutorial.md b/uv-tutorial.md index d413b1afb..506c48d8e 100644 --- a/uv-tutorial.md +++ b/uv-tutorial.md @@ -1,7 +1,8 @@ # 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 lock file called +packages, similar to how `poetry` works. This is done using a lockfile called `uv.lock`. ## uv as a drop-in replacement for pip @@ -20,6 +21,7 @@ bit annoying, especially with an existing venv, so we recommend using a [symlink](https://en.wikipedia.org/wiki/Symbolic_link). ### Symlinking .venv + To create a symlink between your venv and the `.venv` directory, you can use the following command: From 737f70bb31e5f376881a76b87ac4755accbd819b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 16:17:50 +0100 Subject: [PATCH 32/59] update horovod install script --- .../torch/install-horovod-deepspeed-cuda.sh | 28 +++++++++---------- pyproject.toml | 2 +- use-cases/eurac/requirements.txt | 1 + 3 files changed, 16 insertions(+), 15 deletions(-) diff --git a/env-files/torch/install-horovod-deepspeed-cuda.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh index 60e8fa6ec..4709763de 100755 --- a/env-files/torch/install-horovod-deepspeed-cuda.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -14,10 +14,22 @@ ml --force purge ml Stages/2024 GCC OpenMPI CUDA/12 cuDNN MPI-settings/CUDA -ml Python CMake HDF5 PnetCDF libaio mpi4py git Clang +ml Python/3.11.3 CMake HDF5 PnetCDF libaio mpi4py git Clang source .venv/bin/activate +# 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 + +pip install --no-cache-dir --no-build-isolation "deepspeed==0.15.*" + # Horovod variables export LDSHARED="$CC -shared" && export CMAKE_CXX_STANDARD=17 @@ -33,16 +45,4 @@ export HOROVOD_WITH_PYTORCH=1 export HOROVOD_WITHOUT_TENSORFLOW=1 export HOROVOD_WITHOUT_MXNET=1 -uv pip install --no-cache-dir horovod[pytorch] - -# 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 - -uv pip install --no-cache-dir --no-build-isolation deepspeed +pip install --no-cache-dir 'horovod[pytorch] @ git+https://github.com/horovod/horovod' diff --git a/pyproject.toml b/pyproject.toml index 952834f9b..d2b154d31 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,7 +55,7 @@ dev = [ "pytest-cov>=4.1.0", "tensorflow==2.16.*", # needed by tests on tensorboard "ipykernel>=6.29.5", - "ipython>=8.29.0", + "ipython", "isort>=5.13.2", ] macos = [ diff --git a/use-cases/eurac/requirements.txt b/use-cases/eurac/requirements.txt index 2d134c288..5b35ca1b9 100644 --- a/use-cases/eurac/requirements.txt +++ b/use-cases/eurac/requirements.txt @@ -4,3 +4,4 @@ tqdm cf_xarray requests aiohttp +ray From eb8cb08dfd30a061335749bf92c8dc2e5083b6ca Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 15 Nov 2024 17:39:11 +0100 Subject: [PATCH 33/59] fix dead link --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index bc9590ed4..1eb674f6b 100644 --- a/README.md +++ b/README.md @@ -129,7 +129,7 @@ git clone [--recurse-submodules] git@github.com:interTwin-eu/itwinai.git ### Install itwinai environment 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](/uv-tutorial.md) after reading +you are a developer, you should see the [uv tutorial](./uv-tutorial.md) after reading the following `pip` tutorial. #### Installation using pip From 7a784f530d13a904da3a2fbd02053e2f8ac2ed52 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:22:27 +0100 Subject: [PATCH 34/59] update readme --- .../torch-scaling-test/README.md | 5 +- uv-tutorial.md | 12 + uv.lock | 6578 +++++++++++++++++ 3 files changed, 6592 insertions(+), 3 deletions(-) create mode 100644 uv.lock diff --git a/tutorials/distributed-ml/torch-scaling-test/README.md b/tutorials/distributed-ml/torch-scaling-test/README.md index 1344504e3..7525b581e 100644 --- a/tutorials/distributed-ml/torch-scaling-test/README.md +++ b/tutorials/distributed-ml/torch-scaling-test/README.md @@ -32,9 +32,8 @@ 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/uv-tutorial.md b/uv-tutorial.md index 506c48d8e..6047d13e4 100644 --- a/uv-tutorial.md +++ b/uv-tutorial.md @@ -53,6 +53,18 @@ uv sync --extra torch --extra macos These will usually correspond to the optional dependencies in the `pyproject.toml`. +### 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 diff --git a/uv.lock b/uv.lock new file mode 100644 index 000000000..f2758319c --- /dev/null +++ b/uv.lock @@ -0,0 +1,6578 @@ +version = 1 +requires-python = ">=3.10" +resolution-markers = [ + "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 < '3.11' 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 >= '3.13' and platform_system != 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.13' 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 < '3.11' 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 >= '3.13' and platform_system == 'Windows' and sys_platform != 'linux'", + "python_full_version >= '3.13' and platform_system == 'Windows' and sys_platform == 'linux'", +] + +[[package]] +name = "absl-py" +version = "2.1.0" 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"https://files.pythonhosted.org/packages/3f/50/bad581df71744867e9468ebd0bcd6505de3b275e06f202c2cb016e3ff56f/zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", size = 24545 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 }, +] From 3ac931388481e641105885b4efb71cc2b8502d3b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 09:40:15 +0100 Subject: [PATCH 35/59] add uv installation command to readme --- uv-tutorial.md | 17 ++++++++++++++++- 1 file changed, 16 insertions(+), 1 deletion(-) diff --git a/uv-tutorial.md b/uv-tutorial.md index 6047d13e4..4600025bf 100644 --- a/uv-tutorial.md +++ b/uv-tutorial.md @@ -51,7 +51,22 @@ can be added with the `--extra` flag as follows: uv sync --extra torch --extra macos ``` -These will usually correspond to the optional dependencies in the `pyproject.toml`. +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 --extra torch --extra dev --extra linux \ + --no-cache \ + --index https://download.pytorch.org/whl/cu121 +``` + +If you are developing on your local computer with macOS, then you would use: + +```bash +uv sync --extra torch --extra dev --extra macos +``` + ### Updating the uv.lock file From f7519123200a0b216a32167879cc91c638e62aee Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 17:10:26 +0100 Subject: [PATCH 36/59] add requirements files and update pyproject toml --- env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 4 ++++ env-files/torch/requirements-macos.txt | 5 +++++ pyproject.toml | 15 +++++++++++++++ 4 files changed, 24 insertions(+) create mode 100644 env-files/torch/requirements-cpu.txt create mode 100644 env-files/torch/requirements-cuda.txt create mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt new file mode 100644 index 000000000..e69de29bb diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt new file mode 100644 index 000000000..00d03da8a --- /dev/null +++ b/env-files/torch/requirements-cuda.txt @@ -0,0 +1,4 @@ + +torch==2.4.* +torchvision +torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt new file mode 100644 index 000000000..38a99869c --- /dev/null +++ b/env-files/torch/requirements-macos.txt @@ -0,0 +1,5 @@ +torch==2.4.* +torchvision +torchaudio +py-cpuinfo +prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' diff --git a/pyproject.toml b/pyproject.toml index d2b154d31..59d660c22 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -64,6 +64,21 @@ macos = [ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] +linux = [] +macos = [ + "torch==2.4.*", + "torchvision", + "torchaudio", + "py-cpuinfo", +] +cuda = [ + # "torch==2.4.* @ https://download.pytorch.org/whl/cu121", + # "torchvision @ https://download.pytorch.org/whl/cu121", + # "torchaudio @ https://download.pytorch.org/whl/cu121", + "py-cpuinfo", + "horovod" +] + [project.urls] Homepage = "https://www.intertwin.eu/" From 6f9c5c1e996a4b2e32b9ade0edb935d6863f75d6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 11 Nov 2024 18:02:14 +0100 Subject: [PATCH 37/59] update pyproject --- pyproject.toml | 15 --------------- 1 file changed, 15 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 59d660c22..d2b154d31 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -64,21 +64,6 @@ macos = [ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] -linux = [] -macos = [ - "torch==2.4.*", - "torchvision", - "torchaudio", - "py-cpuinfo", -] -cuda = [ - # "torch==2.4.* @ https://download.pytorch.org/whl/cu121", - # "torchvision @ https://download.pytorch.org/whl/cu121", - # "torchaudio @ https://download.pytorch.org/whl/cu121", - "py-cpuinfo", - "horovod" -] - [project.urls] Homepage = "https://www.intertwin.eu/" From 6e65624d5e01006e3f24ae5ab045709d2786fd4c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 12 Nov 2024 16:23:54 +0100 Subject: [PATCH 38/59] update installation in pyproject.toml --- env-files/torch/install-horovod.sh | 34 ++++++++++++++++++++++++++ env-files/torch/requirements-cpu.txt | 0 env-files/torch/requirements-cuda.txt | 4 --- env-files/torch/requirements-macos.txt | 5 ---- pyproject.toml | 6 +++++ 5 files changed, 40 insertions(+), 9 deletions(-) create mode 100755 env-files/torch/install-horovod.sh delete mode 100644 env-files/torch/requirements-cpu.txt delete mode 100644 env-files/torch/requirements-cuda.txt delete mode 100644 env-files/torch/requirements-macos.txt diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh new file mode 100755 index 000000000..2a6c679d8 --- /dev/null +++ b/env-files/torch/install-horovod.sh @@ -0,0 +1,34 @@ +#!/bin/bash + +# Job configuration +#SBATCH --job-name=setup_venv +#SBATCH --account=intertwin +#SBATCH --output=logs_slurm/job.out +#SBATCH --error=logs_slurm/job.err +#SBATCH --time=00:10:00 + +# 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 CMake HDF5 PnetCDF libaio mpi4py + +source .venv/bin/activate +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 + +uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git diff --git a/env-files/torch/requirements-cpu.txt b/env-files/torch/requirements-cpu.txt deleted file mode 100644 index e69de29bb..000000000 diff --git a/env-files/torch/requirements-cuda.txt b/env-files/torch/requirements-cuda.txt deleted file mode 100644 index 00d03da8a..000000000 --- a/env-files/torch/requirements-cuda.txt +++ /dev/null @@ -1,4 +0,0 @@ - -torch==2.4.* -torchvision -torchaudio diff --git a/env-files/torch/requirements-macos.txt b/env-files/torch/requirements-macos.txt deleted file mode 100644 index 38a99869c..000000000 --- a/env-files/torch/requirements-macos.txt +++ /dev/null @@ -1,5 +0,0 @@ -torch==2.4.* -torchvision -torchaudio -py-cpuinfo -prov4ml[apple]@git+https://github.com/matbun/ProvML ; sys_platform == 'darwin' diff --git a/pyproject.toml b/pyproject.toml index d2b154d31..80e5a5b24 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -64,6 +64,12 @@ macos = [ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] +macos = [ + "prov4ml[apple]@git+https://github.com/matbun/ProvML" +] +linux = [ + "prov4ml[linux]@git+https://github.com/matbun/ProvML" +] [project.urls] Homepage = "https://www.intertwin.eu/" From 0a731edc28a9e87244a4cfc1e537c3e1b5e4a1b4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 14 Nov 2024 17:22:51 +0100 Subject: [PATCH 39/59] add version numbers to packages in pyproject.toml --- pyproject.toml | 6 ------ 1 file changed, 6 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 80e5a5b24..d2b154d31 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -64,12 +64,6 @@ macos = [ linux = [ "prov4ml[linux]@git+https://github.com/matbun/ProvML" ] -macos = [ - "prov4ml[apple]@git+https://github.com/matbun/ProvML" -] -linux = [ - "prov4ml[linux]@git+https://github.com/matbun/ProvML" -] [project.urls] Homepage = "https://www.intertwin.eu/" From def18fd9e990b7990b45fd04463c31684bc2d967 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 11:46:33 +0100 Subject: [PATCH 40/59] update horovod install script and add pip as dependency --- env-files/torch/install-horovod.sh | 34 ------------------------------ pyproject.toml | 1 + uv-tutorial.md | 5 +++++ uv.lock | 11 ++++++++++ 4 files changed, 17 insertions(+), 34 deletions(-) delete mode 100755 env-files/torch/install-horovod.sh diff --git a/env-files/torch/install-horovod.sh b/env-files/torch/install-horovod.sh deleted file mode 100755 index 2a6c679d8..000000000 --- a/env-files/torch/install-horovod.sh +++ /dev/null @@ -1,34 +0,0 @@ -#!/bin/bash - -# Job configuration -#SBATCH --job-name=setup_venv -#SBATCH --account=intertwin -#SBATCH --output=logs_slurm/job.out -#SBATCH --error=logs_slurm/job.err -#SBATCH --time=00:10:00 - -# 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 CMake HDF5 PnetCDF libaio mpi4py - -source .venv/bin/activate -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 - -uv pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/horovod.git diff --git a/pyproject.toml b/pyproject.toml index d2b154d31..94d92c11a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -39,6 +39,7 @@ dependencies = [ "omegaconf>=2.3.0", "jsonargparse[signatures]>=4.34.0", "matplotlib>=3.9.2", + "pip>=24.3.1", ] [project.optional-dependencies] diff --git a/uv-tutorial.md b/uv-tutorial.md index 4600025bf..aebf35f4a 100644 --- a/uv-tutorial.md +++ b/uv-tutorial.md @@ -38,6 +38,11 @@ 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 diff --git a/uv.lock b/uv.lock index f2758319c..d75988301 100644 --- a/uv.lock +++ b/uv.lock @@ -1287,6 +1287,7 @@ dependencies = [ { name = "numpy" }, { name = "omegaconf" }, { name = "packaging" }, + { name = "pip" }, { name = "py-cpuinfo" }, { name = "pydantic" }, { name = "pyyaml" }, @@ -1333,6 +1334,7 @@ requires-dist = [ { name = "numpy", specifier = "<2.0.0" }, { name = "omegaconf", specifier = ">=2.3.0" }, { name = "packaging", specifier = ">=24.2" }, + { name = "pip", specifier = ">=24.3.1" }, { name = "prov4ml", extras = ["apple"], marker = "extra == 'macos'", git = "https://github.com/matbun/ProvML" }, { name = "prov4ml", extras = ["linux"], marker = "extra == 'linux'", git = "https://github.com/matbun/ProvML" }, { name = "py-cpuinfo", specifier = ">=9.0.0" }, @@ -2458,6 +2460,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/ec/3d/c32a51d848401bd94cabb8767a39621496491ee7cd5199856b77da9b18ad/pillow-11.0.0-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:224aaa38177597bb179f3ec87eeefcce8e4f85e608025e9cfac60de237ba6316", size = 2567508 }, ] +[[package]] +name = "pip" +version = "24.3.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f4/b1/b422acd212ad7eedddaf7981eee6e5de085154ff726459cf2da7c5a184c1/pip-24.3.1.tar.gz", hash = "sha256:ebcb60557f2aefabc2e0f918751cd24ea0d56d8ec5445fe1807f1d2109660b99", size = 1931073 } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ef/7d/500c9ad20238fcfcb4cb9243eede163594d7020ce87bd9610c9e02771876/pip-24.3.1-py3-none-any.whl", hash = "sha256:3790624780082365f47549d032f3770eeb2b1e8bd1f7b2e02dace1afa361b4ed", size = 1822182 }, +] + [[package]] name = "pipreqs" version = "0.4.13" From 6c8f4db6afc527b28b082fcca10d4dd66b2526d5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 17:16:17 +0100 Subject: [PATCH 41/59] formatting --- pyproject.toml | 6 ------ use-cases/eurac/trainer.py | 9 ++++----- use-cases/virgo/trainer.py | 6 +++--- 3 files changed, 7 insertions(+), 14 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index cf9a4bb39..eecfeff40 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -72,12 +72,6 @@ docs = [ "IPython", "tensorflow==2.16.*", ] -macos = [ - "prov4ml[apple]@git+https://github.com/matbun/ProvML" -] -linux = [ - "prov4ml[linux]@git+https://github.com/matbun/ProvML" -] [project.urls] Homepage = "https://www.intertwin.eu/" diff --git a/use-cases/eurac/trainer.py b/use-cases/eurac/trainer.py index 24c6f3cc9..622aad1f0 100644 --- a/use-cases/eurac/trainer.py +++ b/use-cases/eurac/trainer.py @@ -1,7 +1,7 @@ import os from pathlib import Path from timeit import default_timer -from typing import Dict, Literal, Optional, Union, Any, Tuple +from typing import Any, Dict, Literal, Optional, Tuple, Union import pandas as pd import torch @@ -25,10 +25,9 @@ NonDistributedStrategy, TorchDDPStrategy, ) +from itwinai.torch.profiling.profiler import profile_torch_trainer from itwinai.torch.trainer import TorchTrainer from itwinai.torch.type import Metric -from itwinai.torch.profiling.profiler import profile_torch_trainer -from itwinai.torch.monitoring.monitoring import measure_gpu_utilization class RNNDistributedTrainer(TorchTrainer): @@ -155,11 +154,11 @@ def train(self): num_nodes = int(os.environ.get("SLURM_NNODES", "unk")) epoch_time_output_dir = Path("scalability-metrics/epoch-time") epoch_time_file_name = f"epochtime_{self.strategy.name}_{num_nodes}N.csv" - epoch_time_output_path = epoch_time_output_dir / epoch_time_file_name + epoch_time_output_path = epoch_time_output_dir / epoch_time_file_name epoch_time_tracker = EpochTimeTracker( strategy_name=self.strategy.name, - save_path=epoch_time_output_path, + save_path=epoch_time_output_path, num_nodes=num_nodes ) diff --git a/use-cases/virgo/trainer.py b/use-cases/virgo/trainer.py index e4bc51627..b4873e24d 100644 --- a/use-cases/virgo/trainer.py +++ b/use-cases/virgo/trainer.py @@ -2,10 +2,8 @@ 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 @@ -13,9 +11,11 @@ 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 From 690bed3a6af445940454023ef49acdd58fe26233 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 17:30:39 +0100 Subject: [PATCH 42/59] fix linting --- use-cases/eurac/runall.sh | 4 ++-- uv-tutorial.md | 5 ++--- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/use-cases/eurac/runall.sh b/use-cases/eurac/runall.sh index b24d55e5d..10ee15dec 100755 --- a/use-cases/eurac/runall.sh +++ b/use-cases/eurac/runall.sh @@ -35,5 +35,5 @@ submit_job () { echo "Running distributed training on $NUM_NODES nodes with $NUM_GPUS GPUs per node" submit_job "ddp" -# submit_job "deepspeed" -# submit_job "horovod" +submit_job "deepspeed" +submit_job "horovod" diff --git a/uv-tutorial.md b/uv-tutorial.md index aebf35f4a..01a53d008 100644 --- a/uv-tutorial.md +++ b/uv-tutorial.md @@ -72,18 +72,17 @@ If you are developing on your local computer with macOS, then you would use: uv sync --extra torch --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: +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`. +from the `pyproject.toml`. ## Adding new packages to the project From 9412e48a172e0b313cabd323aa5fffcd67a14012 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 17:35:29 +0100 Subject: [PATCH 43/59] trailing whitespace --- tutorials/distributed-ml/torch-scaling-test/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/distributed-ml/torch-scaling-test/README.md b/tutorials/distributed-ml/torch-scaling-test/README.md index 7525b581e..b03141214 100644 --- a/tutorials/distributed-ml/torch-scaling-test/README.md +++ b/tutorials/distributed-ml/torch-scaling-test/README.md @@ -32,7 +32,7 @@ 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 +`slurm.sh`.You can select the distributed training algorithm and provide the command to execute setting SLURM environment variables using the `--export` option: ```bash From a23583a891f577c6c3a38b17bde56c093c68da26 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 18:03:46 +0100 Subject: [PATCH 44/59] remove comment from readme --- README.md | 13 ------------- 1 file changed, 13 deletions(-) diff --git a/README.md b/README.md index 1eb674f6b..34b38a77e 100644 --- a/README.md +++ b/README.md @@ -204,19 +204,6 @@ pip install --no-cache-dir --no-build-isolation git+https://github.com/horovod/h pip install --no-cache-dir --no-build-isolation deepspeed ``` - - - - - - - - - - - - - #### PyTorch (+ Lightning) virtual environment with makefiles Makefile targets for environment installation: From 60cbc6f40cb8fc2048384b8f901ef65a79834882 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Tue, 19 Nov 2024 18:07:41 +0100 Subject: [PATCH 45/59] remove comments and small formatting difference --- env-files/torch/generic_torch.sh | 35 -------------------------------- use-cases/virgo/trainer.py | 3 ++- 2 files changed, 2 insertions(+), 36 deletions(-) diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index af700d880..7de96f416 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -133,44 +133,9 @@ else export HOROVOD_WITHOUT_TENSORFLOW=1 export HOROVOD_WITHOUT_MXNET=1 -# # need to modify for torch 2.1.0 -# git clone --recurse-submodules https://github.com/horovod/horovod.git -# line=$(cat -n horovod/CMakeLists.txt | grep CMAKE_CXX_STANDARD | awk '{print $1}' | head -n 1) -# var='set(CMAKE_CXX_STANDARD 17)' -# sed -i "${line}s|.*|$var|" horovod/CMakeLists.txt -# line=$(cat -n horovod/horovod/torch/CMakeLists.txt | grep CMAKE_CXX_STANDARD | awk '{print $1}' | head -n 1) -# var=' set(CMAKE_CXX_STANDARD 17)' -# sed -i "${line}s|.*|$var|" horovod/horovod/torch/CMakeLists.txt - -# # create tar! -# rm -rf horovod.tar.gz -# tar czf horovod.tar.gz horovod - -# # install -# pip install --no-cache-dir horovod.tar.gz -# rm -rf horovod horovod.tar.gz - - # Cleaner Horovod installation - # https://github.com/horovod/horovod/pull/3998 - # Assume that Horovod env vars are already in the current env! pip install --no-cache-dir git+https://github.com/horovod/horovod.git || exit 1 - # pip install --no-cache-dir git+https://github.com/thomas-bouvier/horovod.git@compile-cpp17 || exit 1 fi -# get required libraries in reqs.txt -# if [ -f "${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 diff --git a/use-cases/virgo/trainer.py b/use-cases/virgo/trainer.py index b4873e24d..e495413ed 100644 --- a/use-cases/virgo/trainer.py +++ b/use-cases/virgo/trainer.py @@ -33,7 +33,8 @@ class VirgoTrainingConfiguration(TrainingConfiguration): class NoiseGeneratorTrainer(TorchTrainer): def __init__( - self, num_epochs: int=2, + self, + num_epochs: int = 2, config: Union[Dict, TrainingConfiguration] | None = None, strategy: Optional[Literal["ddp", "deepspeed", "horovod"]] = "ddp", checkpoint_path: str = "checkpoints/epoch_{}.pth", From 8f88c3ef51dee8d7121881a65ab73606ecd10020 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 10:51:31 +0100 Subject: [PATCH 46/59] move uv tutorial under docs/ --- README.md | 2 +- uv-tutorial.md => docs/uv-tutorial.md | 0 2 files changed, 1 insertion(+), 1 deletion(-) rename uv-tutorial.md => docs/uv-tutorial.md (100%) diff --git a/README.md b/README.md index 34b38a77e..862adb726 100644 --- a/README.md +++ b/README.md @@ -129,7 +129,7 @@ git clone [--recurse-submodules] git@github.com:interTwin-eu/itwinai.git ### Install itwinai environment 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](./uv-tutorial.md) after reading +you are a developer, you should see the [uv tutorial](/docs/uv-tutorial.md) after reading the following `pip` tutorial. #### Installation using pip diff --git a/uv-tutorial.md b/docs/uv-tutorial.md similarity index 100% rename from uv-tutorial.md rename to docs/uv-tutorial.md From 018cc47616c20569b01bf424dce284169c38a23f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 10:58:42 +0100 Subject: [PATCH 47/59] update readme with nvidia and amd instead of linux --- README.md | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 5ae669f85..6a4a3ff80 100644 --- a/README.md +++ b/README.md @@ -166,7 +166,8 @@ commands they will use the version from your venv. We provide some _extras_ that can be activated depending on which platform you are using. -- `macos` or `linux` depending on which OS you use. Changes the version of `prov4ML`. +- `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. @@ -179,7 +180,7 @@ directory, as you can very easily reach your disk quota otherwise. An example of complete command for installing as a developer on HPC with CUDA thus becomes: ```bash -pip install -e .[torch,dev,linux] \ +pip install -e .[torch,dev,nvidia] \ --no-cache-dir \ --extra-index-url https://download.pytorch.org/whl/cu121 ``` From 6895472eff9eae2c2badbc86705ab1b1d04b2b8d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 11:04:23 +0100 Subject: [PATCH 48/59] remove duplicate entries in pyproject and reformat distributed file --- pyproject.toml | 6 ------ src/itwinai/torch/distributed.py | 24 ++++++++++++------------ 2 files changed, 12 insertions(+), 18 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 24dc695cd..897ea5068 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -60,12 +60,6 @@ dev = [ "ipython", "isort>=5.13.2", ] -macos = [ - "prov4ml[apple]@git+https://github.com/matbun/ProvML" -] -linux = [ - "prov4ml[linux]@git+https://github.com/matbun/ProvML" -] docs = [ "sphinx-rtd-theme==2.0.0", "nbsphinx==0.9.4", diff --git a/src/itwinai/torch/distributed.py b/src/itwinai/torch/distributed.py index f8aaeb1a3..e3fea41a4 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, @@ -409,9 +411,7 @@ def init(self) -> None: which is already initialized. """ if not distributed_resources_available(): - raise RuntimeError( - "Trying to run distributed on insufficient resources." - ) + raise RuntimeError("Trying to run distributed on insufficient resources.") if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") dist.init_process_group(backend=self.backend) @@ -578,9 +578,7 @@ def init(self) -> None: self.deepspeed = deepspeed if not distributed_resources_available(): - raise RuntimeError( - "Trying to run distributed on insufficient resources." - ) + raise RuntimeError("Trying to run distributed on insufficient resources.") if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") @@ -699,7 +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). @@ -747,9 +747,7 @@ def init(self) -> None: already initialized. """ if not distributed_resources_available(): - raise RuntimeError( - "Trying to run distributed on insufficient resources." - ) + raise RuntimeError("Trying to run distributed on insufficient resources.") if self.is_initialized: raise DistributedStrategyError("Strategy was already initialized") @@ -880,7 +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. From 69e1dd2be82f571be05c4cf3bbfdb12c04616cff Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 11:16:31 +0100 Subject: [PATCH 49/59] update readmes --- docs/uv-tutorial.md | 10 ++++++---- pyproject.toml | 1 + tutorials/distributed-ml/torch-scaling-test/README.md | 2 +- 3 files changed, 8 insertions(+), 5 deletions(-) diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md index 01a53d008..4af0e47d5 100644 --- a/docs/uv-tutorial.md +++ b/docs/uv-tutorial.md @@ -18,7 +18,9 @@ If you wish to use the `uv sync` and/or `uv lock` commands, which is how you use 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). +[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 @@ -61,7 +63,7 @@ particular, if you are a developer you would use one of the following two comman you are on HPC with cuda, you would use: ```bash -uv sync --extra torch --extra dev --extra linux \ +uv sync --extra torch --extra dev \ --no-cache \ --index https://download.pytorch.org/whl/cu121 ``` @@ -93,6 +95,6 @@ can use the following command: uv add ``` -> [!NOTE] +> [!Warning] > This will add the package to your `.venv` venv, so make sure to have symlinked to -> this directory if you haven't already. +> this directory if you haven't already. diff --git a/pyproject.toml b/pyproject.toml index 897ea5068..f7162d829 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,6 +41,7 @@ dependencies = [ "matplotlib>=3.9.2", "pip>=24.3.1", "prov4ml@git+https://github.com/matbun/ProvML@new-main", + "ray" ] [project.optional-dependencies] diff --git a/tutorials/distributed-ml/torch-scaling-test/README.md b/tutorials/distributed-ml/torch-scaling-test/README.md index f74b82127..81adfa0d5 100644 --- a/tutorials/distributed-ml/torch-scaling-test/README.md +++ b/tutorials/distributed-ml/torch-scaling-test/README.md @@ -34,7 +34,7 @@ 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 +`slurm.sh`. You can select the distributed training algorithm and provide the command to execute setting SLURM environment variables using the `--export` option: ```bash From bb815e633533d16622890c209f3111669de4ee51 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 11:19:23 +0100 Subject: [PATCH 50/59] separate horovod ds installation script into two files --- env-files/torch/horovod-deepspeed.slurm | 20 ++++++++++++++++++ .../torch/install-horovod-deepspeed-cuda.sh | 21 +------------------ 2 files changed, 21 insertions(+), 20 deletions(-) create mode 100644 env-files/torch/horovod-deepspeed.slurm diff --git a/env-files/torch/horovod-deepspeed.slurm b/env-files/torch/horovod-deepspeed.slurm new file mode 100644 index 000000000..be126f7e6 --- /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 +bash 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 index 4709763de..e0fb2bede 100755 --- a/env-files/torch/install-horovod-deepspeed-cuda.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -1,23 +1,3 @@ -#!/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 - # DeepSpeed variables export DS_BUILD_CCL_COMM=1 export DS_BUILD_UTILS=1 @@ -28,6 +8,7 @@ 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.*" # Horovod variables From d06dfe9f31213ee7e299f0f8baf9bab92ac113b4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 16:30:17 +0100 Subject: [PATCH 51/59] fix linting errors and update dependencies --- README.md | 6 +- docs/uv-tutorial.md | 6 +- .../torch/install-horovod-deepspeed-cuda.sh | 2 + pyproject.toml | 23 +- uv.lock | 16551 +++++++++++++--- 5 files changed, 14327 insertions(+), 2261 deletions(-) diff --git a/README.md b/README.md index 6a4a3ff80..62e1dfd4f 100644 --- a/README.md +++ b/README.md @@ -166,7 +166,7 @@ commands they will use the version from your venv. 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 +- `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. @@ -180,7 +180,7 @@ directory, as you can very easily reach your disk quota otherwise. An example of complete command for installing as a developer on HPC with CUDA thus becomes: ```bash -pip install -e .[torch,dev,nvidia] \ +pip install -e ".[torch,dev,nvidia]" \ --no-cache-dir \ --extra-index-url https://download.pytorch.org/whl/cu121 ``` @@ -189,7 +189,7 @@ If you wanted to install this locally on macOS (i.e. without CUDA) with PyTorch, would do the following instead: ```bash -pip install -e .[torch,dev,macos] +pip install -e ".[torch,dev,macos]" ``` diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md index 4af0e47d5..f55a7997e 100644 --- a/docs/uv-tutorial.md +++ b/docs/uv-tutorial.md @@ -63,7 +63,7 @@ particular, if you are a developer you would use one of the following two comman you are on HPC with cuda, you would use: ```bash -uv sync --extra torch --extra dev \ +uv sync --extra torch --extra dev --extra tf \ --no-cache \ --index https://download.pytorch.org/whl/cu121 ``` @@ -71,7 +71,7 @@ uv sync --extra torch --extra dev \ If you are developing on your local computer with macOS, then you would use: ```bash -uv sync --extra torch --extra dev --extra macos +uv sync --extra torch --extra tf --extra dev --extra macos ``` ### Updating the uv.lock file @@ -97,4 +97,4 @@ 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. +> this directory if you haven't already. diff --git a/env-files/torch/install-horovod-deepspeed-cuda.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh index e0fb2bede..9283fdf86 100755 --- a/env-files/torch/install-horovod-deepspeed-cuda.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -1,3 +1,5 @@ +#!/bin/bash + # DeepSpeed variables export DS_BUILD_CCL_COMM=1 export DS_BUILD_UTILS=1 diff --git a/pyproject.toml b/pyproject.toml index f7162d829..94309ef11 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -52,11 +52,19 @@ torch = [ "torchvision>=0.19.1", "torchaudio>=2.4.1", ] +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", - "tensorflow==2.16.*", # needed by tests on tensorboard "ipykernel>=6.29.5", "ipython", "isort>=5.13.2", @@ -70,7 +78,7 @@ 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/" @@ -98,9 +106,14 @@ 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" }, + ], +] # Ruff configuration: https://docs.astral.sh/ruff/configuration/ [tool.ruff] diff --git a/uv.lock b/uv.lock index d75988301..de33e393e 100644 --- a/uv.lock +++ b/uv.lock @@ -2,2164 +2,9720 @@ version = 1 requires-python = ">=3.10" resolution-markers = [ "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 < '3.11' 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 < '3.11' 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 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< '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 < '3.11' 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 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== '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 == '3.11.*' 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 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e612dd690..11f30a954 100644 --- a/Makefile +++ b/Makefile @@ -44,7 +44,7 @@ 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" + PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ -m "not slurm" test-jsc: tests/run_on_jsc.sh bash tests/run_on_jsc.sh diff --git a/pyproject.toml b/pyproject.toml index 94309ef11..a347ac273 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,7 +41,8 @@ dependencies = [ "matplotlib>=3.9.2", "pip>=24.3.1", "prov4ml@git+https://github.com/matbun/ProvML@new-main", - "ray" + "ray", + "prov", ] [project.optional-dependencies] diff --git a/tests/conftest.py b/tests/conftest.py index 0575e30e1..0ce4e90c8 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -11,6 +11,7 @@ import pytest +from pathlib import Path @pytest.fixture def torch_env() -> str: @@ -20,11 +21,13 @@ 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")) + return str(env_path.resolve()) + # if os.environ.get("TORCH_ENV") is None: + # env_p = "./.venv" + # else: + # env_p = str(os.environ.get("TORCH_ENV")) + # return os.path.abspath(env_p) @pytest.fixture @@ -35,8 +38,10 @@ def tf_env() -> str: Returns absolute path to torch virtual environment. 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== '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 < '3.11' 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 < '3.11' 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 < '3.11' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 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 < '3.11' 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 < '3.11' 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 < '3.11' 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 < '3.11' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 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 < '3.11' 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 < '3.11' 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 < '3.11' 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 < '3.11' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 == '3.11.*' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' 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 >= '3.12' and platform_system != 'Windows' and sys_platform == 'linux'", - "python_full_version >= '3.12' and platform_system != 'Windows' and sys_platform == 'linux'", - 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dependencies = [ From 166f1ec126a4e9ca715e0c3ecebd5b8186bb5569 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Thu, 28 Nov 2024 17:25:56 +0100 Subject: [PATCH 53/59] fix linting errors --- tests/conftest.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/conftest.py b/tests/conftest.py index 0ce4e90c8..dd373923c 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -8,10 +8,10 @@ # -------------------------------------------------------------------------------------- import os +from pathlib import Path import pytest -from pathlib import Path @pytest.fixture def torch_env() -> str: From 59302f5ba7f7b438dd22544ba3a6bbe01dc26b7a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 29 Nov 2024 14:28:49 +0100 Subject: [PATCH 54/59] update installation scripts for testing --- Makefile | 4 +- docs/uv-tutorial.md | 2 +- env-files/tensorflow/generic_tf.sh | 134 +- env-files/torch/generic_torch.sh | 239 +- pyproject.toml | 10 +- tests/conftest.py | 14 +- uv.lock | 8406 ---------------------------- 7 files changed, 195 insertions(+), 8614 deletions(-) delete mode 100644 uv.lock diff --git a/Makefile b/Makefile index 11f30a954..e94b7cdad 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 +44,7 @@ tf-env-vega: env-files/tensorflow/createEnvVegaTF.sh env-files/tensorflow/generi test: - PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ -m "not slurm" + PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ test-jsc: tests/run_on_jsc.sh bash tests/run_on_jsc.sh diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md index f55a7997e..379d3b641 100644 --- a/docs/uv-tutorial.md +++ b/docs/uv-tutorial.md @@ -63,7 +63,7 @@ particular, if you are a developer you would use one of the following two comman you are on HPC with cuda, you would use: ```bash -uv sync --extra torch --extra dev --extra tf \ +uv sync --extra dev --extra nvidia --extra torch --extra tf \ --no-cache \ --index https://download.pytorch.org/whl/cu121 ``` diff --git a/env-files/tensorflow/generic_tf.sh b/env-files/tensorflow/generic_tf.sh index 008839af8..1990d188d 100644 --- a/env-files/tensorflow/generic_tf.sh +++ b/env-files/tensorflow/generic_tf.sh @@ -9,89 +9,87 @@ 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:$PATH" -fi - +# if [ -z "$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:$PATH" +# fi +# # set dir cDir=$PWD # create environment if [ -d "${cDir}/$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' +source $ENV_NAME/bin/activate +pip install --no-cache-dir -e ".[dev,nvidia,tf]" + +# pip3 install --no-cache-dir --upgrade pip +# +# # get wheel -- setuptools extension +# pip3 install --no-cache-dir wheel +# +# # install TF +# if [ -f "${cDir}/$ENV_NAME/bin/tensorboard" ]; then +# echo 'TF already installed' # echo # else # if [ -z "$NO_CUDA" ]; then -# export HOROVOD_GPU=CUDA -# export HOROVOD_GPU_OPERATIONS=NCCL -# export HOROVOD_WITH_TENSORFLOW=1 -# # export TMPDIR=${cDir} +# pip3 install tensorflow[and-cuda]==2.16.* --no-cache-dir # else # # CPU only installation -# export HOROVOD_WITH_TENSORFLOW=1 -# # export TMPDIR=${cDir} +# pip3 install tensorflow==2.16.* --no-cache-dir # 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 [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -else - pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -fi - -# Install itwinai: MUST be last line of the script for the user installation script to work! -pip3 install --no-cache-dir -e .[dev] +# +# # CURRENTLY, horovod is not used with TF. Skipped. +# # # install horovod +# # if [ -f "${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 [[ "$OSTYPE" =~ ^darwin ]] ; then +# pip install "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 +# else +# pip install "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 +# fi +# +# +# # Install itwinai: MUST be last line of the script for the user installation script to work! +# pip3 install --no-cache-dir -e .[dev] diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index 78411b8d1..000705d78 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -8,24 +8,24 @@ if [ -z "$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 '$ENV_NAME' virtual env (CUDA disabled)" -fi +# if [ -z "$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 "$PIP_INDEX_TORCH_CUDA" ]; then - PIP_INDEX_TORCH_CUDA="https://download.pytorch.org/whl/cu121" -fi +# if [ -z "$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 $2}' | cut -f1-2 -d.)" - -# use pyenv if exist -if [ -d "$HOME/.pyenv" ];then - export PYENV_ROOT="$HOME/.pyenv" - export PATH="$PYENV_ROOT/bin:$PATH" -fi +# pver="$(python3 --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:$PATH" +# fi # set dir cDir=$PWD @@ -33,115 +33,114 @@ cDir=$PWD # create environment if [ -d "${cDir}/$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 +source $ENV_NAME/bin/activate +pip install -e ".[torch,tf,dev,nvidia]" \ + --no-cache-dir \ + --extra-index-url https://download.pytorch.org/whl/cu121 - if [ -z "$NO_CUDA" ]; then - # compiler vars - export LDSHARED="$CC -shared" && - export CMAKE_CXX_STANDARD=17 +# pip install --no-cache-dir --upgrade pip +# pip install --no-cache-dir packaging wheel - # CPU vars - export HOROVOD_MPI_THREADS_DISABLE=1 - export HOROVOD_CPU_OPERATIONS=MPI - - # GPU vars - export HOROVOD_GPU_ALLREDUCE=NCCL - export HOROVOD_NCCL_LINK=SHARED - export HOROVOD_NCCL_HOME=$EBROOTNCCL - fi - # Host language vars - export HOROVOD_WITH_PYTORCH=1 - export HOROVOD_WITHOUT_TENSORFLOW=1 - export HOROVOD_WITHOUT_MXNET=1 - - pip install --no-cache-dir git+https://github.com/horovod/horovod.git || exit 1 -fi - -# Install Pov4ML -if [[ "$OSTYPE" =~ ^darwin ]] ; then - pip install --no-cache-dir "prov4ml[apple,nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -else - pip install --no-cache-dir "prov4ml[nvidia]@git+https://github.com/matbun/ProvML@new-main" || exit 1 -fi - -# Install itwinai: MUST be last line of the script for the user installation script to work! -pip install --no-cache-dir -e .[torch,dev] || exit 1 \ No newline at end of file +# Adding this constraint as numpy >= 2 seems to clash with DeepSpeed +# pip install --no-cache-dir 'numpy<2.0.0' || exit 1 +# +# # install Torch +# if [ -f "${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=$EBROOTNCCL +# fi +# # Host language vars +# export HOROVOD_WITH_PYTORCH=1 +# export HOROVOD_WITHOUT_TENSORFLOW=1 +# export HOROVOD_WITHOUT_MXNET=1 +# +# pip install --no-cache-dir git+https://github.com/horovod/horovod.git || exit 1 +# fi +# +# # Install Pov4ML +# if [[ "$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 +# 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 diff --git a/pyproject.toml b/pyproject.toml index a347ac273..7cb4d6c92 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -33,8 +33,8 @@ dependencies = [ "wheel>=0.45.0", "seaborn>=0.13.2", "py-cpuinfo>=9.0.0", - "packaging>=24.2", - "pydantic>=2.9.2", + "packaging", + "pydantic", "pyyaml>=6.0.2", "omegaconf>=2.3.0", "jsonargparse[signatures]>=4.34.0", @@ -49,9 +49,9 @@ 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.*", diff --git a/tests/conftest.py b/tests/conftest.py index dd373923c..b1975f174 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -21,13 +21,8 @@ def torch_env() -> str: Returns absolute path to torch virtual environment. """ - env_path = Path(os.environ.get("TORCH_ENV", "./.venv")) + env_path = Path(os.environ.get("TORCH_ENV", "./.venv-pytorch")) return str(env_path.resolve()) - # if os.environ.get("TORCH_ENV") is None: - # env_p = "./.venv" - # else: - # env_p = str(os.environ.get("TORCH_ENV")) - # return os.path.abspath(env_p) @pytest.fixture @@ -38,10 +33,5 @@ def tf_env() -> str: Returns absolute path to torch virtual environment. 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-[[package]] -name = "zipp" -version = "3.21.0" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/3f/50/bad581df71744867e9468ebd0bcd6505de3b275e06f202c2cb016e3ff56f/zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", size = 24545 } -wheels = [ - { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 }, -] From 402598c450c4594de2251e8098a7a7ebce0a363d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 29 Nov 2024 14:50:41 +0100 Subject: [PATCH 55/59] add local test command --- Makefile | 5 ++++- tests/use-cases/test_3dgan.py | 10 ++-------- tests/use-cases/test_cyclones.py | 13 ++++++------- tests/use-cases/test_mnist.py | 15 +++++---------- 4 files changed, 17 insertions(+), 26 deletions(-) diff --git a/Makefile b/Makefile index e94b7cdad..e03a75793 100644 --- a/Makefile +++ b/Makefile @@ -44,7 +44,10 @@ tf-env-vega: env-files/tensorflow/createEnvVegaTF.sh env-files/tensorflow/generi test: - PYTORCH_ENABLE_MPS_FALLBACK=1 .venv/bin/pytest -v tests/ + .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/tests/use-cases/test_3dgan.py b/tests/use-cases/test_3dgan.py index c813522ae..b7968a2a9 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 b8b1c64d5..c05e3d639 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 98e0d9432..7d6fe753b 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) From 93af26349626d85f2d4f60eea982a91cd7bcffdc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 29 Nov 2024 15:12:51 +0100 Subject: [PATCH 56/59] add tf to installation in readme --- README.md | 4 +- uv.lock | 8438 +++++++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 8440 insertions(+), 2 deletions(-) create mode 100644 uv.lock diff --git a/README.md b/README.md index 62e1dfd4f..778a15ae5 100644 --- a/README.md +++ b/README.md @@ -180,7 +180,7 @@ directory, as you can very easily reach your disk quota otherwise. An example of complete command for installing as a developer on HPC with CUDA thus becomes: ```bash -pip install -e ".[torch,dev,nvidia]" \ +pip install -e ".[torch,dev,nvidia,tf]" \ --no-cache-dir \ --extra-index-url https://download.pytorch.org/whl/cu121 ``` @@ -189,7 +189,7 @@ If you wanted to install this locally on macOS (i.e. without CUDA) with PyTorch, would do the following instead: ```bash -pip install -e ".[torch,dev,macos]" +pip install -e ".[torch,dev,macos,tf]" ``` diff --git a/uv.lock b/uv.lock new file mode 100644 index 000000000..63350ce37 --- /dev/null +++ b/uv.lock @@ -0,0 +1,8438 @@ +version = 1 +requires-python = ">=3.10" +resolution-markers = [ + "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 < '3.11' and 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PnetCDF libaio mpi4py git Clang source .venv/bin/activate -bash install-horovod-deepspeed-cuda.sh +source env-files/torch/install-horovod-deepspeed-cuda.sh diff --git a/pyproject.toml b/pyproject.toml index 7cb4d6c92..73af1099e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -107,6 +107,7 @@ markers = [ "memory_heavy: high memory footprint. 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"https://pypi.org/simple" }, marker = "platform_system != 'Windows'" }, ] wheels = [ - { url = "https://files.pythonhosted.org/packages/ca/31/ff6be541195daf77aa5c72303b2354661a69e717967d44d91eb4f3fdce32/triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:38806ee9663f4b0f7cd64790e96c579374089e58f49aac4a6608121aa55e2505", size = 63268585 }, - { url = "https://files.pythonhosted.org/packages/b7/cd/4aa0179919306f9c2e3e5308f269d20c094b2a4e2963b656e9405172763f/triton-2.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:226941c7b8595219ddef59a1fdb821e8c744289a132415ddd584facedeb475b1", size = 63278135 }, + { url = "https://files.pythonhosted.org/packages/4d/22/91a8af421c8a8902dde76e6ef3db01b258af16c53d81e8c0d0dc13900a9e/triton-2.1.0-0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:66439923a30d5d48399b08a9eae10370f6c261a5ec864a64983bae63152d39d7", size = 89215103 }, + { url = "https://files.pythonhosted.org/packages/5c/c1/54fffb2eb13d293d9a429fead3646752ea190de0229bcf3d591ba2481263/triton-2.1.0-0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:919b06453f0033ea52c13eaf7833de0e57db3178d23d4e04f9fc71c4f2c32bf8", size = 89234153 }, ] [[package]] @@ -8082,17 +8894,41 @@ name = "triton" version = "3.0.0" source = { registry = "https://pypi.org/simple" } 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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != '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 != 'Windows' and sys_platform == 'linux'", ] dependencies = [ From d02a9cfd2fd642e3ee2535a0fb2a47d1803add89 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Fri, 29 Nov 2024 17:40:02 +0100 Subject: [PATCH 58/59] remove index from tutorial --- docs/uv-tutorial.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md index 379d3b641..6722207c5 100644 --- a/docs/uv-tutorial.md +++ b/docs/uv-tutorial.md @@ -63,9 +63,7 @@ particular, if you are a developer you would use one of the following two comman you are on HPC with cuda, you would use: ```bash -uv sync --extra dev --extra nvidia --extra torch --extra tf \ - --no-cache \ - --index https://download.pytorch.org/whl/cu121 +uv sync --extra dev --extra nvidia --extra torch --extra tf --no-cache ``` If you are developing on your local computer with macOS, then you would use: From 08d8d744f53502ef5ff185e35cfa7a432eebf984 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jarl=20Sondre=20S=C3=A6ther?= <60541573+jarlsondre@users.noreply.github.com> Date: Mon, 2 Dec 2024 09:45:39 +0100 Subject: [PATCH 59/59] remove unused comments and update tutorial --- docs/uv-tutorial.md | 2 +- env-files/tensorflow/generic_tf.sh | 85 +---------- env-files/torch/generic_torch.sh | 136 +----------------- .../torch/install-horovod-deepspeed-cuda.sh | 6 +- 4 files changed, 14 insertions(+), 215 deletions(-) diff --git a/docs/uv-tutorial.md b/docs/uv-tutorial.md index 6722207c5..fc240e2a0 100644 --- a/docs/uv-tutorial.md +++ b/docs/uv-tutorial.md @@ -63,7 +63,7 @@ particular, if you are a developer you would use one of the following two comman you are on HPC with cuda, you would use: ```bash -uv sync --extra dev --extra nvidia --extra torch --extra tf --no-cache +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: diff --git a/env-files/tensorflow/generic_tf.sh b/env-files/tensorflow/generic_tf.sh index 1990d188d..0b5d216e0 100644 --- a/env-files/tensorflow/generic_tf.sh +++ b/env-files/tensorflow/generic_tf.sh @@ -1,95 +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:$PATH" -# fi -# -# set dir -cDir=$PWD +work_dir=$PWD -# create environment -if [ -d "${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" else python3 -m venv $ENV_NAME - echo "$ENV_NAME environment is created in ${cDir}" + echo "$ENV_NAME environment is created in ${work_dir}" fi source $ENV_NAME/bin/activate pip install --no-cache-dir -e ".[dev,nvidia,tf]" - -# pip3 install --no-cache-dir --upgrade pip -# -# # get wheel -- setuptools extension -# pip3 install --no-cache-dir wheel -# -# # install TF -# if [ -f "${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 -# fi -# -# -# # Install itwinai: MUST be last line of the script for the user installation script to work! -# pip3 install --no-cache-dir -e .[dev] diff --git a/env-files/torch/generic_torch.sh b/env-files/torch/generic_torch.sh index 000705d78..ac80b9f11 100644 --- a/env-files/torch/generic_torch.sh +++ b/env-files/torch/generic_torch.sh @@ -1,146 +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 +work_dir=$PWD -# if [ -z "$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 $2}' | cut -f1-2 -d.)" -# -# # use pyenv if exist -# if [ -d "$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" else python3 -m venv $ENV_NAME - echo "$ENV_NAME environment is created in ${cDir}" + echo "$ENV_NAME environment is created in ${work_dir}" fi +# Activate the venv and then install itwinai as editable source $ENV_NAME/bin/activate pip install -e ".[torch,tf,dev,nvidia]" \ --no-cache-dir \ --extra-index-url https://download.pytorch.org/whl/cu121 - -# pip install --no-cache-dir --upgrade pip -# pip install --no-cache-dir packaging wheel - -# Adding this constraint as numpy >= 2 seems to clash with DeepSpeed -# pip install --no-cache-dir 'numpy<2.0.0' || exit 1 -# -# # install Torch -# if [ -f "${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=$EBROOTNCCL -# fi -# # Host language vars -# export HOROVOD_WITH_PYTORCH=1 -# export HOROVOD_WITHOUT_TENSORFLOW=1 -# export HOROVOD_WITHOUT_MXNET=1 -# -# pip install --no-cache-dir git+https://github.com/horovod/horovod.git || exit 1 -# fi -# -# # Install Pov4ML -# if [[ "$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 -# 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 diff --git a/env-files/torch/install-horovod-deepspeed-cuda.sh b/env-files/torch/install-horovod-deepspeed-cuda.sh index 9283fdf86..f596ae83e 100755 --- a/env-files/torch/install-horovod-deepspeed-cuda.sh +++ b/env-files/torch/install-horovod-deepspeed-cuda.sh @@ -11,7 +11,7 @@ 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.*" +pip install --no-cache-dir --no-build-isolation "deepspeed==0.15.*" || exit 1 # Horovod variables export LDSHARED="$CC -shared" && @@ -28,4 +28,6 @@ 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' +pip install --no-cache-dir 'horovod[pytorch] @ git+https://github.com/horovod/horovod' || exit 1 + +echo "Finished Horovod and DeepSpeed installation script!"